An Optimal Smooth-Path Motion Planning Method for a Car-like Mobile Robot
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thientd@hcmute.edu.vnDOI:
https://doi.org/10.54644/jte.75A.2023.1276Từ khóa:
Smooth-path motion planning, Car-like mobile robot, Genetic algorithm, Potential field, Dubins curve, Nonholonomic constraintsTóm tắt
This paper proposes an optimal motion planning method consisting of a genetic algorithm (GA), potential field (PF), and Dubins curve for a Car-like mobile robot to solve the problem of finding the shortest and most feasible path in the global environment. Firstly, the GA finds the shortest path by evaluating, selecting, crossing over, and mutating from the initial population and finally provides the strongest individual evolution. Then the result from the GA is further applied with the PF algorithm to improve the ability of obstacle avoidance in the environment. Finally, the Dubins curve method is combined to smooth the path and helps the Car-like mobile robot solve the nonholonomic constraints problem. The major advantages of this method include finding the shortest path, improving avoidance obstacle ability, and smoothing the output path in an environment effectively. The simulation of the proposed method is executed on MATLAB to verify the ability to solve motion planning problems for a Car-like mobile robot.
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B. Tang, Z. Zhu, and J. Luo, “Hybridizing Particle Swarm Optimization and Differential Evolution for the Mobile Robot Global Path Planning,” International Journal of Advanced Robotic Systems, vol. 13, no. 3, 2016, doi: 10.5772/63812.
S. G. Tzafestas, Introduction to Mobile Robot Control, Elsevier, 2014.
K. Kozlowski and D. Pazderski, “Modeling and control of a 4-wheel skid-steering mobile robot,” International journal of applied mathematics and computer science, vol. 14, no. 4, pp. 477–496, 2004.
C. Prahacs, A. Saudners, M. K. Smith, D. McMordie, and M. Buehler, “Towards Legged Amphibious Mobile Robotics,” in Proceedings of the Canadian Engineering Education Association (CEEA), Montreal, Canada, 2004, doi: 10.24908/pceea.v0i0.4043
H. Shakhatreh et al., “Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges,” IEEE Access, vol. 7, pp. 48572–48634, 2019.
G. Marani, S. K. Choi, and J. Yuh, “Underwater autonomous manipulation for intervention missions AUVs,” vol. 36, pp. 15–23, 2009.
Y. S. and W. W. Yan Zhuang, “Mobile robot hybrid path planning in an obstacle-cluttered environment based on steering control and improved distance propagating,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 6, p. 4198, 2012.
C. Weiming, T. Zhenmin, Z. Chunxia, T. Lei, and G. Zhibo, “Path Planning for Nonholonomic Car-like Mobile Robots Using Genetic Algorithms,” in International Conference on Signal Processing Proceedings, Guilin, China, 2006, doi: 10.1109/ICOSP.2006.346113.
P. Khosla and R. Volpe, “Superquadric Artificial Potentials for Obstacle Avoidance and Approach,” in IEEE International Conference on Robotics and Automation, Philadelphia, PA, USA, vol. 3, 1988, pp. 1778–1784.
N. H. Sleumer and N. Tschichold-Gürman, “Exact Cell Decomposition of Arrangements used for Path Planning in Robotics,” Technical Report / ETH Zurich, Department of Computer Science, vol. 329, 1999, doi: https://doi.org/10.3929/ethz-a-006653440.
Z. Chungang and X. Yugeng, “Robot path planning in globally unknown environments based on rolling windows,” Science in China Series E: Technological Sciences, vol. 44, no. 2, pp. 131–139, 2001.
C. W. Warren, “Fast Path Planning Using Modified A* Method,” in Proceedings IEEE International Conference on Robotics and Automation, vol. 2, 1993, pp. 662–667.
H. Hung et al., “A Shortest Smooth-path Motion Planning for a Mobile Robot with Nonholonomic Constraints,” 2021 Int. Conf. Syst. Sci. Eng. (ICSSE), Ho Chi Minh City, Vietnam, 2021, pp. 145-150, doi: 10.1109/ICSSE52999.2021.9538414.
S. Mirjalili, “Ant Colony Optimization,” Studies in Computational Intelligence, vol. 780, pp. 33–42, 2019.
D. Wang, D. Tan, and L. Liu, “Particle swarm optimization algorithm: an overview,” Soft Computing, vol. 22, no. 2, pp. 387–408, 2018.
R. Sarkar, D. Barman, and N. Chowdhury, “Domain knowledge based genetic algorithms for mobile robot path planning having single and multiple targets,” Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 7, pp. 4269-4283, 2022.
B. K. Patle, D. R. K. Parhi, A. Jagadeesh, and S. K. Kashyap, “Matrix-Binary Codes based Genetic Algorithm for path planning of mobile robot,” Computers and Electrical Engineering, vol. 67, pp. 708–728, 2018.
C. Lamini, S. Benhlima, and A. Elbekri, “Genetic algorithm based approach for autonomous mobile robot path planning,” Procedia Computer Science, vol. 127, pp. 180–189, 2018.
U. O. Rosas, O. Montiel, and R. Sepúlveda, “Mobile robot path planning using membrane evolutionary artificial potential fiel,” Appl. Soft Comput. J., vol. 77, pp. 236-251, 2019.
Y. Cen, L. Wang, and H. Zhang, “Real-time obstacle avoidance strategy for mobile robot based on improved coordinating potential field with genetic algorithm,” in Proceedings of the IEEE International Conference on Control Applications, Singapore, 2007, pp. 415–419.
M. Khatib, H. Jaouni, R. Chatila, and J. P. Laumond, “Dynamic path modification for car-like nonholonomic mobile robots,” in Proceedings - IEEE International Conference on Robotics and Automation, Albuquerque, NM, USA, 1997, pp. 2920-2925.
J. Baker, “Adaptive selection methods for genetic algorithms,” in Proceedings Of The First International Conference On Genetic Algorithms And Their Applications, 1985, pp. 58–69.
K. Hamilton, “Principles of Robot Motion,” The Canadian nurse, vol. 53. pp. 1079–1083, 2005.
D. Zivojevic and J. Velagic, “Path planning for mobile robot using dubins-curve based RRT algorithm with differential constraints,” in Proceedings Elmar - International Symposium Electronics in Marine, 2019, pp. 139–142.
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