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1
Takalani, Rofhiwa Lutendo Edward, and Lesedi Masisi. "Development of An Optimal Port Crane Trajectory for Reduced Energy Consumption." Energies 16, no. 20 (2023): 7172. http://dx.doi.org/10.3390/en16207172.
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This paper is concerned with the development of an optimal load-handling trajectory for port cranes. The objective is to minimize load cycle time and reduce energy consumption. Energetic macroscopic representation formalism is used to model a port crane load-handling mechanism. The crane model developed includes the mathematical model, the crane’s local control system, and a MATLAB/Simulink model for simulation. The particle swarm optimization algorithm is used to find the set of pareto optimal crane trajectories given the variation in crane size, ship size, and wind speed. Experimental validation of the crane model is conducted by comparing it with a real-world crane. Simulation results show that the optimal crane load trajectory is 38% faster and more productive than the nonoptimal crane load trajectory. Furthermore, the results show that the optimal trajectory reduces the cranes’ peak power and energy consumption by 36% when compared with the nonoptimal trajectory.
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Sayfullin, Askar Aidarovich. "ANALYTICAL TOOL DEVELOPMENT FOR DEREMINING THE OPTIMAL WELL TRAJECTORY." Nauka Innovatsii Tekhnologii, no. 3 (2022): 47–74. http://dx.doi.org/10.37493/2308-4758.2022.3.3.
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Han, Yun-xiang, Xiao-qiong Huang, and Xin-min Tang. "Development of a new tool for constrained conflict resolution." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 5 (2018): 1683–94. http://dx.doi.org/10.1177/0954410018760356.
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In this paper, the problem of finding the optimal trajectory of an aircraft through a specified airspace for a given start and goal position is put forward. The application of sequential programming to optimal trajectory generation is reported with the selection of the grid size and the space boundaries. A totally discrete approach is adopted in contrast to the other models, which use continuous time but resort to diseretization in the computation. The component of the mathematical formulation of the optimization criteria is considered and the procedures used within the control algorithm on the solution are also proposed. Realistic constraints such as turning rate and spatial layout are incorporated into the system model building before applying the sequential programming technique to be used in solving the problem. Simulation examples for multiple aircrafts are presented to demonstrate the use of the proposed trajectory planner and certain optimal control inputs have been acquired.
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Gui, Xuhao, Junfeng Zhang, Xinmin Tang, and Jie Bao. "Improved Data-Driven Trajectory Optimization Method Utilizing Deep Trajectory Generation." Journal of Aerospace Information Systems 22, no. 1 (2025): 28–42. https://doi.org/10.2514/1.i011418.
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The imbalance between air traffic capacity and demand, especially in the terminal maneuvering area, constrains the development of the civil aviation industry. To enhance the capacity, providing aircraft with optimal trajectories is the way forward. The key challenge of building a trajectory optimization model lies in embedding air traffic controllers’ operation experience into the optimization process. Previous efforts proposed a data-driven trajectory optimization method to learn operation experience from historical data for trajectory optimization use, which is limited by the issues of insufficient quantity and diversity of trajectory data. To solve those issues, an improved model is proposed to further improve the trajectory optimization performance. Firstly, this paper exploited a connecting-based trajectory generation model to generate massive synthetic trajectories. Then, this paper used a data-mining-based valuable trajectory identification technique to find valuable trajectories that can be used to enrich its operation experience. A case study on Guangzhou Baiyun International Airport was conducted to verify the proposed method. The results show that the proposed model successfully incorporates more operation experience during the optimization process. Compared with the benchmark model, the proposed model can adapt to more complex air traffic and provide optimal trajectories for more incoming aircraft.
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Yoo, Hyun-Seok, Jeong-Ho Lee, and Young-Suk Kim. "Development of an Optimal Trajectory Planning Algorithm for Automated Pavement Crack Sealer." Korean Journal of Construction Engineering and Management 11, no. 4 (2010): 68–79. http://dx.doi.org/10.6106/kjcem.2010.11.4.68.
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Hu, Lin, Jie Wang, Jing Huang, Pak Kin Wong, and Jing Zhao. "Lane Change Trajectory Planning for Intelligent Electric Vehicles in Dynamic Traffic Environments: Aiming at Optimal Energy Consumption." Sustainability 17, no. 9 (2025): 4235. https://doi.org/10.3390/su17094235.
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With the reduction in battery costs and the widespread application of artificial intelligence, the adoption of new-energy vehicles is accelerating. Integrating energy consumption optimization into the process of intelligent development is of great significance for sustainable development. This paper, considering the regenerative braking characteristics of electric vehicles and the time-varying nature of surrounding obstacle vehicles during lane changes, proposes a segmented real-time trajectory-planning method combining optimal control and quintic polynomials. At the beginning of the lane change, a safe intermediate position is calculated based on the speed and position information of the ego vehicle and the leading obstacle vehicle in the current lane. The trajectory optimization problem from the starting point to the intermediate position is formulated as an optimal control problem, resulting in the first segment of the trajectory. Upon reaching the intermediate position, the endpoint range is determined based on the speed and position information of the leading and trailing obstacle vehicles in the target lane. Multiple trajectories are then generated using quintic polynomials, and the optimal trajectory is selected as the second segment of the lane-changing trajectory. Experimental results from a driving simulator show that the proposed method can reduce energy consumption by approximately 40%.
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Ketova, K., I. Rusyak, and R. Sedov. "Addressing the Problem of Regional Socio-economic System Management With a Manpower Effective Volume Taken Into Account." Bulletin of Science and Practice 6, no. 7 (2020): 10–25. http://dx.doi.org/10.33619/2414-2948/56/01.
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In the paper, a problem of regional socio-economic system management is solved, as exemplified by one of Russia’s regions. An optimal management algorithm is created, with an effective capacity of the workforce taken into account. The statement of the problem is implemented based on a regional economic system macro model, with an effective capacity of a labor force and a physical capital to be viewed as development factors. The underscore preliminary proposition of the model is the fact that labor force effective capacity consists of both qualitative (labor productivity of a worker) and quantitative (labor pool) properties. The product is distributed into consumption, capital widening and sustainment investments, and regional socio-educational development potential. The qualitative property of the workforce is derived from these socio-educational potential investments. Adding a workforce effective capacity factor to the model is the key feature of the management problem statement. The problem-solving algorithm comprises two stages: building an objective optimal balanced growth trajectory and building an optimal trajectory of socio-economic system motion which would propel it to the balanced growth trajectory. The time of transitional period up to reaching an objective balanced growth trajectory can be changed by varying build-up rates of a socio-educational potential. The paper is first to use a two-factor approach in building an optimal investment distribution to solve the problem of socio-economic system management with a workforce effective capacity taken into consideration. Data on demography and volume of investments in educational, production, and social fields of the Udmurt Republic served as an information base of the model. Due to identify unknown parameters of the model, the data as of 2000-2019 was used. Optimal investment rates were calculated which would enable the socio-economic system to reach a balanced growth trajectory by the year 2025. The suggested method can also be used for building a development trajectory for a given socio-economic system, as well as for handling parametrical model calculations to determine their factors.
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Ketova, K., I. Rusyak, and R. Sedov. "Addressing the Problem of Regional socio-economic System Management with a manpower effective volume taken into account." Bulletin of Science and Practice 6, no. 7 (2020): 10–25. https://doi.org/10.33619/2414-2948/56/01.
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In the paper, a problem of regional socio-economic system management is solved, as exemplified by one of Russia’s regions. An optimal management algorithm is created, with an effective capacity of the workforce taken into account. The statement of the problem is implemented based on a regional economic system macro model, with an effective capacity of a labor force and a physical capital to be viewed as development factors. The underscore preliminary proposition of the model is the fact that labor force effective capacity consists of both qualitative (labor productivity of a worker) and quantitative (labor pool) properties. The product is distributed into consumption, capital widening and sustainment investments, and regional socio-educational development potential. The qualitative property of the workforce is derived from these socio-educational potential investments. Adding a workforce effective capacity factor to the model is the key feature of the management problem statement. The problem-solving algorithm comprises two stages: building an objective optimal balanced growth trajectory and building an optimal trajectory of socio-economic system motion which would propel it to the balanced growth trajectory. The time of the transitional period up to reaching an objective balanced growth trajectory can be changed by varying build-up rates of a socio-educational potential. The paper is first to use a two-factor approach in building an optimal investment distribution to solve the problem of socio-economic system management with a workforce effective capacity taken into consideration. Data on demography and volume of investments in educational, production, and social fields of the Udmurt Republic served as an information base of the model. Due to identify unknown parameters of the model, the data as of 2000-2019 was used. Optimal investment rates were calculated which would enable the socio-economic system to reach a balanced growth trajectory by the year 2025. The suggested method can also be used for building a development trajectory for a given socio-economic system, as well as for handling parametrical model calculations to determine their factors.
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Lysenko, O. I., V. L. Shevchenko, O. M. Tachynina, S. O. Ponomarenko, and O. H. Guida. "Structure of the algorithm for modeling optimal movement of a compound dynamic system." PROBLEMS IN PROGRAMMING, no. 2-3 (September 2024): 69–77. https://doi.org/10.15407/pp2024.02-03.069.
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The work is devoted to the development of the structure of the algorithm for modeling the optimal movement of complex dynamic systems (SDS) along a branched trajectory. Complex systems are called systems consisting of separate subsystems, the flight trajectories of which differ and are called branched. Branched trajectories should consist of trajectory segments, the first of which will be common to the entire SDS, and the other trajectory branches will be different, as each subsystem moves to its goal along its own trajectory segment. The proposed algorithm makes it possible to optimize such trajectories in real time and to carry out operational correction of SDS trajectories in the event of the occurrence of unpredictable influencing factors. It is known that the effectiveness of the SDS functioning between structural transformations depends on the coordinates of the mutual location and speed of each subsystem and the choice of optimal moments of time for structural transformations. The efficiency of determining these parameters during the flight is fundamentally important. The necessary conditions for the optimality of the trajectory of the SDS movement are found, which are universal for problems with any finite number of trajectory branches. The implementation of the proposed conditions will allow to reduce the number of computational procedures in the control calculations in conditions of uncertainty of the initial conditions. These conditions are the methodological basis for the development of computational algorithms for modeling the optimal trajectories of the SDS movement. The necessary optimality conditions have a clear physical meaning and are technological and user-friendly. The results of the research presented in the article are important and relevant for the construction of the laws of trajectory control of existing and prospective SDS.
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Nguyen, Ngoc-Duc, Mai The Vu, Phi Nguyen, et al. "Time-Optimal Trajectory Design for Heading Motion of the Underwater Vehicle." Journal of Marine Science and Engineering 11, no. 6 (2023): 1099. http://dx.doi.org/10.3390/jmse11061099.
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Underwater vehicles are a powerful tool that can assist oceanologists with measuring the state of oceans on a large scale. The heading control is essential for the underwater vehicle to follow a specific path. This study describes the general decoupled dynamics of underwater vehicles, which is a nonlinear second-order differential equation considering linear and quadratic damping hydrodynamics. A novel aspect of this study is the development of a new analytical solution for the second-order nonlinear differential equation, which involves the heading motion of the underwater vehicle. In this study, the time-optimal trajectory is formulated as the closed-form solution for the heading dynamics of the underwater vehicle. The concept of this trajectory is based on the shortest arrival time when the maximum force from the thrusters is applied to the underwater vehicle. Finally, a simulation of the time-optimal trajectory and evaluation of the robustness of the controller were demonstrated in order to verify the effectiveness of the proposed trajectory for controlling underwater vehicles.
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BANNOVA, Kristina A., and Yulia G. TYURINA. "OPTIMAL TAX TRAJECTORIES OF THE KAZAKHSTAN LARGEST COMPANIES." Tyumen State University Herald. Social, Economic, and Law Research 6, no. 4 (2020): 279–94. http://dx.doi.org/10.21684/2411-7897-2020-6-4-279-294.
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The agro-industrial complex of any country forms its food and economic security; it also acts as a guarantor of sustainable development of the socio-economic system. Today, one of the components of the agro-industrial complex, agriculture, contributes to the implementation of a number of life-supporting functions of the state. Thus, due to its geographical location and vast territories, agriculture is one of the most important types of economic activity in Kazakhstan. The current stage of the country’s economic activity is closely related to the development of the fuel and energy industry. The key factor in the development of the industry is a company’s tax strategy. This article features an analysis of the main large companies of Kazakhstan (Svetland-Oil, Kazgermunai, Potentsial Oil, South Oil, Karatau, Mangistaumunaigas, Katko, Kazburgas, Adzhip Karachaganak), which was performed in order to determine an effective tax policy and increase the capacity of enterprises. The authors have implemented a numerical study of the company’s tax trajectory. Using the Cobb-Douglas model, they describe the production function of companies. The choice of the model coefficients is due to the agreement of the calculation results with the official data. As a result of taking into account the optimization of the tax trajectory, an increase in fixed assets in the time range of 2008-2017 has been revealed. The authors assume that taking into account the effect of optimization of the tax trajectory will allow increasing the efficiency of distribution of financial and production resources of companies.
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Lee, Jae Kwan. "Transformer-Based Vehicle-Trajectory Prediction at Urban Low-Speed T-Intersection." Sensors 25, no. 14 (2025): 4256. https://doi.org/10.3390/s25144256.
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Transformer-based models have demonstrated outstanding performance in trajectory prediction; however, their complex architecture demands substantial computing power, and their performance degrades significantly in long-term prediction. A transformer model was developed to predict vehicle trajectory in urban low-speed T-intersections. Microscopic traffic simulation data were generated to train the trajectory-prediction model; furthermore, validation data focusing on atypical scenarios were also produced. The appropriate loss function to improve prediction accuracy was explored, and the optimal input/output sequence length for efficient data management was examined. Various driving-characteristics data were employed to evaluate the model’s generalization performance. Consequently, the smooth L1 loss function showed outstanding performance. The optimal length for the input and output sequences was found to be 1 and 3 s, respectively, for trajectory prediction. Additionally, improving the model structure—rather than diversifying the training data—is necessary to enhance generalization performance in atypical driving situations. Finally, this study confirmed that the additional features such as vehicle position and speed variation extracted from the original trajectory data decreased the model accuracy by about 21%. These findings contribute to the development of applicable lightweight models in edge computing infrastructure to be installed at intersections, as well as the development of a trajectory prediction and accident analysis system for various scenarios.
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Zhang, Xiaolong, Yu Huang, Youmin Rong, Gen Li, Hui Wang, and Chao Liu. "Optimal Trajectory Planning for Wheeled Mobile Robots under Localization Uncertainty and Energy Efficiency Constraints." Sensors 21, no. 2 (2021): 335. http://dx.doi.org/10.3390/s21020335.
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With the rapid development of robotics, wheeled mobile robots are widely used in smart factories to perform navigation tasks. In this paper, an optimal trajectory planning method based on an improved dolphin swarm algorithm is proposed to balance localization uncertainty and energy efficiency, such that a minimum total cost trajectory is obtained for wheeled mobile robots. Since environmental information has different effects on the robot localization process at different positions, a novel localizability measure method based on the likelihood function is presented to explicitly quantify the localization ability of the robot over a prior map. To generate the robot trajectory, we incorporate localizability and energy efficiency criteria into the parameterized trajectory as the cost function. In terms of trajectory optimization issues, an improved dolphin swarm algorithm is then proposed to generate better localization performance and more energy efficiency trajectories. It utilizes the proposed adaptive step strategy and learning strategy to minimize the cost function during the robot motions. Simulations are carried out in various autonomous navigation scenarios to validate the efficiency of the proposed trajectory planning method. Experiments are performed on the prototype “Forbot” four-wheel independently driven-steered mobile robot; the results demonstrate that the proposed method effectively improves energy efficiency while reducing localization errors along the generated trajectory.
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Zakharchenko, V. I., and S. V. Oneshko. "Clarification of the Formalization Process for Models of Economic Dynamics in the Study of the Development of Organizational and Technological Systems." HERALD OF THE ECONOMIC SCIENCES OF UKRAINE, no. 1(42) (2022): 57–63. http://dx.doi.org/10.37405/1729-7206.2022.1(42).57-63.
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The article substantiates the creation and practical development of organizational and technological systems in high-tech production on the basis of the main theory and solution of linear programming problems. The main problem when using models of economic dynamics in creating this type of system is the large dimension of the emerging optimization problems, which prevents the direct use of known computational procedures for solving linear programming problems. To do this, we consider an extreme problem for direct dynamic analysis of the Leontief model using the standard linear programming problem. At the same time, we should not forget about the problem of determining the target functional, the choice of which prevents the choice of the optimal trajectory of development of the simulated system. Due to these difficulties, the need for quality research methods of optimal trajectories to obtain theoretical conclusions for making scientifically sound planning decisions is determined. Theorems on highways describe the qualities of invariance of optimal trajectories of extreme dynamic problems in relation to the purpose of the target functional and to the choice of the optimal trajectory. The theoretical generalizations of Samuelson’s main theory were used in a consulting project on planned studies of the introduction of organizational and technological system for the production of high-tech products at a machine-building enterprise. Keywords system, technology, technology, highway, model, trajectory, programming, functional, vector, function, matrix.
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Yoo, Hyun-Seok, and Young-Suk Kim. "Development of an Optimal Trajectory Planning Algorithm for an Automated Pavement Crack Sealer." Journal of Construction Engineering and Project Management 2, no. 1 (2012): 35–44. http://dx.doi.org/10.6106/jcepm.2012.2.1.035.
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Diao, X. D., S. X. Zeng, and Vivian W. Y. Tam. "Development of an optimal trajectory model for spray painting on a free surface." Computers & Industrial Engineering 57, no. 1 (2009): 209–16. http://dx.doi.org/10.1016/j.cie.2008.11.010.
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Llopis-Albert, Carlos, Francisco Rubio, and Francisco Valero. "Optimization approaches for robot trajectory planning." Multidisciplinary Journal for Education, Social and Technological Sciences 5, no. 1 (2018): 1. http://dx.doi.org/10.4995/muse.2018.9867.
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<p class="Textoindependiente21">The development of optimal trajectory planning algorithms for autonomous robots is a key issue in order to efficiently perform the robot tasks. This problem is hampered by the complex environment regarding the kinematics and dynamics of robots with several arms and/or degrees of freedom (dof), the design of collision-free trajectories and the physical limitations of the robots. This paper presents a review about the existing robot motion planning techniques and discusses their pros and cons regarding completeness, optimality, efficiency, accuracy, smoothness, stability, safety and scalability.</p>
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Xu, Hanwen, Wengen Gao, Jiaming Zhu, and Guoqing Zhang. "Time-optimal trajectory planning for manipulator based on an improved sparrow search algorithm." Journal of Physics: Conference Series 2816, no. 1 (2024): 012056. http://dx.doi.org/10.1088/1742-6596/2816/1/012056.
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Abstract With the development of industrial automation, it is crucial to use manipulators for efficient painting. To solve the problem of inefficient trajectory planning of manipulators in the point-to-point painting process, this paper proposes a time-optimal trajectory planning method based on an improved sparrow search algorithm. Initially, the standard D-H parameter method is used to establish the kinematic model of the manipulator. To ensure the continuity of each joint in the manipulator, a 3-5-3 polynomial interpolation function is utilized to construct the motion trajectory in joint space. Subsequently, the improved sparrow search algorithm is utilized to optimize the point-to-point motion trajectory of the manipulator with a constraint on motion time. Finally, simulations carried out in MATLAB demonstrated that the manipulator, which was optimized by using the improved sparrow search algorithm, exhibited a significant increase in motion efficiency compared to its pre-optimization state. Additionally, the movements of the manipulator’s joints were smooth.
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Kirillova, L. G., and G. A. Khismatullin. "DEVELOPMENT OF THE MOTIVATIONAL POTENTIAL OF EMPLOYEES." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 12/6, no. 153 (2024): 207–13. https://doi.org/10.36871/ek.up.p.r.2024.12.06.027.
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In modern companies, the development of the motivational potential of employees creates conditions for achieving the company’s strategic goals, promotes employee involvement in production processes for improvements, and increases labor productivity. The use of various forms of tariff-free remuneration allows you to choose the most optimal option for financial incentives for staff, make the motivation system transparent to all staff, and make the career trajectory of employees more predictable.
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Likhter, Pavel L. "The Externalist Trajectory of the Development of Law: Utilitarianism or Eudemonism?" History of state and law 1 (January 28, 2021): 23–29. http://dx.doi.org/10.18572/1812-3805-2021-1-23-29.
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The article examines the importance of externalist and internalist approaches for the formation of an optimal strategy for the development of legal science in modern conditions. Some aspects of interaction of law with economics, ethics, politics and other spheres of public relations are considered. Special attention is paid to the influence of eudaimonism, utilitarianism and other consequential concepts on the legal institutions. It is concluded that the externalist path of development is promising, provided that the narrow utilitarian realization of the ideals and economic prerequisites of consumer capitalism is abandoned.
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Li, Huifang, and Dariusz Ceglarek. "Optimal Trajectory Planning For Material Handling of Compliant Sheet Metal Parts." Journal of Mechanical Design 124, no. 2 (2002): 213–22. http://dx.doi.org/10.1115/1.1463035.
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One of the most critical issues in the material handling of compliant objects is excessive part deformation. The deformation of compliant sheet metal parts during the handling process can significantly impact both part dimensional quality and production rate. Increasing production rate while maintaining part quality requires an optimal design of the part transfer trajectory. This paper describes a new methodology of time-optimal trajectory planning for compliant parts by discretizing the part transfer path into N segments that have equal horizontal distance and by approximating the trajectory as having piecewise constant acceleration that can only change its value at the end of each segment. The contribution of the methodology is that part deformation determined by transfer velocity and acceleration is considered as a nonlinear constraint, which is obtained from FEA simulation and model fitting. Part permanent deformation, trajectory smoothness, and static obstacle avoidance are also considered. The methodology is validated by simulations at different motion conditions and obstacle configurations. This paper addresses the lack of current design guidelines for material handing development and simultaneously provides a mathematical tool to significantly enhance the production efficiency in manufacturing of compliant sheet metal parts.
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Igor, Lutsenko, Oksanych Аnatolii, Fomovskaya Olena, Oksanych Iryna, Mospan Denis, and Serdiuk Olga. "DEVELOPMENT OF A METHOD FOR DETERMINING THE OPTIMAL CONTROL TRAJECTORY FOR THE PERIODIC PROCESSES." EUREKA: Physics and Engineering, no. 3 (August 29, 2019): 59–68. https://doi.org/10.21303/2461-4262.2019.00900.
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The development of new converting technologies and increasing the level of automation leads to an increase in the processing speed of available resources. This means that in case of inefficient or inefficient use of resources, the potential of economic advantage is lost, and the negative consequences of such losses can be identified too late. In such conditions, the requirements for the selection of the criterion of optimization and the validity of the principles of optimal control increase. Moreover, the approach used may vary depending on the daily change in prices for energy products and fluctuations in the level of demand for manufactured products. Despite the fact that such an approach seems obvious, today energy-intensive production suffers significant losses associated with the use of an inadequate model of technological operation, a subjective approach to the choice of optimization criterion and optimization method. The task of developing a method for determining the optimal trajectory of managing energy-intensive industries with a changing level of demand for final products is posed. The solution to this problem consists of several stages. At the first stage, a model of a technological operation is being created, within the framework of which all significant factors affecting the decision result are taken into account. At the second stage, a global operation model is created, the input and output products of which are converted to comparable value values. At the third stage, the optimization criterion for the continuous operation of the system and the mode of incomplete use of its production capabilities is selected. At the final stage, the control path for intermittent and continuous modes of operation is determined. Thus, the aim of research is development of a method for determining the optimal control trajectory in systems of energy-intensive systems, depending on the level of demand for the final product.
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Filippova, Maryna, Mariia Demchenko, Denis Smolnikov, Natalia Bezuglaya та Halina Bohdan. "Використання систем автоматизованого проектування для підвищення точності механічної обробки". Aerospace Technic and Technology, № 2 (24 квітня 2023): 27–37. http://dx.doi.org/10.32620/aktt.2023.2.03.
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The subject of the study is methods and means of determining the influence of the trajectory of the tool on the foreground of the volume of complex parts. The aim is to improve the quality and accuracy of the production of composite profile parts after machining at CNC machining centers, by using the optimal machining strategy. Task: to analyze existing methods of processing complex profile parts at CNC processing centers and justify the choice of the optimal strategy for the side of the surface of the part. The methods used are: methods of controlling the accuracy of processing complex surfaces, graphical methods of forming the trajectory of the tool, and mechanical methods of measuring geometric dimensions. The results obtained are as follows. To achieve this goal, an analysis of existing methods and strategies for processing surfaces of a complex profile was carried out and the existing experience in the development of control programs was adapted using automated methods with the application of CAD/CAM systems. As a result, SolidWorks was chosen as the primary modeling tool for creating a part with a complex profile. The tool path is created using the SolidCAM CAM system, which supports various strategies for processing such elements. Using the developed control programs based on the methods of linear trajectory, bitmap trajectory, spiral trajectory, and waterline trajectory, experimental analysis of the influence of the tool trajectory on the accuracy of processing surfaces located at different angles to the processing axis was carried out. Deviations of geometrical dimensions of parts obtained in re-treatment by programs formed using different methods from the real values of model characteristics are evaluated. Conclusions. Based on the analysis of the strategies for processing parts of a complex profile, the optimal trajectories of the tool are determined for parts with surfaces such as at a low angle, at a high angle, radius surface, and joints between surfaces. The results of experimental studies in further shaping of folding parts when they are prepared on CNC machine with the choice of the optimal trajectory of the movement of the tool. The choice of the optimal trajectory of the processing of parts allows to increase the accuracy of the processing in finishing operations.
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Potter, Harold, John Kern, Guillermo Gonzalez, and Claudio Urrea. "Energetically Optimal Trajectory for a Redundant Planar Robot by Means of a Nested Loop Algorithm." Elektronika ir Elektrotechnika 28, no. 2 (2022): 4–17. http://dx.doi.org/10.5755/j02.eie.30397.
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This work presents an optimal point-to-point trajectory planning method based on fourth degree polynomials to reduce the energy consumption of a redundant planar robot in the XY plane. The contribution of this study focuses on the development of a two-level nested optimization algorithm, which manages to optimize three elements: the Optimal Weighting Vector that establishes the influence of each joint on the total energy consumption of the robotic equipment; the optimal start and finish configurations of the trajectory; and the vector corresponding to the fifth coefficient of the trajectory generator polynomial. The tests are carried out with different optimization techniques and objective functions related to energy consumption to determine their best combination and achieve the minimum possible computation time and energy savings, according to the test conditions used. Furthermore, the energetic performance of the redundant manipulator is compared with its non-redundant version, limiting its operation to only two degrees of freedom in all its variants.
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Novrianti, Novrianti, Rycha Melisa, and Rafhie Adrian. "Kick-Off Point (KOP) and End of Buildup (EOB) Data Analysis in Trajectory Design." Journal of Geoscience, Engineering, Environment, and Technology 2, no. 2 (2017): 133. http://dx.doi.org/10.24273/jgeet.2017.2.2.302.
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Well X is a development well which is directionally drilled. Directional drilling is choosen because the coordinate target of Well X is above the buffer zone. The directional track plan needs accurate survey calculation in order to make the righ track for directional drilling. There are many survey calculation in directional drilling such as tangential, underbalance, average angle, radius of curvature, and mercury method. Minimum curvature method is used in this directional track plan calculation. This method is used because it gives less error than other method. Kick-Off Point (KOP) and End of Buildup (EOB) analysis is done at 200 ft, 400 ft, and 600 ft depth to determine the trajectory design and optimal inclination. The hole problem is also determined in this trajectory track design. Optimal trajectory design determined at 200 ft depth because the inclination below 35º and also already reach the target quite well at 1632.28 ft TVD and 408.16 AHD. The optimal inclination at 200 ft KOP depth because the maximum inclination is 18.87º which is below 35º. Hole problem will occur if the trajectory designed at 600 ft. The problems are stuck pipe and the casing or tubing will not able to bend.
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Zakharova, K. A., and D. A. Muravev. "Mathematical modeling of the optimal tax trajectory of a commercial organization." MIR (Modernization. Innovation. Research) 15, no. 4 (2025): 607–24. https://doi.org/10.18184/2079-4665.2024.15.4.607-624.
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Purpose: is to develop the mathematical model for quantitative assessment of the tax burden by building the tax trajectory of a commercial organization as the tool for optimizing tax payments.Methods: the presented concept is developed on the basis of mathematical modeling of related economic processes concerning the formation of the tax base of the large economic entity. The model is based on a differential equation that determines the dynamics of fixed assets in relation to the selected optimal tax trajectory of the company.Results: the authors propose an approach to the calculation of tax payments based on the construction of the optimal tax trajectory of an economic entity. The analysis of the impact of building the optimal tax trajectory on the efficiency of the organization’s activity was carried out. In this context, the number of principles for the construction of the optimal tax trajectory of the company are formed, allowing to take into account the interests of the taxpayers and the state in terms of the efficiency of resource allocation and stable budget replenishment. It’s revealed that in order to replenish the revenue part of the budget it’s possible to increase the tax burden of an economic entities, which doesn’t affect their financial position.Conclusions and Relevance: the proposed approach expands the instrumental apparatus for calculating tax payments from the position of both taxpayers and fiscal authorities. The construction of the optimal tax trajectory contributes to the adoption of targeted decisions regarding the increase or decrease of the tax burden of an economic entity in mutual accounting with the factors of the macroeconomic situation. This approach allows both to manage the revenue part of the budget and subsequently redistribute it to solve social problems or overcome the decline in business economic activity. At the micro level, this contributes to the synchronization of the organization’s taxation system and the financial results of its activities. The practical significance of this approach lies in the prospect of further development and scaling of the mechanism of building an optimal tax trajectory for a wider range of companies, including through various instruments of state financial support.
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Yoon, Namkyung, Dongjae Lee, Kiseok Kim, Taehoon Yoo, Hyeontae Joo, and Hwangnam Kim. "STEAM: Spatial Trajectory Enhanced Attention Mechanism for Abnormal UAV Trajectory Detection." Applied Sciences 14, no. 1 (2023): 248. http://dx.doi.org/10.3390/app14010248.
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Accurate unmanned aerial vehicle (UAV) trajectory tracking is crucial for the successful execution of UAV missions. Traditional global positioning system (GPS) methods face limitations in complex environments, and visual observation becomes challenging with distance and in low-light conditions. To address this challenge, we propose a comprehensive framework for UAV trajectory verification, integrating a range-based ultra-wideband (UWB) positioning system and advanced image processing technologies. Our key contribution is the development of the Spatial Trajectory Enhanced Attention Mechanism (STEAM), a novel attention module specifically designed for analyzing and classifying UAV trajectory patterns. This system enables real-time UAV trajectory tracking and classification, facilitating swift and accurate assessment of adherence to predefined optimal trajectories. Another major contribution of our work is the integration of a UWB system for precise UAV location tracking, complemented by our advanced image processing approach that includes a deep neural network (DNN) for interpolating missing data from images, thereby significantly enhancing the model’s ability to detect abnormal maneuvers. Our experimental results demonstrate the effectiveness of the proposed framework in UAV trajectory tracking, showcasing its robust performance irrespective of raw data quality. Furthermore, we validate the framework’s performance using a lightweight learning model, emphasizing both its computational efficiency and exceptional classification accuracy.
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Lutsenko, Igor, Аnatolii Oksanych, Olena Fomovskaya, Iryna Oksanych, Denis Mospan, and Olga Serdiuk. "DEVELOPMENT OF A METHOD FOR DETERMINING THE OPTIMAL CONTROL TRAJECTORY FOR THE PERIODIC PROCESSES." EUREKA: Physics and Engineering 3 (May 31, 2019): 59–68. http://dx.doi.org/10.21303/2461-4262.2019.00900.
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The development of new converting technologies and increasing the level of automation leads to an increase in the processing speed of available resources. This means that in case of inefficient or inefficient use of resources, the potential of economic advantage is lost, and the negative consequences of such losses can be identified too late. In such conditions, the requirements for the selection of the criterion of optimization and the validity of the principles of optimal control increase. Moreover, the approach used may vary depending on the daily change in prices for energy products and fluctuations in the level of demand for manufactured products. Despite the fact that such an approach seems obvious, today energy-intensive production suffers significant losses associated with the use of an inadequate model of technological operation, a subjective approach to the choice of optimization criterion and optimization method. The task of developing a method for determining the optimal trajectory of managing energy-intensive industries with a changing level of demand for final products is posed. The solution to this problem consists of several stages. At the first stage, a model of a technological operation is being created, within the framework of which all significant factors affecting the decision result are taken into account. At the second stage, a global operation model is created, the input and output products of which are converted to comparable value values. At the third stage, the optimization criterion for the continuous operation of the system and the mode of incomplete use of its production capabilities is selected. At the final stage, the control path for intermittent and continuous modes of operation is determined. Thus, the aim of research is development of a method for determining the optimal control trajectory in systems of energy-intensive systems, depending on the level of demand for the final product.
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Lazarowska, Agnieszka. "Decision support system for collision avoidance at sea." Polish Maritime Research 19, Special (2012): 19–24. http://dx.doi.org/10.2478/v10012-012-0018-2.
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ABSTRACT The paper presents design and realization of computer decision support system in collision situations of passage with greater quantity of met objects. The system was implemented into the real ship electro-navigational system onboard research and training ship m/v HORYZONT II. The radar system with Automatic Radar Plotting Aid constitutes a source of input data for algorithm determining safe trajectory of a ship. The article introduces radar data transmission details. The dynamic programming algorithm is used for the determination of safe optimal trajectory of own ship. The system enables navigational data transmission from radar system and automatic determining of safe manoeuvre or safe trajectory of a ship. Further development of navigator’s decision support system is also presented. Path Planning Subsystem is proposed for the determination of global optimal route between harbours with the use of Ant Colony Optimization algorithms.
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Valera, Ángel, Francisco Valero, Marina Vallés, Antonio Besa, Vicente Mata, and Carlos Llopis-Albert. "Navigation of Autonomous Light Vehicles Using an Optimal Trajectory Planning Algorithm." Sustainability 13, no. 3 (2021): 1233. http://dx.doi.org/10.3390/su13031233.
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Autonomous navigation is a complex problem that involves different tasks, such as location of the mobile robot in the scenario, robotic mapping, generating the trajectory, navigating from the initial point to the target point, detecting objects it may encounter in its path, etc. This paper presents a new optimal trajectory planning algorithm that allows the assessment of the energy efficiency of autonomous light vehicles. To the best of our knowledge, this is the first time in the literature that this is carried out by minimizing the travel time while considering the vehicle’s dynamic behavior, its limitations, and with the capability of avoiding obstacles and constraining energy consumption. This enables the automotive industry to design environmentally sustainable strategies towards compliance with governmental greenhouse gas (GHG) emission regulations and for climate change mitigation and adaptation policies. The reduction in energy consumption also allows companies to stay competitive in the marketplace. The vehicle navigation control is efficiently implemented through a middleware of component-based software development (CBSD) based on a Robot Operating System (ROS) package. It boosts the reuse of software components and the development of systems from other existing systems. Therefore, it allows the avoidance of complex control software architectures to integrate the different hardware and software components. The global maps are created by scanning the environment with FARO 3D and 2D SICK laser sensors. The proposed algorithm presents a low computational cost and has been implemented as a new module of distributed architecture. It has been integrated into the ROS package to achieve real time autonomous navigation of the vehicle. The methodology has been successfully validated in real indoor experiments using a light vehicle under different scenarios entailing several obstacle locations and dynamic parameters.
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BURLAKA, Serhii, Oleksandr HALUSHCHAK, Dmytro BORYSIUK, and Vladyslav BARANOV. "RESEARCH OF THE TRAJECTORY OF THE MOVEMENT OF FUEL PARTICLES IN THE MIXER." ENGINEERING, ENERGY, TRANSPORT AIC, no. 1(124) (April 22, 2024): 89–94. http://dx.doi.org/10.37128/2520-6168-2024-1-10.
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This article is devoted to the study of the trajectories of the movement of fuel particles in the mixer, which is a key aspect for improving the technological processes of modern combustion systems. It is noted that effective mixing and distribution of fuel particles plays a decisive role in ensuring optimal combustion, which, in turn, leads to increased efficiency and reduced emissions of harmful substances. The article covers various aspects of the research, including studying the hydrodynamic characteristics of the mixer, modeling the movement of fuel particles and determining the optimal mixing parameters. An important part of the research is the analysis of particle movement trajectories, which allows to accurately determine their paths in the mixing environment. The application of the latest modeling methods and experimental studies allows to obtain a deeper understanding of the internal processes in the mixer, which contributes to the development of optimal designs and modes of operation. The obtained results can have a significant impact on the development and improvement of combustion systems aimed at reducing emissions and increasing the efficiency of using fuel resources. This article is devoted to a thorough analysis of the trajectories of the movement of fuel particles in mixers. The main aspects of the study include hydrodynamic characteristics of the mixer, modeling of particle motion and determination of optimal mixing parameters to achieve maximum efficiency and minimize emissions. The obtained results can make a significant contribution to the development of efficient and environmentally friendly fuel combustion systems.
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Zhang, Hongxin, Haoran Qiu, Xu Zhang, and Ping Hu. "Recent Advances on Manipulator Trajectory Planning Methods." Recent Patents on Mechanical Engineering 13, no. 4 (2020): 303–27. http://dx.doi.org/10.2174/2212797613666200319151513.
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Background: Traditional manipulator requires professionals to write control programs for specific job requirements so that the end-effector of the manipulator can work following the control instructions. However, the flexibility of the manipulator is not high under the control of off-line programming. With the diversification of the job requirements, the complexity of the work environment has gradually increased. Therefore, the relevant scholars focused their research on the automatic trajectory planning method of the manipulator. They used some algorithms to plan optimal trajectories for the manipulator to automatically avoid obstacles in the complex environment. Researches show that the hybrid optimal trajectory with parameter optimization such as time, energy and impact can be planned by automated programming under some constraint conditions. The trajectory planning is helpful to improve the automation and working efficiency of manipulators for the development of intelligent manufacturing. Objective: Providing references for researchers from related fields by reviewing recent advances of the manipulator trajectory planning. Methods: This paper reviews the latest patents and current representative articles related to the manipulator trajectory planning. The key methods of some references are introduced in several aspects of the algorithm, innovation and principle. Results: Researches on the manipulator trajectory planning in recent 10 years are reviewed. The differences between algorithms in latest patents and current articles are introduced and analyzed and the future developments and potential problems of the manipulator trajectory optimization are discussed. Conclusion: The manipulator trajectory planning reduces complicated operator and hard programming tasks, improving the intelligence of robots and the work efficiency. Current researches focus on collision- free, parameter-optimized and high-efficiency solution which can be used to solve the problem of the end-trajectory planning of the manipulator in the complicated space with obstacles. The aspects that need to be improved in the future include: algorithm reliability, operational security and intelligence, human-computer interaction, efficient simulation, and so on. More patents on manipulator trajectory planning should be invented.
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Xing, Bowen, Liang Zhang, Zhenchong Liu, Hengjiang Sheng, Fujia Bi, and Jingxiang Xu. "The Study of Fishing Vessel Behavior Identification Based on AIS Data: A Case Study of the East China Sea." Journal of Marine Science and Engineering 11, no. 5 (2023): 1093. http://dx.doi.org/10.3390/jmse11051093.
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The goal of this paper is to strengthen the supervision of fishing behavior in the East China Sea and effectively ensure the sustainable development of fishery resources. Based on AIS data, this paper analyzes three types of fishing boats (purse seine operation, gill net operation and trawl operation) and uses the cubic spline interpolation algorithm to optimize the ship trajectory and construct high-dimensional features. It proposes a new coding method for fishing boat trajectory sequences. This method uses the Geohash algorithm to divide the East China Sea into grids and generate corresponding numbers. Then, the ship trajectory is mapped to the grid, the fishing boat trajectory points are associated with the divided grid, and the ship trajectory ID is extracted from the corresponding grid. The extracted complete trajectory sequence passes through the CBOW (continuous bag of words) model, and the correlation of trajectory points is fully learned. Finally, the fishing boat trajectory is converted from coordinate sequence to trajectory vector, and the processed trajectory sequence is trained by the LightGBM algorithm. In order to obtain the optimal classification effect, the optimal superparameter combination is selected. We put forward a LightGBM algorithm based on the Bayesian optimization algorithm, and obtained the classification results of three kinds of fishing boats. The final result was evaluated using the F1_score. Experimental results show that the F1_score trained with the proposed trajectory vectorization method is the highest, with a training accuracy of 0.925. Compared to XgBoost and CatBoost, the F1_score increased by 1.8% and 1.2%, respectively. The results show that this algorithm demonstrates strong applicability and effectiveness in fishery area evaluations and is significant for strengthening fishery resource management.
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Yamada, Yu, Abu Saleh Md Bakibillah, Kotaro Hashikura, Md Abdus Samad Kamal, and Kou Yamada. "Autonomous Vehicle Overtaking: Modeling and an Optimal Trajectory Generation Scheme." Sustainability 14, no. 3 (2022): 1807. http://dx.doi.org/10.3390/su14031807.
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Traffic congestion or accidents may occur as a consequence of the difficulty of performing a safe, comfortable, and efficient overtaking in a timely manner when there is a slow or stopped vehicle, cyclist, or partial lane blockage on the road. Specifically, most drivers find it challenging to overtake a sluggish vehicle on a single-lane road in the presence of vehicles coming from other directions. To resolve such overtaking concerns, this paper proposes a novel optimal trajectory generating scheme for autonomous vehicle overtaking that is both smooth and safe and can be used in a variety of traffic scenarios. The proposed scheme is based on the solution of an optimal predictive problem with the goal of minimizing driving costs while limiting collision risks in the presence of any opposite vehicle on the overtaking lane. The computational burden of the scheme is almost negligible and can be implemented in real-time. The scheme is evaluated in a variety of traffic conditions, including stopped and slow vehicles in the lane, as well as the presence or absence of a nearby opposite vehicle. The simulation results show that the proposed scheme effectively obtains the optimal trajectories even in the difficult overtaking contexts considering various constraints imposed by the road curve, opposite vehicles, and slow preceding vehicles. Finally, the optimal overtaking costs are obtained for various states of the associated vehicles, which provide an indication of the best state to initiate the overtake. The proposed technology can be employed as a fully automated system or an advanced driver assistance system (ADAS) to improve the vehicle flows at challenging driving conditions and enhance transportation sustainability.
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Ossen, Saskia, and Serge P. Hoogendoorn. "Car-Following Behavior Analysis from Microscopic Trajectory Data." Transportation Research Record: Journal of the Transportation Research Board 1934, no. 1 (2005): 13–21. http://dx.doi.org/10.1177/0361198105193400102.
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The development of accurate and robust models in the field of car following has suffered greatly from the lack of appropriate microscopic data. Because of this lack, little is known about differences in car-following behavior between individual driver–vehicle combinations. This paper studies the car-following behaviors of individual drivers by making use of vehicle trajectory data extracted from high-resolution digital images collected at a high frequency from a helicopter. The analysis was performed by estimating the parameters of different specifications of the well-known Gazis–Herman–Rothery car-following rule for individual drivers. This analysis showed that a relation between the stimuli and the response could be established in 80% of the cases. The main contribution of this paper is that considerable differences between the car-following behaviors of individual drivers could be identified. These differences are expressed as different optimal parameter values for the reaction time and the sensitivity, as well as different car-following models that appear to be optimal on the basis of the data for individual drivers.
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Topputo, F., and C. Zhang. "Survey of Direct Transcription for Low-Thrust Space Trajectory Optimization with Applications." Abstract and Applied Analysis 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/851720.
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Space trajectory design is usually addressed as an optimal control problem. Although it relies on the classic theory of optimal control, this branch possesses some peculiarities that led to the development of ad hoc techniques, which can be grouped into two categories: direct and indirect methods. This paper gives an overview of the principal techniques belonging to the direct methods. The technique known as “direct transcription and collocation” is illustrated by considering Hermite-Simpson, high-order Gauss-Lobatto, and pseudospectral methods. Practical examples are given, and several hints to improve efficiency and robustness are implemented.
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SHALAGINOVA, OLGA, ROMAN STAKHNO, and ARTEM GONCHAR. "DEVELOPMENT OF AN AUTOMATED INFORMATION SYSTEM FOR CALCULATING THE MOVEMENT OF A HIGH-SPEED SMALL-SIZED BODY." Computational Nanotechnology 9, no. 4 (2022): 22–29. http://dx.doi.org/10.33693/2313-223x-2022-9-4-22-29.
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The article presents a variant of the development of an automated information system for mathematical modeling of the movement of a high-speed small-sized body based on differential equations and approximation of the trajectory of a high-speed small-sized body by numerical methods, as well as a comparative analysis of various options for numerical solutions. The automated information system allows calculating the flight trajectory coordinates of a high-speed small-sized body based on a differential equation, as well as determining the flight trajectory coordinates by the Euler method, using the Newton interpolation polynomial and the Lagrange interpolation polynomial. In the article, a search for a suitable variant of numerical solutions is carried out, as well as calculations of the movement of a high-speed small-sized body under conditions of limited time for decision-making. The substantiation of the use of an automated information system to automate the calculation and analysis of the movement of a high-speed small-sized body is carried out. While designing an automated information system for calculating and analyzing the flight of a high-speed small-sized body, it is proposed to apply four modules for calculating the flight trajectory of a high-speed small-sized body by numerical methods and a module for comparative analysis and making the results of the optimal variant. The proposed automated information system should provide users with uninterrupted operation, a convenient interface, the required system response time to a request, and the creation of necessary reports. The reports should reflect all types of calculations, as well as a comparative analysis with the choice of the optimal option for calculating the flight path of a high-speed small-sized body. An automated information system is needed to improve the quality of calculations and analysis of movement in the development of new and modernization of existing small arms.
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Muhamediyeva, D. K., and M. Fozilova. "Analysis of the base motion model of industrial robots moving." E3S Web of Conferences 402 (2023): 03050. http://dx.doi.org/10.1051/e3sconf/202340203050.
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Development of mathematical models and algorithms for optimal control of the functioning of industrial robots on a movable base to ensure the accuracy of the trajectory of movement and positioning is considered. An equation for the functioning of industrial robots on a movable base in the implementation of a complex spatial operation obtained and, on its basis, a mathematical model of optimal control is developed.
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Wu, Yufei, Sabrullah Deniz, Yang Shi, and Zhenbo Wang. "Convex Approach to Real-Time Multiphase Trajectory Optimization for Urban Air Mobility." Journal of Air Transportation 33, no. 1 (2025): 69–85. https://doi.org/10.2514/1.d0348.
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Electric vertical takeoff and landing technology has emerged as a promising solution to alleviate ground transportation congestion. However, the limited capacity of onboard batteries enforces hard time constraints for vehicle operations in a complex urban environment. Therefore, a constrained, real-time trajectory optimization method is necessary to enable safe and energy-efficient vehicle flight. Unfortunately, most existing trajectory optimization methods suffer from low computational efficiency, unpredictable convergence processes, and strong dependence on a good initial trajectory. In this paper, we employ a successive convex programming approach to solve the multiphase minimum-energy-cost electric vertical takeoff and landing vehicle trajectory optimization problem for urban air mobility applications. The main contribution is the development and validation of two novel convexification methods that find approximate optimal solutions to the multiphase nonlinear trajectory optimization problem in real time by solving a sequence of convex subproblems. Specifically, the first method transforms the original nonlinear problem into a sequence of second-order cone programming problems through a convenient change of variables and lossless convexification, while the second approach achieves a similar goal without the need for control convexification. The resulting convex subproblems can be solved reliably in real time by advanced interior point methods. The proposed methods are demonstrated through numerical simulations of two different urban air mobility scenarios and compared with the solution obtained from GPOPS-II, a state-of-the-art general-purpose optimal control solver. Our proposed sequential convex programming methods can obtain near-optimal solutions with faster computational speed than GPOPS-II.
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Hailu, Fitih F., Worku T. Bitew, Tsegaye G. Ayele, and Simon D. Zawka. "Marine protected areas for resilience and economic development." Aquatic Living Resources 36 (2023): 22. http://dx.doi.org/10.1051/alr/2023016.
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In this research, we attempt to give a comparative analysis of the space allocation of multiple-use marine protected areas (MPAs) including but not limited to the introduction of aquaculture in the area. Specifically, we consider the case where there is a need to develop MPAs for the conservation of the environment and ecological diversity. There is also a prevailing call for the establishment of aquaculture activities within the area to meet societal demands. Although aquaculture has negative externalities on MPAs, it helps to reduce the pressure on the capture fishery and increases the supply of fish. We develop a deterministic bioeconomic model that describes the transition dynamics and interrelationships of the systems. We find an optimal aquaculture size relative to the optimal size of MPAs that maximizes the overall economic and ecological benefits. Using numerical methods we determine the trajectory of optimal solutions, the recovery rate of the stocks in and outside the MPAs, and the expansion rate of the aquaculture. Sensitivity analysis was also performed to see the effect of a change in the parameters on the optimal solutions. The numerical results show that MPAs are resilient after the implementation of aquaculture. Moreover, the effectiveness of the optimized management system mainly depends on the cooperative planning between the capture fishery and aquaculture managers.
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Yang, Jing, Yingjie Gao, Rui Guo, Qingshan Gao, and Jingyi Zhao. "Research on Excavator Trajectory Control Based on Hybrid Interpolation." Sustainability 15, no. 8 (2023): 6761. http://dx.doi.org/10.3390/su15086761.
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In this study, to address the issues of tooth tip operation discontinuity and jitter during autonomous excavator operation, a multi-segment mixed interpolation method utilizing different higher-order polynomials has been proposed. This approach is designed to optimize the tooth tip trajectory of the excavator under multiple constraints, resulting in a smoother trajectory. Specifically, the single-bucket excavator was chosen as the research object, and three different high-order mixed polynomials were utilized to interpolate the trajectory of the digging discrete points. Through a comparative analysis under multiple constraints, this study explored and analyzed the joint angle, angular velocity, and angular acceleration curves of each excavator’s joint. An experimental platform was established to investigate the hydraulic system of an excavator, and the optimal trajectory was controlled using a high-order mixed polynomial interpolation. The results of this study demonstrate that the tracking accuracy of the excavator’s actuator under the optimal interpolation strategy is high, with a maximum displacement deviation of ±3 mm. Additionally, during operation, the excavator manipulator runs smoothly and continuously with minimal flexible impact and vibration.
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Sun, Jun, Ling Lu, Jun Qing Chen, and Jiu Fu Jin. "Analysis of Gait Planning Method for Biped Robots." Advanced Materials Research 753-755 (August 2013): 1995–2000. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1995.
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Biped robots research is mainly concentrated on the control system development and doing simulation, cubic spline interpolation method is widely applied to pre-gait planning work. This paper analyzed the robots walking process and calculated the joint trajectory curves of a walk cycle by using spline interpolation and the quintic polynomial fitting means, verifies that the result obtained by quintic polynomial algorithm tends to be more ideal, it is conducive to maintain walking stability and find the optimal joint angles. The paper provides a theoretical basis for optimizing robots trajectory planning.
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Cao, Xiaoman, Hansheng Yan, Zhengyan Huang, et al. "A Multi-Objective Particle Swarm Optimization for Trajectory Planning of Fruit Picking Manipulator." Agronomy 11, no. 11 (2021): 2286. http://dx.doi.org/10.3390/agronomy11112286.
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Stable, efficient and lossless fruit picking has always been a difficult problem, perplexing the development of fruit automatic picking technology. In order to effectively solve this technical problem, this paper establishes a multi-objective trajectory model of the manipulator and proposes an improved multi-objective particle swarm optimization algorithm (represented as GMOPSO). The algorithm combines the methods of mutation operator, annealing factor and feedback mechanism to improve the diversity of the population on the basis of meeting the stable motion, avoiding the local optimal solution and accelerating the convergence speed. By adopting the average optimal evaluation method, the robot arm motion trajectory has been testified to constructively fulfill the picking standards of stability, efficiency and lossless. The performance of the algorithm is verified by ZDT1~ZDT3 benchmark functions, and its competitive advantages and disadvantages with other multi-objective evolutionary algorithms are further elaborated. In this paper, the algorithm is simulated and verified by practical experiments with the optimization objectives of time, energy consumption and pulsation. The simulation results show that the solution set of the algorithm is close to the real Pareto frontier. The optimal solution obtained by the average optimal evaluation method is as follows: the time is 34.20 s, the energy consumption is 61.89 °/S2 and the pulsation is 72.18 °/S3. The actual test results show that the trajectory can effectively complete fruit picking, the average picking time is 25.5 s, and the success rate is 96.67%. The experimental results show that the trajectory of the manipulator obtained by GMOPSO algorithm can make the manipulator run smoothly and facilitates efficient, stable and nondestructive picking.
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Bousquet, Gabriel D., Michael S. Triantafyllou, and Jean-Jacques E. Slotine. "Optimal dynamic soaring consists of successive shallow arcs." Journal of The Royal Society Interface 14, no. 135 (2017): 20170496. http://dx.doi.org/10.1098/rsif.2017.0496.
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Albatrosses can travel a thousand kilometres daily over the oceans. They extract their propulsive energy from horizontal wind shears with a flight strategy called dynamic soaring. While thermal soaring, exploited by birds of prey and sports gliders, consists of simply remaining in updrafts, extracting energy from horizontal winds necessitates redistributing momentum across the wind shear layer, by means of an intricate and dynamic flight manoeuvre. Dynamic soaring has been described as a sequence of half-turns connecting upwind climbs and downwind dives through the surface shear layer. Here, we investigate the optimal (minimum-wind) flight trajectory, with a combined numerical and analytic methodology. We show that contrary to current thinking, but consistent with GPS recordings of albatrosses, when the shear layer is thin the optimal trajectory is composed of small-angle, large-radius arcs. Essentially, the albatross is a flying sailboat, sequentially acting as sail and keel, and is most efficient when remaining crosswind at all times. Our analysis constitutes a general framework for dynamic soaring and more broadly energy extraction in complex winds. It is geared to improve the characterization of pelagic birds flight dynamics and habitat, and could enable the development of a robotic albatross that could travel with a virtually infinite range.
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Shen, Lingfeng, Ning Wang, Xiang Ji, Xiaomin Mu, and Lin Cai. "Iterative Trajectory Optimization for Physical-Layer Secure Buffer-Aided UAV Mobile Relaying." Sensors 19, no. 15 (2019): 3442. http://dx.doi.org/10.3390/s19153442.
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With the fast development of commercial unmanned aerial vehicle (UAV) technology, there are increasing research interests on UAV communications. In this work, the mobility and deployment flexibility of UAVs are exploited to form a buffer-aided relaying system assisting terrestrial communication that is blocked. Optimal UAV trajectory design of the UAV-enabled mobile relaying system with a randomly located eavesdropper is investigated from the physical-layer security perspective to improve the overall secrecy rate. Based on the mobility of the UAV relay, a wireless channel model that changes with the trajectory and is exploited for improved secrecy is established. The secrecy rate is maximized by optimizing the discretized trajectory anchor points based on the information causality and UAV mobility constraints. However, the problem is non-convex and therefore difficult to solve. To make the problem tractable, we alternatively optimize the increments of the trajectory anchor points iteratively in a two-dimensional space and decompose the problem into progressive convex approximate problems through the iterative procedure. Convergence of the proposed iterative trajectory optimization technique is proved analytically by the squeeze principle. Simulation results show that finding the optimal trajectory by iteratively updating the displacements is effective and fast converging. It is also shown by the simulation results that the distribution of the eavesdropper location influences the security performance of the system. Specifically, an eavesdropper further away from the destination is beneficial to the system’s overall secrecy rate. Furthermore, it is observed that eavesdropper being further away from the destination also results in shorter trajectories, which implies it being energy-efficient as well.
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Ulu, Burak, Sertaç Savaş, Ömer Faruk Ergin, et al. "Tuning the Proportional–Integral–Derivative Control Parameters of Unmanned Aerial Vehicles Using Artificial Neural Networks for Point-to-Point Trajectory Approach." Sensors 24, no. 9 (2024): 2752. http://dx.doi.org/10.3390/s24092752.
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Nowadays, trajectory control is a significant issue for unmanned micro aerial vehicles (MAVs) due to large disturbances such as wind and storms. Trajectory control is typically implemented using a proportional–integral–derivative (PID) controller. In order to achieve high accuracy in trajectory tracking, it is essential to set the PID gain parameters to optimum values. For this reason, separate gain values are set for roll, pitch and yaw movements before autonomous flight in quadrotor systems. Traditionally, this adjustment is performed manually or automatically in autotune mode. Given the constraints of narrow orchard corridors, the use of manual or autotune mode is neither practical nor effective, as the quadrotor system has to fly in narrow apple orchard corridors covered with hail nets. These reasons require the development of an innovative solution specific to quadrotor vehicles designed for constrained areas such as apple orchards. This paper recognizes the need for effective trajectory control in quadrotors and proposes a novel neural network-based approach to tuning the optimal PID control parameters. This new approach not only improves trajectory control efficiency but also addresses the unique challenges posed by environments with constrained locational characteristics. Flight simulations using the proposed neural network models have demonstrated successful trajectory tracking performance and highlighted the superiority of the feed-forward back propagation network (FFBPN), especially in latitude tracking within 7.52745 × 10−5 RMSE trajectory error. Simulation results support the high performance of the proposed approach for the development of automatic flight capabilities in challenging environments.
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Herizon, Herizon, Milda Yuliza, and Rahmat Rahmat. "Implementation of Photodiode Sensors in a Line Follower Robot." JECCOM: International Journal of Electronics Engineering and Applied Science 2, no. 1 (2024): 32–41. https://doi.org/10.30630/jeccom.2.1.32-41.2024.
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Line follower robot is a type of autonomous robot designed to follow a specific trajectory, usually a black line on a white background. In order for the robot to follow the trajectory accurately, a sensor is required that is able to detect the difference in light intensity between the line and the background. This study evaluates the application of a photodiode sensor to a microcontroller-based line follower robot, focusing on the performance of the sensor under various lighting conditions and surfaces. The results show that the photodiode sensor is able to detect lines with high accuracy of almost 100% between black lines on a white surface. To achieve fast response speed and high trajectory stability, the optimal distance between the photodiode sensor and the surface must be maintained. Fast response speed and high trajectory stability are at a distance of 0.5 to 1.0 cm. Under normal lighting conditions (200-300 lux), the robot can follow the trajectory with optimal speed and precision. Under low lighting conditions (below 100 lux), the sensor is still able to detect the line, but the robot speed must be reduced to maintain accuracy. Under very bright lighting conditions (above 500 lux), the photodiode sensor shows a little difficulty in distinguishing lines if there is significant light reflection, but it can still be compensated by adjusting the sensor sensitivity. This research provides a solid foundation for further development in improving the performance of line follower robots in various practical applications.
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Yu, Wen Ming. "Research on Optimal Vehicle Path in Intelligent Transportation." Applied Mechanics and Materials 644-650 (September 2014): 2615–18. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2615.
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The rapid development of economy and science and technology is quite obvious, which makes cars becoming more and more widely into the general family life. With the rapid development of economics and technology; the number of vehicles has largely increased. In this paper, there is the basic organizational framework for intelligent transportation, intelligent transportation network proposed model and its data storage structure, and the important influence on optimal path trajectory intelligent transportation planning. This paper analyzes intersection road network in the distribution based on computer graphics language, type and grade roads. The dynamic mathematical model of single vehicle is used vehicle planning algorithm based on period, effectively avoided the traffic road, reduce vehicle travel cost, improve the real-time effect and accuracy of the vehicle dynamic path. We hope the results and researches could combine with reality in order to reduce traffic congestion.
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Galeano-Urueña, Carlos Humberto, Carlos Alberto Duque-Daza, and Diego Alexander Garzón-Alvarado. "Application of sizing design optimization to position and velocity synthesis in four bar linkage." Revista Facultad de Ingeniería Universidad de Antioquia, no. 47 (September 18, 2013): 129–44. http://dx.doi.org/10.17533/udea.redin.16690.
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In this work, we have developed and solved the synthesis of position and velocity for four bar mechanisms by means of dimensional and optimal algorithms of nonlinear optimization (sequential quadratic programming SQP). The optimization problem was defined according to the synthesis needed: it can be trajectory, function or velocity generation. The velocity can be defined with an explicit or implicit trajectory. The optimization problem and the search algorithm used in this work allow reaching the best configuration by way of a simple scheme and few iterations. Alternatively, the development of a mix synthesis of position and velocity allows us validate the algorithm efficiency.
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Korolev, S. A., and R. R. Mansurov. "Development of Mathematical Support and Software for Ballistic Analysis and Optimization of Active-Missile Projectile Parameters." Intellekt. Sist. Proizv. 22, no. 4 (2024): 98–107. https://doi.org/10.22213/2410-9304-2024-4-98-107.
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The paper presents the results of developing mathematical and software support for internal and external ballisticsmodelling, as well as optimizing the parameters of an active-reactive projectile. A complex mathematical model of active-reactive projectile ballistic analysis includes the problem of external ballistics, the problem of internal ballistics inside the gun barrel and the problem of internal ballistics of a solid-fuel jet engine. The problem of active-reactive projectile parameteroptimization is to increase the flight range with respecttomotion stabilitycondition along the entire trajectory. Based on the mathematical model of ballistic analysis, the algorithms for solving a multi-criteria problem of active-reactive projectileparameteroptimization have been developed. The developed software package includes a block of calculation modules implementing mathematical models and computational algorithms, a database of projectile parameters and simulation results, a block for visualization the computational experiment results in the form of diagrams and tables. The software package can be used in the design and optimization of the projectileparameters of artillery systems implementing the active-reactive throwingprinciple. The results of mathematical modeling and optimization of parameters are considered using the example of the designed active-reactive projectile for the 152 mm artillery system. To improve the projectilestability on the trajectory during jet engineoperation, it is proposed to install ribs at an angle to the projectile axis on the inner surface of the nozzle so as to create extra torque. Based on the developed model, the optimal characteristics of firing an active-reactive projectile of caliber 152 mm are determined. The results of internal and external ballisticsproblem solutionfor an active-reactive projectile obtained by means ofthe software package for ballistic process modeling are presented. The main problem of internal ballistics inside the gun barrel, the problem of internal ballistics of a solid-fuel jet engine, the direct problem of external ballistics of an active-reactive projectile and the study of the projectile motion stability along the trajectory are solved. Optimal parameters of internal and external ballistics, providing the maximum firing range of an active-reactive projectile with respect toitsmotionstability along the entire trajectory, are found.