Relevant bibliographies by topics / Optimal trajectory development

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Optimal trajectory development'

Author: Grafiati
Published: 3 June 2025
Last updated: 13 July 2025

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Journal articles on the topic "Optimal trajectory development"

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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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Dissertations / Theses on the topic "Optimal trajectory development"

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Schaupp, Michael. "Development of an optimal control strategy for robot trajectory planning." Thesis, Liverpool John Moores University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244448.

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Fisch, Florian [Verfasser]. "Development of a Framework for the Solution of High-Fidelity Trajectory Optimization Problems and Bilevel Optimal Control Problems / Florian Fisch." München : Verlag Dr. Hut, 2011. http://d-nb.info/1011441756/34.

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Fisch, Florian [Verfasser], Florian [Akademischer Betreuer] Holzapfel, and Matthias [Akademischer Betreuer] Gerdts. "Development of a Framework for the Solution of High-Fidelity Trajectory Optimization Problems and Bilevel Optimal Control Problems / Florian Fisch. Gutachter: Florian Holzapfel ; Matthias Gerdts. Betreuer: Florian Holzapfel." München : Universitätsbibliothek der TU München, 2011. http://d-nb.info/1013435443/34.

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Perronno, Paul. "Development of a biosensor for in situ pathogen detection on hands." Electronic Thesis or Diss., Strasbourg, 2024. http://www.theses.fr/2024STRAD049.

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Les infections sont un problème grandissant aujourd’hui, notamment due à l’augmentation de pathogènes résistant aux antibiotiques, L’hygiène des mains et les gestes barrières sont les premiers outils de prévention d’infections. Cependant, il y a un besoin de systèmes d’alertes rapides pour une meilleure prévention et éviter des épidémies ou pandémies. Il existe de nombreuses techniques de détection d‘infections tel que la réaction en chaine par polymérase. Ces dernières années, de nouveaux systèmes miniatures ont émergé basé sur diverses technologies comme l’optique ou l’impédance. Ces méthodes sont souvent spécifiques, longues ou couteuses. Une prévention efficace repose sur la possibilité de tester rapidement un grand nombre d’infections, ce qui n’est pas possible actuellement. Cette thèse développe un système de détection d’infections intégrable, rapide et abordable scindé en trois parties : un tri microfluidique, une détection par spectroscopie d’impédance et une détection optique<br>Infections are a big issue in today’s health world, partly due to the rising number of multi-resistant pathogens. Hand hygiene and barrier gestures are the first tools for infections prevention. However, early alert systems are also required for a better prevention and to avoid future epidemics or pandemics. Numerous techniques exist for infection detection such as culture or polymerase chain reaction. In recent years, miniaturized systems emerged based on various technologies such as optics, mechanics, nuclear magnetic resonance or impedance. Unfortunately, all these methods are usually specific, time-consuming or expensive. An effective prevention relies on the performance of a large number of rapid tests on a large scale, which is not currently achievable. This thesis develops an integrable, fast and affordable infection detection system combining three parts based on three technologies: a microfluidic sorting, an impedance spectroscopy detection and an optical detection
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Meng-HsienLin and 林孟弦. "Optimal Design of an Innovative Eight-Bar Legged Walking Mechanism that Mimics Human Foot Trajectory when Climbing Stairs and the Development of a Multi-Legged Stair Climbing Robot." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/34707355229552780889.

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碩士<br>國立成功大學<br>機械工程學系<br>104<br>This study presents an innovative linkage mechanism and the design of a multi-legged stair-climbing robot. As the traditional continuous track type, star wheel type, and individually controlled multi-legged type stair-climbing machines are either moved slowly or with large oscillation at the centroid during operation. This study presents a multi-legged stair-climbing robot with the capability to steadily climb stairs with consistent human foot trajectory. The leg design is based on the eight-bar Jansen mechanism but a new set of leg configuration is numerically identified based on the proposed optimal design method with the aim to mimic the human foot trajectory when climbing stairs. The kinematic analysis of the leg mechanism based on loop closure equation has been derived in order to identify the leg trajectories for various designs. The targeted foot trajectory is experimentally measured. The weighted sum and sequential quadratic programming methods are used to solve the multi-objective function in the optimal design process. The proposed design is an eight-leg robot; its dynamic performance and trajectories of the multibody motion when climbing stairs have been numerically verified by using the commercial CAE package, RecurDyn. The prototype of the biomimetic robot has been developed to proof the concept design. The experimental results show the multi-legged robot can step up and down stairs with steady human foot trajectory. The outcomes of this study provide numerical methods to analyze the multibody dynamics of the linkage mechanisms as well as to develop an innovative multi-legged walking robot for stair-climbing. The development is expected to be further used for various applications such as rescue robots, information collection/detection, and assistive devices.
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Ku, Alex, and 古敏鋒. "Forming the strategy of Taiwan memory card business from development trajectory of Taiwan optical disc business ---- take an example of Apex company." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/03432677749425086376.

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Books on the topic "Optimal trajectory development"

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United States. National Aeronautics and Space Administration., ed. Rapid near-optimal trajectory generation and guidance law development for single-stage-to-orbit airbreathing vehicles. School of Aerospace Engineering, Georgia Institute of Technology, 1990.

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National Aeronautics and Space Administration (NASA) Staff. Rapid near-Optimal Trajectory Generation and Guidance Law Development for Single-Stage-To-Orbit Airbreathing Vehicles. Independently Published, 2018.

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Rapid near-optimal trajectory generation and guidance law development for single-stage-to-orbit airbreathing vehicles. School of Aerospace Engineering, Georgia Institute of Technology, 1990.

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Trajectory optimization and guidance law development for national aerospace plane applications: Final report, July 1, 1987 to November 30, 1988. School of Aerospace Engineering, Georgia Institute of Technology, 1988.

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Book chapters on the topic "Optimal trajectory development"

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Anderson, Sterling J., Steven C. Peters, Tom E. Pilutti, and Karl Iagnemma. "Design and Development of an Optimal-Control-Based Framework for Trajectory Planning, Threat Assessment, and Semi-autonomous Control of Passenger Vehicles in Hazard Avoidance Scenarios." In Springer Tracts in Advanced Robotics. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19457-3_3.

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Borovik, V. S., and V. V. Borovik. "Formation of a Strategy for Managing Scientific Research." In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde240816.

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A model for control strategy realization when automating the research process was developed. The control strategy is considered as a certain realizable control trajectory carried out within the boundaries of the hypersurface area which surrounds the optimal control trajectory. The distance from the optimal control trajectory, which determines the range of acceptable values, is assessed by the quality of control -ρ, which is the total statistical value of the “distance” of the real trajectory from the optimal one. This approach allows us to move to a certain realizable control trajectory, carried out within the boundaries of the hypersurface area which surrounds the optimal control trajectory. The model creates the prerequisites for the development of a computer program that allows automating the research process. The program will allow you to calculate quickly the implementation of the optimal control trajectory according to a given strategy, evaluate the quality of control and present ways to have optimal control taking into account the real conditions of research process.
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Tachinina, Olena, and Oleksandr Lysenko. "Methods for the Synthesis of Optimal Control of Deterministic Compound Dynamical Systems With Branch." In Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1415-3.ch014.

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This chapter states the result of the development of optimal control methods for deterministic discontinuous systems of optimal control problems for deterministic compound dynamical systems (CDS) with branching paths. The necessary conditions for optimality of the CDS branching paths are formulated in the form convenient for subsequent development of algorithms for the operational synthesis of these paths. The optimality conditions developed by the authors allow both preliminary and in real time (on-line) optimization of the CDS branching paths. The need for an operational synthesis of the CDS branching trajectory is caused by the inaccuracy of prior knowledge of information about the factors affecting CDS movement which are critical for the implementation of the CDS end-use. The developed conditions are universal for solving problems with any finite number of branches of a branching trajectory and are focused on the use of artificially intelligent systems which allow analyzing the structure of optimal control of CDS components as they move along the path branches.
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A. Rendón, Manuel. "Quadrotor Unmanned Aerial Vehicles: Visual Interface for Simulation and Control Development." In Robotics Software Design and Engineering. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97435.

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Quadrotor control is an exciting research area. Despite last years developments, some aspects demand a deeper analysis: How a quadrotor operates in challenging trajectories, how to define trajectory limits, or how changing physical characteristics of the device affects the performance. A visual interface development platform is a valuable tool to support this effort, and one of these tools is briefly described in this Chapter. The quadrotor model uses Newton-Euler equations with Euler angles, and considers the effect of air drag and propellers’ speed dynamics, as well as measurement noise and limits for propeller speeds. The tool is able to test any device just by setting a few parameters. A three-dimensional optimal trajectory defined by a set of waypoints and corresponding times, is calculated with the help of a Minimum Snap Trajectory planning algorithm. Small Angle Control, Desired Thrust Vector (DTV) Control and Geometric Tracking Control are the available strategies in the tool for quadrotor attitude and trajectory following control. The control gains are calculated using Particle Swarm Optimization. Root Mean Square (RMS) error and Basin of Attraction are employed for validation. The tool allows to choose the control strategy by visual evaluation on a graphical user interface (GUI), or analyzing the numerical results. The tool is modular and open to other control strategies, and is available in GitHub.
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Hannon, Breffni, Stein Kaasa, and Camilla Zimmermann. "Specialist palliative care along the trajectory of illness." In Oxford Textbook of Palliative Medicine, edited by Nathan I. Cherny, Marie T. Fallon, Stein Kaasa, Russell K. Portenoy, and David C. Currow. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780198821328.003.0011.

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The benefits of early, integrated palliative care have been demonstrated through several randomized controlled trials. These benefits include improved quality of life, satisfaction with care, symptom management, and, in some cases, survival. Despite heterogeneity in study design and execution, as well as limitation to mainly the oncology population, these trials have answered the question of why patients should receive palliative care early in their disease trajectory. Attention must now shift to the practicalities of early integration; these include questions about when is the optimal time to refer to palliative care services, who is best placed to provide palliative care supports, where early palliative care should be provided, and how best to integrate early palliative care services across the care continuum. This chapter summarizes current evidence supporting early integration of palliative care; describes the respective roles of primary, secondary, and tertiary care providers in the delivery of early palliative care; explores the optimal timing and venues for the delivery of early palliative care; and outlines a hierarchy of integration models to best meet the needs of all patients throughout the illness trajectory. Although rooted in evidence primarily from oncology trials conducted in North American and European settings, these options may be adaptable across a variety of healthcare settings, irrespective of available resources and stages of development of palliative care services. Future research should include patients from non-oncology populations, and focus on models of integration that include primary and secondary providers, rather than relying only on tertiary palliative care.
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Mebarki, Ahmed. "Industrial Risks and Domino Effects: Resilience, Risks and Optimal Layouts." In Critical Energy Infrastructure Protection. IOS Press, 2022. http://dx.doi.org/10.3233/nicsp220003.

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The modern concept of resilience relies on adequate metrics of the objective and utility functions, pertinent evaluation of the damages and utility drops, multi-hazards modeling, adaptive options and recovery functions. The paper presents some key topics for the theoretical resilience in industrial and urban contexts. Three case studies are investigated: - The case of industrial tanks: fragments generated by explosions, their trajectory and impact on surrounding facilities, risk and domino effects. - The case of industrial tanks: effect of tsunamis and fragility curves development. - A construction site: risk analysis, optimal layouts, guided crowd evacuation, and digital twins.
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Rodzin, Sergei Ivanovich, Iurii Aleksandrovich Skobtsov та Samer Adnan El'-Khatib. "Bioheuristics: theory, algorithms and applications". У Биоэвристики: теория, алгоритмы и приложения. Publishing house Sreda, 2019. http://dx.doi.org/10.31483/r-22141.

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The book examines the current state and problems of bioheuristics development, biographical and memetic algorithms, the issues of finding optimal solutions by trajectory algorithms and bioheuristics of multicriteria optimization. Ant and swarm bioheuristics, their features and modifications are presented. Hybrid formic and hypeuruistic swarm segmentation algorithms of complexly structured images are considered as applications. The monograph is interdisciplinary, it is addressed to masters and graduate students studying the theory and practice of creating intelligent information systems and technologies, as well as specialists in the theoretical foundations of computer science, software engineering, system analysis, information management and processing, information systems and processes, bioinformatics.
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Thomas, Jishamol, and Sheeja Remani B. Karalam. "Empowering Indigenous Adolescents." In Enhancing Curricula with Service Learning Models. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5933-4.ch007.

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This chapter synthesizes results from examining service-learning initiatives tailored for Indigenous adolescents. The authors emphasize customized educational approaches, community collaboration, and cultural sensitivity. The Paniya Tribes case study in Wayanad illustrates efforts of this kind that seek to address historical inequities and enhance students' academic performance, life skills, and engagement. The enduring impact extends beyond academics, empowering young people to take on leadership roles. Cultural sensitivity and the responsible application of technology are two factors that can significantly impact Indigenous education's trajectory in the future. Implementing suggested strategies and optimal methods advances inclusive and culturally attuned education, thereby preserving Indigenous cultures and fostering sustainable development.
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Fauerbach, James A., and Carisa Perry-Parrish. "Self-Management of Burn Injury." In Promoting Self-Management of Chronic Health Conditions, edited by Erin Martz. Oxford University Press, 2017. http://dx.doi.org/10.1093/med-psych/9780190606145.003.0009.

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Burn injuries present individuals with a range of physical, medical, emotional, social, and behavioral challenges. Burn injuries are painful, as are the necessary medical treatments that typically follow. In this chapter, research is presented on physiological (e.g., pain, pruritus), psychological (e.g., worries, negative emotions, distress), and social sequelae (e.g., self-perception of appearance, body image) of burn injuries in adults. Research is also reviewed on the evidence-based strategies to address impairments across domains, the emotional impact and methods for optimal coping, and the methods that generally facilitate self-management. The chapter concludes that progress has been made in identifying, quantifying the prevalence, and tracking differences in trajectory of many burn-related conditions, development of support group, prevention and intervention approaches to burn-specific challenges, as well as in identifying individual characteristics that increase risk for adjustment difficulties.
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Zhao, Jingyuan, and Andrew F. Burke. "Deep Learning for Planning and Control in Autonomous Vehicles." In Modeling and Control of Autonomous Systems [Working Title]. IntechOpen, 2025. https://doi.org/10.5772/intechopen.1009340.

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In autonomous systems, path planning and control are critical for ensuring safety, efficiency, and comfort. Deep learning has significantly enhanced these aspects by introducing adaptability and real-time responsiveness into autonomous operations. Reinforcement learning-based motion planning algorithms, for example, are adept at devising optimal navigation paths even within intricate environments. Moreover, trajectory prediction models, particularly those employing recurrent neural networks, excel in anticipating the movements of nearby objects accurately. Furthermore, the integration of end-to-end methodologies has augmented the capabilities of autonomous control systems, providing a more streamlined approach to decision-making processes. The application of explainable AI techniques brings a layer of transparency to these technologies, elucidating the reasoning behind decisions and fostering trust among users. Herein, we explore these technological advancements and examine their impact on the development of autonomous vehicle technology.
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Conference papers on the topic "Optimal trajectory development"

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Galisteu, Danilo, Florian Adolf, Jörg Dittrich, Falk Sachs, and Holger Duda. "Towards Autonomous Emergency Landing for an Optionally Piloted Autogyro." In Vertical Flight Society 71st Annual Forum & Technology Display. The Vertical Flight Society, 2015. http://dx.doi.org/10.4050/f-0071-2015-10294.

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In this paper, we present the development of a system for automation of the emergency maneuver for an autogyro after engine power loss. The purpose of the system is to determine a safe and feasible trajectory from the initial condition in forward flight to a final position that is suitable for final approach and landing at a desired location. The flight dynamics of the autogyro is evaluated and a flight control system is developed for the unpowered flight. A simplified dynamic model is created for generation of the gliding trajectory from the starting point to a given final position and ground track, taking into account constant wind values. This model allows us to predict the vertical speed for a given vehicle state and, through optimization, to plan feasible trajectories with minimum altitude loss. Results for generation and tracking of the optimal trajectories are presented, showing good performance and the potential to be used with a sampling-based algorithm for real-time motion planning.
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Goulos, Ioannis, Vassilios Pachidis, Cesar Celis, Roberto D’Ippolito, and Jos Stevens. "Simulation Framework Development for Aircraft Mission Analysis." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23379.

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Since the very beginning of first commercial flight operations, aircraft mission analysis has played a major role in minimizing costs, increasing performances and satisfying regulations. The operational trajectory of any aircraft must comply with several constraints that need to be satisfied during its operation. The nature of these constraints can vary from Air Traffic Control (ATC) regulations, to emissions regulations and any combination between these two. The development of an integrated tool capable of determining the resources required (fuel and operational time) for a given aircraft trajectory, as well as assessing its environmental impact, is therefore essential. The present work illustrates the initial steps of a methodology developed in order to acquire the optimal trajectory of any specified aircraft under specific operational or environmental constraints. The simulation framework tool is the result of a collaborative effort between Cranfield University (UK), National Aerospace Laboratory NLR (NL) and LMS International (BE). With this tool, the optimal trajectory for a given aircraft can be computed and its environmental impact assessed. In order to simulate the characteristics of a specific trajectory, as well as to evaluate the emissions that are produced during the aircraft operation within it, three computational models developed at Cranfield University have been integrated into the simulation tool. These models consist of an aircraft performance model, an engine performance model and an emission indices model. The linking has been performed with the deployment of the OPTIMUS process and simulation integration framework developed by LMS International. The optimization processes carried out were based on OPTIMUS’ built-in optimizing algorithms. A comparative evaluation between an arbitrarily defined baseline trajectory and optimized ones has been waged for the purpose of quantifying the operational profit (in terms of fuel required or operational time) gained by the aircraft operation within the path of an optimized trajectory. Trade-off studies between trajectories optimized for different operational and environmental constraints have been performed. The results of the optimizations revealed a substantial margin available for reduction in fuel consumption as well as required operational time compared to a notional baseline. The optimal trajectories for minimized environmental impact in terms of produced emissions have been acquired and their respective required resources (fuel required and operational time) have been evaluated.
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Goulos, Ioannis, Martina Mohseni, Vassilios Pachidis, Roberto D’Ippolito, and Jos Stevens. "Simulation Framework Development for Helicopter Mission Analysis." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23389.

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Helicopter mission performance analysis has always been an important topic for the helicopter industry. This topic is now raising even more interest as aspects related to emissions and noise gain more importance for environmental and social impact assessments. The present work illustrates the initial steps of a methodology developed in order to acquire the optimal trajectory of any specified helicopter under specific operational or environmental constraints. For this purpose, it is essential to develop an integrated tool capable of determining the resources required (e.g. fuel burnt) for a given helicopter trajectory, as well as assessing its environmental impact. This simulation framework tool is the result of a collaborative effort between Cranfield University (UK), National Aerospace Laboratory NLR (NL) and LMS International (BE). In order to simulate the characteristics of a specific trajectory, as well as to evaluate the emissions that are produced during the helicopter’s operation within the trajectory, three computational models developed at Cranfield University have been integrated into the simulation tool. These models consist of a helicopter performance model, an engine performance model and an emission indices prediction model. The models have been arranged in order to communicate linearly with each other. The linking has been performed with the deployment of the OPTIMUS process and simulation integration framework developed by LMS International. The optimization processes carried out for the purpose of this work have been based on OPTIMUS’ built-in optimizing algorithms. A comparative evaluation between the optimized and an arbitrarily defined baseline trajectory’s results has been waged for the purpose of quantifying the operational profit (in terms of fuel required) gained by the helicopter’s operation within the path of an optimized trajectory for a given constraint. The application of the aforementioned methodology to a case study for the purpose of assessing the environmental impact of a helicopter mission, as well as the associated required operational resources is performed and presented.
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LIAO, X. P., W. XIA, and F. Y. LONG. "A COMPUTATIONAL INTELLIGENCE DEVELOPMENT OF OPTIMAL TOOL TRAJECTORY IN SURFACE SPRAY MANUFACTURING." In Proceedings of the 4th International ISKE Conference on Intelligent Systems and Knowledge Engineering. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789814295062_0018.

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Reynoso-Mora, Pedro, and Masayoshi Tomizuka. "LQ-Based Trajectory Tracking of Robotic Manipulators With “Near” Dynamically Feasible Time-Optimal Trajectory." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7271.

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In this paper we study the trajectory tracking of robotic manipulators using LQ methods. We also present the development of an algorithm that generates “near” dynamically feasible time-optimal trajectories with complete dynamics model, which incorporates both Coulomb and viscous friction. It is shown how to incorporate the viscous-friction term through a convex relaxation of the original non-convex formulation. Viscous friction is traditionally ignored in all existing related formulations due to the intractability in solving the non-convex problem. As a case study, the methodology is applied to a 6-DOF industrial manipulator.
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Garcia, Orlando, Omar Santos, Hugo Romero, and Sergio Salazar. "On the tracking trajectory using optimal control in a quadrotor helicopter: Experimental results." In 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS). IEEE, 2015. http://dx.doi.org/10.1109/red-uas.2015.7441001.

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Kruglova, T. N., and A. S. Vlasov. "RESEARCH OF METAHEURISTIC ALGORITHMS FOR SOLVING THE PROBLEMS OF AN OPTIMAL PATH PLANNING." In STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS. DSTU-PRINT, 2020. http://dx.doi.org/10.23947/interagro.2020.1.175-177.

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This paper is devoted to the study of metaheuristic algorithms for solving problems of finding the optimal route for an agricultural mobile robot. Methods of an ant colony, simulated annealing, prohibition search, and a genetic algorithm were considered as the basis for the development of a navigation system capable of selecting the best trajectory in terms of speed and safety according to several criteria. This paper does not compare work with science-based algorithms such as dynamic programming due to the high demands on computing power as the size of the task increases. The aim of the study is to obtain practical results of the work of metaheuristic algorithms.
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McIntosh, Kristoff, Jean Reddinger, Sandipan Mishra, and Di Zhao. "Optimal Trajectory Generation for Transitioning Quadrotor Biplane Tailsitter using Differential Flatness." In Vertical Flight Society 77th Annual Forum & Technology Display. The Vertical Flight Society, 2021. http://dx.doi.org/10.4050/f-0077-2021-16858.

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This paper presents the development of an optimization-based trajectory planner for the autonomous transition of a quadrotor biplane tailsitter (QRBP) between the flight modes of hover to forward flight and forward flight to hover. The trajectory planner is formulated as an optimization problem with an embedded dynamic model of the QRBP, vehicle design constraints (e.g. power), physical constraints (e.g. stall) and initial/terminal states for the transition. A differentially flat reformulation is employed to reduce the computational cost of the trajectory planner for on-board mission planning. The solution of this problem yields time-optimal state and input trajectories for transition. Using this trajectory planner, we generate trajectories for various transition flight missions (from hover to forward flight and vice versa) under various constraints. Further, we demonstrate how the proposed algorithm can also be used to assess the agility of a vehicle in terms of minimum space required to perform a specific maneuver or transition, given physical design constraints (such as maximum power). Finally, we demonstrate trajectory tracking on a high fidelity simulation of a QRBP with a cascaded dynamic-inversion based controller with a control blending strategy between the quadcopter and forward-flight control modes, for hover to forward flight.
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Shestakova, A. O., S. O. Sbrodov, and I. N. Glukhikh. "Development of a Software Solution for Scheduling for Individual Learning Trajectory." In International scientific and practical conference “Smart cities and sustainable development of regions” (SMARTGREENS 2024). Crossref, 2025. https://doi.org/10.63550/iceip.2025.1.1.106.

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This paper deals with the actual problem of creating efficient schedules in various spheres of human activity such as education and transportation. The difficulties in creating optimal schedules are related to a variety of constraints, requirements and constantly changing conditions. The paper discusses the main problems associated with scheduling and proposes approaches and methods to solve them using modern technologies and artificial intelligence techniques. A developed module for integration with an educational institution and a Telegram bot for scheduling classes are presented. The process of generating schedules based on the entered information about students, classes, time and location is described. A genetic algorithm was used to minimize the target function considering all requirements. Plans for further development are presented, including the creation of a website for constraint and requirement selection, the development of a neural network to evaluate the quality of the generated options, and the creation of a mobile version for user-friendliness. Tests of the program on data from Tyumen State University were conducted, showing its potential for efficient schedule creation.
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Borovik, V. S., V. V. Borovik, and O. V. Protsenko. "Modeling of Research Processes’ Automation." In International Conference on Finance, Economics, Management and IT Business (FEMIB 2024). Crossref, 2025. https://doi.org/10.63550/iceip.2025.17.48.001.

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An algorithm for trajectory implementation of scientific research management strategy was developed. Simulation was carried out using the specified algorithm. The calculations were performed using the developed model. It is found that it was advisable to analyze the trajectory of a managerial strategy as a certain realizable trajectory of management carried out within the boundaries of the hypersurface region surrounding the trajectory of optimal management. It was found that the distance from the optimal management trajectory, which determines the region of acceptable values, is estimated by the quality of management -, which is the aggregate statistical value of the “distance” of the real trajectory from the optimal one. The developed model for management strategy realization of research process when solving a scientific problem, taking into account real conditions based on a digital model, allows for the development of a computer program. The program allows you to calculate quickly the trajectory of optimal control of research process according to a given strategy, evaluate the quality of management and present ways of optimal control taking into account the real conditions of research process.
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Reports on the topic "Optimal trajectory development"

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Mousavi, Seyedmostafa, Behzad Rismanchi, Stefan Brey, and Lu Aye. Experimental evaluation of PCM embedded radiant chilled ceiling for efficient space cooling. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau609928685.

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Because of climate change, together with rapid urbanisation and continuous population growth, the global demand for space cooling is increasing dramatically. Under a business-as-usual trajectory, there will be a more than threefold rise in the number of in-use air conditioners worldwide by 2050. A radical shift to innovative space cooling technologies is therefore essential, ones that can sustainably meet the growing requirements. Phase change material embedded radiant chilled ceiling, called PCM-RCC, offers an emerging alternative for more sustainable space cooling provision. This system provides a range of benefits to endusers, in terms of efficiency and indoor environmental quality, together with demand-side flexibility. PCM-RCC, however, is still under development, and further research is needed to realise its full capabilities. The present work experimentally analyses the thermal-energy performance of a PCM-RCC system using a full-scale test cabin equipped with PCM ceiling panels. Here, the transient thermal behaviour of the panels besides the cooling energy delivered in charging-discharging cycles are examined. Additionally, the indoor thermal comfort and peak energy demand reduction enabled by the present PCM-RCC are discussed. Based on the results, typically 4–5 hours of chilled water circulation overnight could sufficiently be able to fully recharge the panels in the morning. Over 80% of the occupancy time was found within Class B thermal comfort defined in ISO 7730. About 70% of the system’s daily electricity usage time was during off-peak hours. The significance of implementing optimal predictive operating schedules was also highlighted to fully utilise PCM-RCC’s potentials.
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