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All issues Volume 41 / No 3 (June 2023) JNWPU, 41 3 (2023) 500-509 References
Open Access
Issue
JNWPU
Volume 41, Number 3, June 2023
Page(s) 500 - 509
DOI https://doi.org/10.1051/jnwpu/20234130500
Published online 01 August 2023
  1. FANG H C, ONG S K, NEE A Y C. Robot path planning optimization for welding complex joints[J]. The International Journal of Advanced Manufacturing Technology, 2017, 90(9): 3829–3839 [CrossRef] [Google Scholar]
  2. WANG W R, ZHU M C, WANG X M, et al. An improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators[J]. International Journal of Advanced Robotic Systems, 2018, 15(5): 1–13 [Google Scholar]
  3. LUO Q, WANG H, ZHENG Y, et al. Research on path planning of mobile robot based on improved ant colony algorithm[J]. Neural Computing and Applications, 2020, 32(6): 1555–1566 [Article] [CrossRef] [Google Scholar]
  4. NAZARAHARI M, KHANMIZRA E, DOOSTIE S. Multi-objective multi-robot path planning in continuous environment using an enhanced genetic algorithm[J]. Expert Systems with Applications, 2019, 115106–120 [Article] [CrossRef] [Google Scholar]
  5. WANG S K, ZHU L. Motion planning method for obstacle avoidance of 6-dof manipulator based on improved A* algorithm[J]. Journal of Donghua University, 2015, 32(1): 79–85 [Google Scholar]
  6. AKRAM M, HABIB A, ALCANTUD J C R. An optimization study based on Dijkstra algorithm for a network with trapezoidal picture fuzzy numbers[J]. Neural Computing and Applications, 2021, 33(4): 1329–1342 [Article] [CrossRef] [Google Scholar]
  7. WANG X, LUO X, HAN B, et al. Collision-free path planning method for robots based on an improved rapidly-exploring random tree algorithm[J]. Applied Sciences, 2020, 10(4): 1381[Article] [CrossRef] [Google Scholar]
  8. WANG J, LI B, MENG Q H. Kinematic constrained bi-directional RRT with efficient branch pruning for robot path planning[J]. Expert Systems with Applications, 2020, 170114541–114547 [Google Scholar]
  9. TAHIR Z, QURESHI A H, AYAZ Y, et al. Potentially guided bidirectionalized RRT* for fast optimal path planning in cluttered environments[J]. Robotics and Autonomous Systems, 2018, 10813–27 [Article] [CrossRef] [Google Scholar]
  10. CHEN Manyi, ZHANG Qiao, ZHANG Gong, et al. Research on obstacle avoidance path planning of manipulator in multiple obstacles environmen[J]. Computer Integrated Manufacturing Systems, 2021, 27(4): 990–998 [Article] (in Chinese) [Google Scholar]
  11. KARAMAN S, FRAZZOLI E. Sampling-based algorithms for optimal motion planning[J]. International Journal of Robotics Research, 2011, 30(7): 846–894 [Article] [Google Scholar]
  12. ZHANG Weimin, FU Shixiong. Mobile robot path planning based on improved RRT* algorithm[J]. Journal Huazhong University of Science and Technology, 2021, 49(1): 31–36 [Article] (in Chinese) [Google Scholar]
  13. ZHANG Libin, LIN Houkai, TAN Dapeng. Manipulator path planning based on grid space-based adaptive goal bias rapidly exploring random tree star[J]. Computer Integrated Manufacturing Systems, 2022, 28(6): 1638–1649 [Article] (in Chinese) [Google Scholar]
  14. LI Wenguang, SUN Shiyu, LI Jianzeng, et al. UAV dynamic path planning algorithm based on segmentated optimization RRT[J]. Systems Engineering and Electronics, 2018, 40(8): 123–130 [Article] (in Chinese) [Google Scholar]
  15. KANG J G, LIM D W, CHOI Y S, et al. Improved RRT-connect algorithm based on triangular inequality for robot path planning[J]. Sensors, 2021, 21(2): 333 [NASA ADS] [CrossRef] [Google Scholar]
  16. WANG X Y, LI X J, GUAN Y, et al. Bidirectional potential guided RRT* for motion planning[J]. IEEE Access, 201999): 1 [Google Scholar]
  17. KALISIAK M, VAN DE PANNE M. RRT-blossom: RRT with a local flood-fill behavior[C]//Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006: 1237–1242 [Google Scholar]
  18. ZHU Zhanxia, JING Sa, ZHONG Jianfei, et al. Obstacle avoidance path planning of space redundant manipulator based on a collision detection algorithm[J]. Journal of Northwestern Polytechnical University, 2020, 38(1): 183–190 [Article] (in Chinese) [CrossRef] [EDP Sciences] [Google Scholar]
  19. MA Yuhao, LIANG Yanbing. An obstacle avoidance algorithm for manipulators based on six-order polynomial trajectory planning[J]. Journal of Northwestern Polytechnical University, 2020, 38(2): 392–400 [Article] (in Chinese) [CrossRef] [EDP Sciences] [Google Scholar]
  20. LI Yang, XU Da. Cooperative path planning of dual-arm robot based on attractive force self-dadptive step size RRT[J]. Robot, 2020, 42(5): 606–616 [Article] (in Chinese) [Google Scholar]
  21. DAI Wei, LI Chuangye, YANG Chunyu, et al. Manipulator path planning using fusion algorithm of low difference sequence and rapidly exploring random tree[J]. Contrd Theory & Applications, 2022, 39(1): 130–144 [Article] (in Chinese) [Google Scholar]

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