Open Access
Volume 41, Number 3, June 2023
Page(s) 500 - 509
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]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.