To see the other types of publications on this topic, follow the link: Motion path planning.
Journal articles on the topic 'Motion path planning'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Motion path planning.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Wu, Chi-haur, and Chi-cheng Jou. "Design of a Controlled Spatial Curve Trajectory for Robot Manipulations." Journal of Dynamic Systems, Measurement, and Control 113, no. 2 (1991): 248–58. http://dx.doi.org/10.1115/1.2896372.
Full textAbstract:
For integrating different constraints from robot’s tasks, such as geometry, kinematics, and dynamics, with trajectory planning and robot motion control, a two-layer robot trajectory planning structure is proposed. The structure decomposes the trajectory planning problem into path geometry planning and motion speed planning. By separating speed planning from path geometry planning, two different problems can be solved. The first problem is to incorporate geometric changes of a robot task into both translational and orientational path plannings. By solving it, various spatial curve paths can be planned and the difficulty of predicting rotational motions in the Cartesian space can be removed. The second problem is to incorporate motion constraints into the trajectory planning, such as the constraint of maintaining a desired constant robot speed along any planned geometric path. Through the proposed structure, different robot motion requirements along various spatial curves can be controlled by different speed control functions. To demonstrate the proposed scheme, examples are given.
2
teja, T. Ravi. "Autonomous robot motion path planning using shortest path planning algorithms." IOSR Journal of Engineering 3, no. 01 (2013): 65–69. http://dx.doi.org/10.9790/3021-03116569.
Full text
3
Gonzalez-Lopez, M. J. "Path Tracking in Motion Planning." Computer Journal 36, no. 5 (1993): 515–24. http://dx.doi.org/10.1093/comjnl/36.5.515.
Full text
4
Yokozuka, Masashi, and Osamu Matsumoto. "A Reasonable Path Planning via Path Energy Minimization." Journal of Robotics and Mechatronics 26, no. 2 (2014): 236–44. http://dx.doi.org/10.20965/jrm.2014.p0236.
Full textAbstract:
This paper presents a path planning method by path energy minimizing that enables mobile robots to move smoothly in the real world with optimizing path shape for shortest distance or minimum curvature. It also enables robots to travel safely toward a destination because pedestrian motion prediction is embedded in path planning. This path planning method is based on problems experienced in a robot competition called Tsukuba Challenge. The problems involved nonsmooth motion arising from finite path patterns in A* algorithm, stuck motion arising from frequently path switching, and near misses arising from nonpredictive planning. Our path planning method minimizes pathshape energy defined as the connection between path points. Minimizing energy provides smooth paths and avoids path switching. We propose a path planning method with prediction of dynamic obstacle motion embedded to avoid near misses. Experimental results showed improvements in solving these problems.
5
Guzzi, Jerome, R. Omar Chavez-Garcia, Mirko Nava, Luca Maria Gambardella, and Alessandro Giusti. "Path Planning With Local Motion Estimations." IEEE Robotics and Automation Letters 5, no. 2 (2020): 2586–93. http://dx.doi.org/10.1109/lra.2020.2972849.
Full text
6
Orthey, Andreas, Olivier Roussel, Olivier Stasse, and Michel Taïx. "Motion planning in Irreducible Path Spaces." Robotics and Autonomous Systems 109 (November 2018): 97–108. http://dx.doi.org/10.1016/j.robot.2018.08.012.
Full text
7
Valbahs, Edvards, and Peter Grabusts. "Path Planning Usage for Autonomous Agents." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (August 8, 2015): 40. http://dx.doi.org/10.17770/etr2013vol2.867.
Full textAbstract:
In order to achieve the wide range of the robotic application it is necessary to provide iterative motions among points of the goals. For instance, in the industry mobile robots can replace any components between a storehouse and an assembly department. Ammunition replacement is widely used in military services. Working place is possible in ports, airports, waste site and etc. Mobile agents can be used for monitoring if it is necessary to observe control points in the secret place. The paper deals with path planning programme for mobile robots. The aim of the research paper is to analyse motion-planning algorithms that contain the design of modelling programme. The programme is needed as environment modelling to obtain the simulation data. The simulation data give the possibility to conduct the wide analyses for selected algorithm. Analysis means the simulation data interpretation and comparison with other data obtained using the motion-planning. The results of the careful analysis were considered for optimal path planning algorithms. The experimental evidence was proposed to demonstrate the effectiveness of the algorithm for steady covered space. The results described in this work can be extended in a number of directions, and applied to other algorithms.
8
Niu, Guochen, Yunxiao Zhang, and Wenshuai Li. "Path Planning of Continuum Robot Based on Path Fitting." Journal of Control Science and Engineering 2020 (December 22, 2020): 1–11. http://dx.doi.org/10.1155/2020/8826749.
Full textAbstract:
The Continuum Robot has a multiredundant dof structure, which is extremely advantageous in the unstructured environment, and can complete such tasks as aircraft fuel tank inspection. However, due to its complex kinematics and coupling of joint motion, its motion path planning is also a challenging task. In this paper, a path planning method for Continuum Robot based on an equal curvature model in an aircraft fuel tank environment is proposed. Considering the complexity of calculation and the structural characteristics of Continuum Robot, a feasible obstacle avoidance discrete path is obtained by using the improved RRT algorithm. Then, joint fitting is performed on the existing discrete path according to the kinematic model of Continuum Robot, joint obstacle avoidance was conducted in the process of fitting, and finally, a motion path suitable for the Continuum Robot was selected. A reasonable experiment is designed based on MATLAB, and simulation and analysis results demonstrate excellent performance of this method and feasibility of path planning.
9
Paliwal, Shubham Singh, and Rahul Kala. "Maximum clearance rapid motion planning algorithm." Robotica 36, no. 6 (2018): 882–903. http://dx.doi.org/10.1017/s0263574718000127.
Full textAbstract:
SUMMARYThis paper proposes a new path-planning algorithm which is close to the family of bug algorithms. Path planning is one of the challenging problems in the area of service robotics. In practical applications, traditional methods have some limitations with respect to cost, efficiency, security, flexibility, portability, etc. Our proposed algorithm offers a computationally inexpensive goal-oriented strategy by following a smooth and short trajectory. The paper also presents comparisons with other algorithms. In addition, the paper also presents a test bed which is created to test the algorithm. We have used a two-wheeled differential drive robot for the navigation and only a single camera is used as a feedback sensor. Using an extended Kalman filter, we localize the robot efficiently in the map. Furthermore, we compare the actual path, predicted path and planned path to check the effectiveness of the control system.
10
Li, Ji Ze, and Tao Yang. "The influence of the length of parallel mechanism on path planning." Journal of Physics: Conference Series 2569, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1742-6596/2569/1/012001.
Full textAbstract:
Abstract The path planning of the parallel mechanism should not only consider the motion path of the end effector but also the motion path of the member. As an important factor affecting the workspace of parallel mechanisms, links do not participate in path planning. To realize the intelligence of path planning for parallel mechanisms, a method to determine and modify the feasibility of path planning is proposed based on the parallel 6-DOF attitude adjustment platform. First, the kinematic inverse solution of the motion path of the end effector is carried out to obtain the motion path of the six struts. At the same time, the corresponding workspace is obtained according to the change in the length of the struts, Finally, based on the intersection of the motion path and workspace of the six struts, the success of path planning is determined, and the corresponding path modification method is given. Through the actual experiment and MATLAB simulation, the results show that this method can avoid the motion stop phenomenon caused by a single strut passing through the non-workspace in the path planning of the parallel mechanism.
11
Valbahs, Edvards, Peter Grabusts, and Ilo Dreyer. "Path Planning Methods in Chemical Engineering." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 3 (June 16, 2015): 198. http://dx.doi.org/10.17770/etr2015vol3.188.
Full textAbstract:
Usually, when the practical motion planning and the shortest path are discoursed, mainly the limited number of tasks is observed. Almost all the tasks associated with the path from one point in 2D or 3D space to another point can be attributed to the usual issue in the practical application. Motion planning and the shortest path have vivid and indisputable importance as human activity in such areas as logistics and robotics. In our work we would like to draw particular attention to the field of application seems to be unnoticeable for the task such as motion planning and the shortest path problem. Due to quite simple examples used, we would like to show that the task of motion planning can be used for simulation and optimization of multi-staged and restricted processes which are presented in chemical engineering accordingly. In the article the simulation and optimization of three important chemical-technological processes for the chemical industry are discussed. The work done gave us the possibility to work out software for simulation and optimization of processes that in some cases facilitates and simplifies the work of professionals engaged in the field of chemical engineering.
12
Zhou, Yuquan, Li Yan, Yaxi Han, Hong Xie, and Yinghao Zhao. "A Survey on the Key Technologies of UAV Motion Planning." Drones 9, no. 3 (2025): 194. https://doi.org/10.3390/drones9030194.
Full textAbstract:
Unmanned aerial vehicles (UAVs) are widely employed across diverse fields due to their flexibility and scalability. However, achieving full autonomy remains a challenge as human intervention is still required in most scenarios. Motion planning, a cornerstone of UAV autonomous navigation, has garnered extensive attention, with numerous advanced algorithms having been proposed in recent years. This paper provides a comprehensive overview of UAV motion planning frameworks, systematically addressing three key components: map representation, path planning, and trajectory optimization. Map representation establishes environmental awareness, path planning balances efficiency and safety in path generation, and trajectory optimization refines paths into feasible, energy-efficient motions. Unlike prior reviews focused on specific techniques, this study offers an integrated perspective, helping researchers understand the overall framework and recent advancements in UAV motion planning. Additionally, emerging trends and potential strategies are discussed to improve the efficiency, adaptability, and robustness of UAVs to meet increasingly complex mission requirements.
13
Trujillo Suárez, Carlos Andrés, and Qiaode Jeffrey Ge. "Piecewise line-symmetric spherical motions for orientation interpolation in 5-Axis CNC tool path planning." Revista Facultad de Ingeniería Universidad de Antioquia, no. 60 (November 22, 2012): 62–71. http://dx.doi.org/10.17533/udea.redin.13658.
Full textAbstract:
This paper employs quaternion biarcs to interpolate a set of orientations with angular velocity constraints. The resulting quaternion curve represents a piecewise line-symmetric spherical motion with C1 continuity. The purpose of this effort is to put line-symmetric motions into use from the viewpoint of motion approximation and interpolation, and to present their potential applications in Computerized Numerical Control (CNC) machining simulation and tool path planning. Quaternion biarcs may be used to approximate B-spline quaternion curves that represent rational spherical motions that have applications in robot path planning, CAD/CAM and computer graphics.
14
Gammell, Jonathan D., and Marlin P. Strub. "Asymptotically Optimal Sampling-Based Motion Planning Methods." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (2021): 295–318. http://dx.doi.org/10.1146/annurev-control-061920-093753.
Full textAbstract:
Motion planning is a fundamental problem in autonomous robotics that requires finding a path to a specified goal that avoids obstacles and takes into account a robot's limitations and constraints. It is often desirable for this path to also optimize a cost function, such as path length. Formal path-quality guarantees for continuously valued search spaces are an active area of research interest. Recent results have proven that some sampling-based planning methods probabilistically converge toward the optimal solution as computational effort approaches infinity. This article summarizes the assumptions behind these popular asymptotically optimal techniques and provides an introduction to the significant ongoing research on this topic.
15
Cai, Yiyi, Tuanfa Qin, Yang Ou, and Rui Wei. "Intelligent Systems in Motion." International Journal on Semantic Web and Information Systems 19, no. 1 (2023): 1–35. http://dx.doi.org/10.4018/ijswis.333056.
Full textAbstract:
Simultaneous localization and mapping (SLAM) serves as a cornerstone in autonomous systems and has seen exponential growth in its roles, particularly in facilitating advanced path planning solutions. One emerging avenue of research that is rapidly evolving is the incorporation of multi-sensor fusion techniques to enhance SLAM-based path planning. The paper initiates with a thorough review of various sensor types and their attributes before covering a broad spectrum of both traditional and contemporary algorithms for multi-sensor fusion within SLAM. Performance evaluation metrics pertinent to SLAM and sensor fusion are explored. A special focus is laid on the interconnected roles and applications of multi-sensor fusion in SLAM-based path planning, discussing its significance in navigation scenarios as well as addressing challenges such as computational burden and real-time implementation. This paper sets the stage for future developments in creating more robust, resilient, and efficient SLAM-based path planning systems enabled by multi-sensor fusion.
16
Li, Feng, Young-Chul Kim, and Boyin Xu. "Non-Standard Map Robot Path Planning Approach Based on Ant Colony Algorithms." Sensors 23, no. 17 (2023): 7502. http://dx.doi.org/10.3390/s23177502.
Full textAbstract:
Robot path planning is an important component of ensuring the robots complete work tasks effectively. Nowadays, most maps used for robot path planning obtain relevant coordinate information through sensor measurement, establish a map model based on coordinate information, and then carry out path planning for the robot, which is time-consuming and labor-intensive. To solve this problem, a method of robot path planning based on ant colony algorithms after the standardized design of non-standard map grids such as photos was studied. This method combines the robot grid map modeling with image processing, bringing in calibration objects. By converting non-standard actual environment maps into standard grid maps, this method was made suitable for robot motion path planning on non-standard maps of different types and sizes. After obtaining the planned path and pose, the robot motion path planning map under the non-standard map was obtained by combining the planned path and pose with the non-standard real environment map. The experimental results showed that this method has a high adaptability to robot non-standard map motion planning, can realize robot path planning under non-standard real environment maps, and can make the obtained robot motion path display more intuitive and convenient.
17
Miura, Jun, and Yoshiaki Shirai. "Probabilistic Uncertainty Modeling of Obstacle Motion for Robot Motion Planning." Journal of Robotics and Mechatronics 14, no. 4 (2002): 349–56. http://dx.doi.org/10.20965/jrm.2002.p0349.
Full textAbstract:
This paper describes a method of modeling the motion uncertainty of moving obstacles and its application to mobile robot motion planning. The method explicitly considers three sources of uncertainty: path ambiguity, velocity uncertainty, and observation uncertainty. In the uncertainty model, the position of an obstacle at a certain time point is represented by a probabilistic distribution over possible positions on each possible path of the moving obstacle. Using this model, the best robot motion is selected in a decision-theoretic way. By considering the distribution, not the range, of uncertainty, more efficient behavior of the robot is realized.
18
Fan, Zeyu. "Multi-Point path planning for robots based on deep reinforcement learning." Journal of Physics: Conference Series 2580, no. 1 (2023): 012048. http://dx.doi.org/10.1088/1742-6596/2580/1/012048.
Full textAbstract:
Abstract Motion Planning is a key technology for mobile robots, which decomposes a Motion task that cannot be completed by a single action into multiple discrete actions that can be performed. This paper aims to design a robot motion planning algorithm based on reinforcement learning and make a robot carry out continuous multi-objective point motion planning. Motion planning network is a planning algorithm based on a neural network, and DQN is a classical algorithm in the field of reinforcement learning. Based on the two kinds of algorithm for motion planning, the Deep Q - learning algorithm chooses the robot’s next target, and then through the motion planning of the network between the current coordinates to the next target path planning. This paper analyzes the performance of the multi-point motion planning algorithm, and the results show that the algorithm is able to a higher success rate of successful completion of the task planning, but the reward strategy derived from the experiment still has the possibility of optimization.
19
Krustev, Evgeny, and Ljubomir Lilov. "Kinematic path control of robot arms." Robotica 4, no. 2 (1986): 107–16. http://dx.doi.org/10.1017/s0263574700008572.
Full textAbstract:
SUMMARYPath planning of the end effector motion is here treated from the viewpoint of the path invariance under the transformations of its parametrical representation. Thus, a new method for path planning of the robot arm motion is being developed. Both the problems of finding the end effector time optimal motion and the end effector motion with a prescribed velocity profile along a preplanned path are being solved by the employment of this method. Simulation results are presented and some aspects of implementation are also discussed.
20
Li, Yun, Xinqi He, Zhenkun Lu, Peiguang Jing, and Yishan Su. "Comprehensive Ocean Information-Enabled AUV Motion Planning Based on Reinforcement Learning." Remote Sensing 15, no. 12 (2023): 3077. http://dx.doi.org/10.3390/rs15123077.
Full textAbstract:
Motion planning based on the reinforcement learning algorithms of the autonomous underwater vehicle (AUV) has shown great potential. Motion planning algorithms are primarily utilized for path planning and trajectory-tracking. However, prior studies have been confronted with some limitations. The time-varying ocean current affects algorithmic sampling and AUV motion and then leads to an overestimation error during path planning. In addition, the ocean current makes it easy to fall into local optima during trajectory planning. To address these problems, this paper presents a reinforcement learning-based motion planning algorithm with comprehensive ocean information (RLBMPA-COI). First, we introduce real ocean data to construct a time-varying ocean current motion model. Then, comprehensive ocean information and AUV motion position are introduced, and the objective function is optimized in the state-action value network to reduce overestimation errors. Finally, state transfer and reward functions are designed based on real ocean current data to achieve multi-objective path planning and adaptive event triggering in trajectorytracking to improve robustness and adaptability. The numerical simulation results show that the proposed algorithm has a better path planning ability and a more robust trajectory-tracking effect than those of traditional reinforcement learning algorithms.
21
Tremblay, Louis-Francis Y., Marc Arsenault, and Meysar Zeinali. "Development of a trajectory planning algorithm for a 4-DoF rockbreaker based on hydraulic flow rate limits." Transactions of the Canadian Society for Mechanical Engineering 44, no. 4 (2020): 501–10. http://dx.doi.org/10.1139/tcsme-2019-0173.
Full textAbstract:
In this paper, a novel trajectory planning methodology is proposed for use within a semi-automated hydraulic rockbreaker system. The objective of the proposed method is to minimize the trajectory duration while hydraulic fluid flow rate limits are respected. Within the trajectory planning methodology, a point-to-point path planning approach based on the decoupling of the motion of the rockbreaker’s first joint is compared with an alternative approach based on Cartesian straight-line motion. Each of these path types is parameterized as a function of time based on an imposed trajectory profile that ensures smooth rockbreaker motions. A constrained nonlinear optimization problem is formulated and solved with the trajectory duration as the objective function while constraints are applied to ensure that flow rate limits through the rockbreaker’s proportional valves and hydraulic pump are not exceeded. The proposed methodology is successfully implemented to compute a set of representative trajectories, with the path planning approach based on the decoupling of the motion of the rockbreaker’s first joint consistently producing shorter trajectory durations.
22
Aomura, Shigeru, and Takehiko Kawabe. "Study on the Motion Planning for a Manipulator Using Extended Manipulability(Autonomous Path Planning,Session: MP1-A)." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2004.4 (2004): 26. http://dx.doi.org/10.1299/jsmeicam.2004.4.26_1.
Full text
23
Bai, Xinlin, Xiwen Li, Zhen Zhao, et al. "Motion Planning of Ground Simulator for Space Instable Target Based on Energy Saving." Machines 9, no. 12 (2021): 368. http://dx.doi.org/10.3390/machines9120368.
Full textAbstract:
In order to achieve the high-precision motion trajectory in ground experiment of space instable target (SIT) while reducing the energy consumption of the motion simulator, a robot motion planning method based on energy saving is proposed. Observable-based ground robot motion experiment system for SIT is designed and motion planning process is illustrated. Discrete optimization mathematical model of energy consumption of motion simulator is established. The general motion form of the robot joints in ground test is given. The optimal joint path of motion simulator based on energy consumption under discontinuous singularity configuration is solved by constructing the complete energy consumption directed path and Dijkstra algorithm. An improved method by adding the global optimization algorithm is used to decouple the coupled robot joints to obtain the minimum energy consumption path under the continuous singularity configuration of the motion simulator. Simulations are carried out to verify the proposed solution. The simulation data show that total energy saving of motion simulator joints adopting the proposed method under the condition of non-singularity configuration, joints coupled motion with continuous singularity configuration, and coexistence of non-singularity path and continuous singularity path are, respectively, 72.67%, 28.24%, and 62.23%, which proves that the proposed method can meet the requirements of ground motion simulation for SIT and effectively save energy.
24
Zhang, Yingyu. "Motion path planning algorithm for dynamic graphics in visual arts." Journal of Physics: Conference Series 2963, no. 1 (2025): 012008. https://doi.org/10.1088/1742-6596/2963/1/012008.
Full textAbstract:
Abstract Aiming at the problems of non-smooth motion and unnatural trajectory in motion path planning of dynamic graphics in visual arts, this paper proposes a path planning algorithm based on multi-stage optimization. Firstly, the initial motion path is fitted and smoothed by using Bezier curves to ensure that the motion trajectory of dynamic graphics has high continuity and naturalness. Next, a multi-objective optimization strategy based on a genetic algorithm is introduced to comprehensively optimize the path smoothness, motion speed change, and visual comfort through the adaptive evaluation function. Finally, a dynamic weight adjustment mechanism is adopted to adapt to the changes in the requirements of different visual scenes in real time. Specifically, the standard deviation of the curvature variation of the path generated by the multi-stage optimization-based path planning algorithm is 0.0459, which is much lower than that of the other two algorithms; the mean squared error (MSE) of the speed change rate is 0.65, which is significantly reduced compared with other methods; in the visual comfort test, the fixation point dwell time is 360 ms, which is significantly higher than other methods. The dynamic deviation is the lowest. Experimental data shows that the algorithm in this paper effectively solves the problem of unsmooth motion trajectories of dynamic graphics, significantly improves the naturalness and visual experience of the path, and proves the practicability and superiority of the algorithm in visual art creation.
25
Erickson, Lawrence, and Steven LaValle. "A Simple, but NP-Hard, Motion Planning Problem." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (2013): 1388–93. http://dx.doi.org/10.1609/aaai.v27i1.8545.
Full textAbstract:
Determining the existence of a collision-free path between two points is one of the most fundamental questions in robotics. However, in situations where crossing an obstacle is costly but not impossible, it may be more appropriate to ask for the path that crosses the fewest obstacles. This may arise in both autonomous outdoor navigation (where the obstacles are rough but not completely impassable terrain) or indoor navigation (where the obstacles are doors that can be opened if necessary). This problem, the minimum constraint removal problem, is at least as hard as the underlying path existence problem. In this paper, we demonstrate that the minimum constraint removal problem is NP-hard for navigation in the plane even when the obstacles are all convex polygons, a case where the path existence problem is very easy.
26
Krustev, Evgeny, and Ljubomir Lilov. "Extended kinematic path control of robot arms." Robotica 5, no. 1 (1987): 45–53. http://dx.doi.org/10.1017/s0263574700009632.
Full textAbstract:
SUMMARYPath planning a robot arm motion essentially requires that the constraints of the joint variables and the vector of the joint motion rates are taken into account. In order to satisfy the constraints of the joint variables a sliding mode is being employed together with the developed kinematic path control method. The extended form of the kinematic path control method, here proposed, treats simultaneously the constraints of the joint variables and the vector of joint motion rates in path planning a robot arm motion.
27
Wang, Xiaoting, Xiangxu Meng, Chenglei Yang, and Junqing Zhang. "Data Driven Avatars Roaming in Digital Museum." International Journal of Virtual Reality 8, no. 3 (2009): 13–18. http://dx.doi.org/10.20870/ijvr.2009.8.3.2736.
Full textAbstract:
This paper describes a motion capture (mocap) data-driven digital museum roaming system with high walking reality. We focus on three main questions: the animation of avatars; the path planning; and the collision detection among avatars. We use only a few walking clips from mocap data to synthesize walking motions with natural transitions, any direction and any length. Let the avatars roam in the digital museum with its Voronoi skeleton path, shortest path or offset path. And also we use Voronoi diagram to do collision detection. Different users can set up their own avatars and roam along their own path. We modify the motion graph method by classify the original mocap data and set up their motion graph which can improve search efficiency greatly.
28
Lin, Jin. "Path planning based on reinforcement learning." Applied and Computational Engineering 5, no. 1 (2023): 853–58. http://dx.doi.org/10.54254/2755-2721/5/20230728.
Full textAbstract:
With the wide application of mobile robots in industry, path planning has always been a difficult problem for mobile robots. Reinforcement learning algorithms such as Q-learning play a huge role in path planning. Traditional Q-learning algorithm mainly uses - greedy search policy. But for a fixed search factor -greedy. For example, the problems of slow convergence speed, time-consuming and many continuous action transformations (such as the number of turns during robot movement) are not conducive to the stability requirements of mobile robots in industrial transportation. Especially for the transportation of dangerous chemicals, continuous transformation of turns will increase the risk of objects toppling. This paper proposes a new method based on - greedy 's improved dynamic search strategy is used to improve the stability of mobile robots in motion planning. The experiment shows that the dynamic search strategy converges faster, consumes less time, has less continuous transformation times of action, and has higher motion stability in the test environment.
29
Kulathunga, G., D. Devitt, R. Fedorenko, and A. Klimchik. "Path Planning Followed by Kinodynamic Smoothing for Multirotor Aerial Vehicles (MAVs)." Nelineinaya Dinamika 17, no. 4 (2021): 491–505. http://dx.doi.org/10.20537/nd210410.
Full textAbstract:
Any obstacle-free path planning algorithm, in general, gives a sequence of waypoints that connect start and goal positions by a sequence of straight lines, which does not ensure the smoothness and the dynamic feasibility to maneuver the MAV. Kinodynamic-based motion planning is one of the ways to impose dynamic feasibility in planning. However, kinodynamic motion planning is not an optimal solution due to high computational demands for real-time applications. Thus, we explore path planning followed by kinodynamic smoothing while ensuring the dynamic feasibility of MAV. The main difference in the proposed technique is not to use kinodynamic planning when finding a feasible path, but rather to apply kinodynamic smoothing along the obtained feasible path. We have chosen a geometric-based path planning algorithm “RRT*” as the path finding algorithm. In the proposed technique, we modified the original RRT* introducing an adaptive search space and a steering function that helps to increase the consistency of the planner. Moreover, we propose a multiple RRT* that generates a set of desired paths. The optimal path from the generated paths is selected based on a cost function. Afterwards, we apply kinodynamic smoothing that will result in a dynamically feasible as well as obstacle-free path. Thereafter, a b-spline-based trajectory is generated to maneuver the vehicle autonomously in unknown environments. Finally, we have tested the proposed technique in various simulated environments. According to the experiment results, we were able to speed up the path planning task by 1.3 times when using the proposed multiple RRT* over the original RRT*.
30
Yan, Fu Yu, Fan Wu, Fei Peng, and Zhi Jie Zhu. "On Improving Path Clearance Optimization Method for Motion Planning." Advanced Materials Research 926-930 (May 2014): 3128–31. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3128.
Full textAbstract:
The efficiency of path clearance optimization method is low and the corresponding path may collide with obstacles when applying it to the original path planned by RRTConCon algorithm. The paper analyzed the original path clearance and corridor width and chose proper moving distance towards the medial axis and binary search step. The paper also analyzed the collision reason and proposed an method to deal with it. The method moves collision configurations to the free space and retracts them to the medial axis, then adds them to the retracted path. The experimental results showed the measures are effective to improve efficiency and could deal with collision problem.
31
Ji, Xue Song, Ping Xu, and Guo Chen Niu. "Visual-Based Motion Planning for Autonomous Humanoid Service Robot." Advanced Materials Research 143-144 (October 2010): 1031–35. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.1031.
Full textAbstract:
A visual-based autonomous motion planning algorithm is designed to guide the robot to take the elevator autonomously. The floor chosen operation as well as the path planning and motion control for the robot’s in-out elevator are the two critical issues. A visual-based motion regulation method is proposed in this paper, so is a manipulator motion planning algorithm based on image Jacobian Matrix. Fuzzy logic is used to mobile path planning. Experimental results on humanoid service robot proves the validity of this control system.
32
Yoshida, Eiichi, Fumio Kanehiro, Kazuhito Yokoi, and Pierre Gergondet. "Online Motion Planning using Path Deformation and Replanning." Journal of the Robotics Society of Japan 29, no. 8 (2011): 716–25. http://dx.doi.org/10.7210/jrsj.29.716.
Full text
33
Moreno, Luis, and Eladio Dapena. "Path quality measures for sensor-based motion planning." Robotics and Autonomous Systems 44, no. 2 (2003): 131–50. http://dx.doi.org/10.1016/s0921-8890(03)00041-1.
Full text
34
Krishnan, Jinu, U. P. Rajeev, J. Jayabalan, and D. S. Sheela. "Optimal motion planning based on path length minimisation." Robotics and Autonomous Systems 94 (August 2017): 245–63. http://dx.doi.org/10.1016/j.robot.2017.04.014.
Full text
35
Parman, Setyamartana, and Mahmud Iwan Solihin. "Self-motion behaviors of kinematically redundant manipulator for continuous path planning." Journal of Advanced Technology and Multidiscipline 1, no. 1 (2022): 1–9. http://dx.doi.org/10.20473/jatm.v1i1.39600.
Full textAbstract:
This paper presents self-motion behaviors of 3-DOF planar robotic arm when it tracks a predefined end-effector path. In this case, the self-motion contributes to geometry of a motion envelope. The Bezier curve degree fifth is utilized as the tracked path. Different geometry of the motion envelope can be used to avoid collision while it also follows the tracked path accurately. A theta global as closed form solution of 3-DOF planar robot is modeled as a polynomial degree sixth. A Genetic Algorithm (GA) as one of meta-heuristic optimizations is used to find optimal solution of the path planning approach. An effect of initial and final joint angles in the robotic arm motion is also investigated. The theta global trajectories are also possible to contain an imaginary number. The imaginary number of the theta global trajectories can be used as a sign that position errors are present and the trajectories need to be repaired using the self-motion analysis.
36
Salzman, Oren, Brian Hou, and Siddhartha Srinivasa. "Efficient Motion Planning for Problems Lacking Optimal Substructure." Proceedings of the International Conference on Automated Planning and Scheduling 27 (June 5, 2017): 531–39. http://dx.doi.org/10.1609/icaps.v27i1.13855.
Full textAbstract:
We consider the motion-planning problem of planning a collision-free path of a robot in the presence of risk zones. The robot is allowed to travel in these zones but is penalized in a super-linear fashion for consecutive accumulative time spent there. We suggest a natural cost function that balances path length and risk-exposure time. Specifically, we consider the discrete setting where we are given a graph, or a roadmap, and we wish to compute the minimal-cost path under this cost function. Interestingly, paths defined using our cost function do not have an optimal substructure. Namely, subpaths of an optimal path are not necessarily optimal. Thus, the Bellman condition is not satisfied and standard graph-search algorithms such as Dijkstra cannot be used. We present a path-finding algorithm, which can be seen as a natural generalization of Dijkstra’s algorithm. Our algorithm runs in O ((n B · n) log(n B · n) + n B · m) time, where n and m are the number of vertices and edges of the graph, respectively, and n B is the number of intersections between edges and the boundary of the risk zone. We present simulations on robotic platforms demonstrating both the natural paths produced by our cost function and the computational efficiency of our algorithm.
37
Keanly, Oran, and Jacobus Adriaan Albertus Engelbrecht. "Optimization-based path planning and collision avoidance for autonomous racing." MATEC Web of Conferences 388 (2023): 04018. http://dx.doi.org/10.1051/matecconf/202338804018.
Full textAbstract:
This paper presents a hierarchical motion planner for autonomous racing. The long-term motion planner functions offline and formulates the optimal motion plan for the entire race track. The short-term collision avoidance planner functions online and formulates a motion plan for a limited horizon ahead of the autonomous car when an obstacle is detected in the path of the vehicle. The motion planners formulate the planning problems as optimal control problems and solve the resulting optimizations using an interior point optimizer (IPOPT). Simulation experiments show that an autonomous vehicle using the motion planner is able to race around the track with minimum lap time while avoiding unexpected obstacles.
38
Shiller, Zvi, and William Serate. "Trajectory Planning of Tracked Vehicles." Journal of Dynamic Systems, Measurement, and Control 117, no. 4 (1995): 619–24. http://dx.doi.org/10.1115/1.2801122.
Full textAbstract:
This paper presents a method for computing the track forces and track speeds of planar tracked vehicles, required to follow a given path at specified speeds on horizontal and inclined planes. It is shown that the motions of a planar tracked vehicle are constrained by a velocity dependent nonholonomic constraint, derived from the force equation perpendicular to the tracks. This reduces the trajectory planning problem to determining the slip angle between the vehicle and the path tangent that satisfies the nonholonomic constraint along the entire path. Once the slip angle has been determined, the track forces are computed from the remaining equations of motion. Computing the slip angle is shown to be an initial boundary-value problem, formulated as a parameter optimization. This computational scheme is demonstrated numerically for a planar vehicle moving along circular paths on horizontal and inclined planes.
39
Qiao, Dong. "Motion planning optimization of trajectory path of space manipulators." International Journal of Metrology and Quality Engineering 10 (2019): 11. http://dx.doi.org/10.1051/ijmqe/2019011.
Full textAbstract:
With the development of the aerospace industry, the work carried out inside and outside the weightless space station is becoming more and more complicated. In order to ensure the safety of astronauts, space manipulators are used for operation, but it will disturb the space station that is a base during work. In order to solve the above problems, in this paper, the planning method of the motion trajectory of manipulators, the motion model of manipulators and the particle swarm optimization (PSO) algorithm used for optimizing the trajectory are briefly introduced, the multi-population co-evolution method is used to improve the PSO algorithm, and the above two algorithms are used to optimize the motion trajectory of the floating pedestal space manipulator with three free degrees of rotation in the same plane by the matrix laboratory (MATLAB) software. It is compared with genetic algorithm. The results show that the improved PSO algorithm can converge to a better global optimal fitness with fewer iterations compared with the traditional PSO algorithm and genetic algorithm. The obtained motion trajectory optimized by the improved PSO algorithm has less disturbances to the pedestal posture, and less time is required to achieve the target motion; moreover the changes of mechanical arm joint are more stable during the motion.
40
Ma, Hao, Wenhui Pei, and Qi Zhang. "Research on Path Planning Algorithm for Driverless Vehicles." Mathematics 10, no. 15 (2022): 2555. http://dx.doi.org/10.3390/math10152555.
Full textAbstract:
In a complex environment, although the artificial potential field (APF) method of improving the repulsion function solves the defect of local minimum, the planned path has an oscillation phenomenon which cannot meet the vehicle motion. In order to improve the efficiency of path planning and solve the oscillation phenomenon existing in the improved artificial potential field method planning path. This paper proposes to combine the improved artificial potential field method with the rapidly exploring random tree (RRT) algorithm to plan the path. First, the improved artificial potential field method is combined with the RRT algorithm, and the obstacle avoidance method of the RRT algorithm is used to solve the path oscillation; The vehicle kinematics model is then established, and under the premise of ensuring the safety of the vehicle, a model predictive control (MPC) trajectory tracking controller with constraints is designed to verify whether the path planned by the combination of the two algorithms is optimal and conforms to the vehicle motion. Finally, the feasibility of the method is verified in simulation. The simulation results show that the method can effectively solve the problem of path oscillation and can plan the optimal path according to different environments and vehicle motion.
41
Esmaiel, Hamada, Guolin Zhao, Zeyad A. H. Qasem, Jie Qi, and Haixin Sun. "Double-Layer RRT* Objective Bias Anytime Motion Planning Algorithm." Robotics 13, no. 3 (2024): 41. http://dx.doi.org/10.3390/robotics13030041.
Full textAbstract:
This paper proposes a double-layer structure RRT* algorithm based on objective bias called DOB-RRT*. The algorithm adopts an initial path with an online optimization structure for motion planning. The first layer of RRT* introduces a feedback-based objective bias strategy with segment forward pruning processing to quickly obtain a smooth initial path. The second layer of RRT* uses the heuristics of the initial tree structure to optimize the path by using reverse maintenance strategies. Compared with conventional RRT and RRT* algorithms, the proposed algorithm can obtain the initial path with high quality, and it can quickly converge to the progressive optimal path during the optimization process. The performance of the proposed algorithm is effectively evaluated and tested in real experiments on an actual wheeled robotic vehicle running ROS Kinetic in a real environment.
42
Fan, Li, Liao, et al. "Second Path Planning for Unmanned Surface Vehicle Considering the Constraint of Motion Performance." Journal of Marine Science and Engineering 7, no. 4 (2019): 104. http://dx.doi.org/10.3390/jmse7040104.
Full textAbstract:
When utilizing the traditional path planning method for unmanned surface vehicles (USVs), ‘planning-failure’ is a common phenomenon caused by the inflection points of large curvatures in the planned path, which exceed the performances of USVs. This paper presents a second path planning method (SPP), which is an initial planning path optimization method based on the geometric relationship of the three-point path. First, to describe the motion performance of a USV in conjunction with the limited test data, a method of integral nonlinear least squares identification is proposed to rapidly obtain the motion constraint of the USV merely by employing a zig zag test. It is different from maneuverability identification, which is performed in combination with various tests. Second, the curvature of the planned path is limited according to the motion performance of the USV based on the traditional path planning, and SPP is proposed to make the maximum curvature radius of the optimized path smaller than the rotation curvature radius of the USV. Finally, based on the ‘Dolphin 1’ prototype USV, comparative simulation experiments were carried out. In the experiment, the path directly obtained by the initial path planning and the path optimized by the SPP method were considered as the tracking target path. The artificial potential field method was used as an example for the initial path planning. The experimental results demonstrate that the tracking accuracy of the USV significantly improved after the path optimization using the SPP method.
43
Mann, Moshe P., Lior Damti, and David Zarrouk. "Minimally actuated hyper-redundant robots: Motion planning methods based on fractals and self-organizing systems." International Journal of Advanced Robotic Systems 16, no. 2 (2019): 172988141983158. http://dx.doi.org/10.1177/1729881419831586.
Full textAbstract:
This article presents a motion planning method for a novel hyper-redundant robot with minimal actuation based on the principles of fractals and self-organizing systems. The robot consists of multiple links connected by passive joints and a movable actuator. The actuator travels over the links to a given joint and adjusts the relative angle between the two adjacent links allowing the robot to undergo the same wide range of motions of hyper-redundant robot but with only one actuator. A suitable objective of the motion planner is to minimize the number of actuator traversals, which translates into minimizing the number of bends in the c-space trajectory. To this end, we propose a novel method for motion planning using fractals and self-organizing systems. A self-similar pattern for the path is implemented to map a path from start to finish. Each iteration of path segments is of smaller dimension than the previous one and is appended to it, just as in classical fractals. This process continues until a feasible trajectory is calculated. Self-organizing systems are then applied to this trajectory post-processing to optimize it by eliminating bends in the path. Examples of the robot maneuvering around obstacles and through confined spaces are shown to demonstrate the efficacy of the motion planner.
44
Sakawa, Yoshiyuki, and Takao Akiyama. "Path Planning of Space Robots by Using Nonlinear Optimization Technique." Journal of Robotics and Mechatronics 6, no. 5 (1994): 356–59. http://dx.doi.org/10.20965/jrm.1994.p0356.
Full textAbstract:
A space robot, which consists of a satellite base and a manipulator mounted on it, is expected to perform various tasks involved in the construction and maintenance of space structures. Since the angular momentum of a space robot system is conserved, the motion of the system is subject to nonholonomic constraints. When the manipulator makes motion from an initial position to a desired position, variation of the base orientation depends on the trajectory of the motion owing to the nonholonomic property of the system. Since the satellite base is desired to have a constant orientation, we seek such a trajectory of the manipulator that a given motion is attained, that the base orientation is unchanged before and after the motion, and that the integral of the sum of the squares of accelerations of the joint angles is minimized during motion. First, we derive the equations of motion of the space robot, where the orientation of the satellite base is expressed in terms of Euler quaternions. We express the motion of joint angles in terms of the truncated Fourier series, and apply a nonlinear programming technique using a sequential quadratic programming algorithm to determine the optimal coefficients of the Fourier series. Some results of numerical computations are shown.
45
Kim, Chyon Hae, Hiroshi Tsujino, and Shigeki Sugano. "Rapid Short-Time Path Planning for Phase Space." Journal of Robotics and Mechatronics 23, no. 2 (2011): 271–80. http://dx.doi.org/10.20965/jrm.2011.p0271.
Full textAbstract:
This paper addresses optimal motion for general machines. Approximation for optimal motion requires a global path planning algorithm that precisely calculates the whole dynamics of a machine in a brief calculation. We propose a path planning algorithm that consists of path searching and pruning algorithms. The pruning algorithmis based on our analysis of state resemblance in general phase space. To confirm precision, calculation cost, optimality and applicability of the proposed algorithm, we conducted several shortest time path planning experiments for the dynamic models of double inverted pendulums. Precision to reach the goal states of the pendulums was better than other algorithms. Calculation cost was 58 times faster at least. We could tune optimality of proposed algorithm via resolution parameters. A positive correlation between optimality and resolutions was confirmed. Applicability was confirmed in a torque based position and velocity feedback control simulation. As a result of this simulation, the double inverted pendulums tracked planned motion under noise while keeping within torque limitations.
46
Cohen, Liron, Tansel Uras, T. K. Kumar, and Sven Koenig. "Optimal and Bounded-Suboptimal Multi-Agent Motion Planning." Proceedings of the International Symposium on Combinatorial Search 10, no. 1 (2021): 44–51. http://dx.doi.org/10.1609/socs.v10i1.18501.
Full textAbstract:
Multi-Agent Motion Planning (MAMP) is the task of finding conflict-free kinodynamically feasible plans for agents from start to goal states. While MAMP is of significant practical importance, existing solvers are either incomplete, inefficient or rely on simplifying assumptions. For example, Multi-Agent Path Finding (MAPF) solvers conventionally assume discrete timesteps and rectilinear movement of agents between neighboring vertices of a graph. In this paper, we develop MAMP solvers that obviate these simplifying assumptions and yet generalize the core ideas of state-of-the-art MAPF solvers. Specifically, since different motions may take arbitrarily different durations, MAMP solvers need to efficiently reason with continuous time and arbitrary wait durations. To do so, we adapt (Enhanced) Conflict-Based Search to continuous time and develop a novel bounded-suboptimal extension of Safe Interval Path Planning, called Soft Conflict Interval Path Planning. On the theoretical side, we justify the completeness, optimality and bounded-suboptimality of our MAMP solvers. On the experimental side, we show that our MAMP solvers scale well with increasing suboptimality bounds.
47
Wang, Zhaotian, Yezhuo Li, and Yan-An Yao. "Motion and path planning of a novel multi-mode mobile parallel robot based on chessboard-shaped grid division." Industrial Robot: An International Journal 45, no. 3 (2018): 390–400. http://dx.doi.org/10.1108/ir-01-2018-0001.
Full textAbstract:
Purpose The purpose of this paper is to put forward a rolling assistant robot with two rolling modes, and the multi-mode rolling motion strategy with path planning algorithm, which is suitable to this multi-mode mobile robot, is proposed based on chessboard-shaped grid division (CGD). Design/methodology/approach Based on the kinematic analysis and motion properties of the mobile parallel robot, the motion strategy based on CGD path planning algorithm of a mobile robot with two rolling modes moving to a target position is divided into two parts, which are local self-motion planning and global path planning. In the first part, the mobile parallel robot can move by switching and combining the two rolling modes; and in the second part, the specific algorithm of the global path planning is proposed according to the CGD of the moving ground. Findings The assistant robot, which is a novel 4-RSR mobile parallel robot (where R denotes a revolute joint and S denotes a spherical joint) integrating operation and rolling locomotion (Watt linkage rolling mode and 6R linkage rolling mode), can work as a moving spotlight or worktable. A series of simulation and prototype experiment results are presented to verify the CGD path planning strategy of the robot, and the performance of the path planning experiments in simulations and practices shows the validation of the path planning analysis. Originality/value The work presented in this paper is a further exploration to apply parallel mechanisms with two rolling modes to the field of assistant rolling robots by proposing the CGD path planning strategy. It is also a new attempt to use the specific path planning algorithm in the field of mobile robots for operating tasks.
48
Chen, Rong, Huashan Song, Ling Zheng, and Bo Wang. "Robot Motion Planning Based on an Adaptive Slime Mold Algorithm and Motion Constraints." World Electric Vehicle Journal 15, no. 7 (2024): 296. http://dx.doi.org/10.3390/wevj15070296.
Full textAbstract:
The rapid advancement of artificial intelligence technology has significantly enhanced the intelligence of mobile robots, facilitating their widespread utilization in unmanned driving, smart home systems, and various other domains. As the scope, scale, and complexity of robot deployment continue to expand, there arises a heightened demand for enhanced computational power and real-time performance, with path planning emerging as a prominent research focus. In this study, we present an adaptive Lévy flight–rotation slime mold algorithm (LRSMA) for global robot motion planning, which incorporates LRSMA with the cubic Hermite interpolation. Unlike traditional methods, the algorithm eliminates the need for a priori knowledge of appropriate interpolation points. Instead, it autonomously detects the convergence status of LRSMA, dynamically increasing interpolation points to enhance the curvature of the motion curve when it surpasses the predefined threshold. Subsequently, it compares path lengths resulting from two different objective functions to determine the optimal number of interpolation points and the best path. Compared to LRSMA, this algorithm reduced the minimum path length and average processing time by (2.52%, 3.56%) and (38.89%, 62.46%), respectively, along with minimum processing times. Our findings demonstrate that this method effectively generates collision-free, smooth, and curvature-constrained motion curves with the least processing time.
49
Berman, Sigal, Dario G. Liebermann, and Joseph McIntyre. "Constrained motion control on a hemispherical surface: path planning." Journal of Neurophysiology 111, no. 5 (2014): 954–68. http://dx.doi.org/10.1152/jn.00132.2013.
Full textAbstract:
Surface-constrained motion, i.e., motion constraint by a rigid surface, is commonly found in daily activities. The current work investigates the choice of hand paths constrained to a concave hemispherical surface. To gain insight regarding paths and their relationship with task dynamics, we simulated various control policies. The simulations demonstrated that following a geodesic path (the shortest path between 2 points on a sphere) is advantageous not only in terms of path length but also in terms of motor planning and sensitivity to motor command errors. These stem from the fact that the applied forces lie in a single plane (that of the geodesic path). To test whether human subjects indeed follow the geodesic, and to see how such motion compares to other paths, we recorded movements in a virtual haptic-visual environment from 11 healthy subjects. The task comprised point-to-point motion between targets at two elevations (30° and 60°). Three typical choices of paths were observed from a frontal plane projection of the paths: circular arcs, straight lines, and arcs close to the geodesic path for each elevation. Based on the measured hand paths, we applied k-means blind separation to divide the subjects into three groups and compared performance indicators. The analysis confirmed that subjects who followed paths closest to the geodesic produced faster and smoother movements compared with the others. The “better” performance reflects the dynamical advantages of following the geodesic path and may also reflect invariant features of control policies used to produce such a surface-constrained motion.
50
Guo, Yinjing, Hui Liu, Xiaojing Fan, and Wenhong Lyu. "Research Progress of Path Planning Methods for Autonomous Underwater Vehicle." Mathematical Problems in Engineering 2021 (February 12, 2021): 1–25. http://dx.doi.org/10.1155/2021/8847863.
Full textAbstract:
Path planning is a key technology for autonomous underwater vehicle (AUV) navigation. With the emphasis and research on AUV, AUV path planning technology is continuously developing. Path planning techniques generally include environment modelling methods and path planning algorithms. Based on a brief description of the environment modelling methods, this paper focuses on the path planning algorithms commonly used by AUV. According to the basic principles of the algorithm, the AUV path planning algorithms are divided into four categories: artificial potential field methods, geometric model search methods, random sampling methods, and intelligent bionic methods. In this review, we summarize in detail the development and application of various path planning algorithms in recent years. Meanwhile, we analyse the advantages and disadvantages of various algorithms and their improvement methods. Obstacles, ocean currents, and undersea terrain have an impact on AUV path planning. Therefore, how to deal with the complex underwater environment adds some limits to AUV path planning algorithms. In addition to the external environment, path planning algorithms also need to consider AUV’s physical constraints, such as energy constraints and motion constraints. Then, we analyse the motion constraints in AUV path planning. Finally, we discuss the development direction of AUV path planning algorithm. Time-varying ocean currents, special obstacles, multiobjective constraints, and practicability will be the problems that AUV path planning algorithms need to solve.