Xiaoyang Hu, Sairu Liu, and Jie Zhao


  1. [1] Y. Cong, C. Chen, B. Yang, F. Liang, R. Ma, and F. Zhang,CAOM: Change-aware online 3D mapping with heterogeneousmulti-beam and push-broom LiDAR point clouds, ISPRSJournal of Photogrammetry and Remote Sensing, 195, 2023,204–219. DOI:
  2. [2] S. Zeng and K. Liu, Research status and developmenttrend of UAV path planning algorithms, Journal ofPhysics: Conference Series, 2283(1), 2022, 012004.DOI:
  3. [3] Y.J. Cui, Y.C. Wang, Z. He, D. Cao, L. Ma, and K. Li,Global path planning of kiwifruit harvesting robot based onimproved RRT algorithm, Transactions of the Chinese Societyof Agricultural Machinery, 53(6), 2022, 151–158.
  4. [4] D. Chen and X. Wu, Research on improved laser SLAMalgorithm for mobile robots, Computer Engineering andApplication, 58(4), 2022, 163–168.
  5. [5] S. Wen, Z. Wen, D. Zhang, H. Zhang, and T. Wang,A multi-robot path-planning algorithm for autonomousnavigation using meta-reinforcement learning based on transferlearning, Applied Soft Computing, 110(4), 2021, 107605.DOI:
  6. [6] B.G. Sarmina and G. Khachaturov, QPA: Designof a searching and path planning algorithm forintelligent agents in two dimensions, Proc. IEEE19th International Conf. on Cognitive Informatics &Cognitive Computing (ICCICC), Beijing, 2020, 202–209.DOI:
  7. [7] M. Nazarahari, E. Khanmirza, and S. Doostie, Multi-objective multi-robot path planning in continuousenvironment using an enhanced genetic algorithm,9Expert Systems with Applications, 115, 2019, 106–120.DOI:
  8. [8] U. Orozco-Rosas, O. Montiel, and R. Sep´ulveda, Mobilerobot path planning using membrane evolutionary artificialpotential field, Applied Soft Computing, 77, 2019, 236–251.DOI:
  9. [9] G.S. Zhang, J.J. Wei, J.Q. Liu, C.B. Wang, T. Wang, Z.X. Mao,C.K. Luo, Path planning strategy for mobile robot navigation,Mechanical & Electrical Engineering Technology, 50(04), 2021,14–24.
  10. [10] Y. Song, Q.L. Li, and Y.F. Kang, Conjugate unscentedfastSLAM for autonomous mobile robots in large-scaleenvironments, Cognitive Computation, 6(3), 2014, 496–509.DOI:
  11. [11] G. Grisetti, C. Stachniss, and W. Burgard, improvedtechniques for grid mapping with rao-blackwellized particlefilters, IEEE Transactions on Robotics, 23(1), 2007, 34–46.DOI:
  12. [12] R. K¨ummerle, G. Grisetti, H. Strasdat, K. Konolige,and W. Burgard, G2o: A general framework forgraph optimization, Proc. IEEE International Conf. onRobotics and Automation, Shanghai, 2011, 3607–3613.DOI:
  13. [13] R. Zhang, J. Wu, and Y. Wang, Stability analysis of a novelmobile spray-painting robot for touch-up painting in vehiclerepair plant, Journal of Mechanical Science and Technology,36(5), 2022, 2571–2584. DOI:
  14. [14] J. Wu, X. Wang, B. Zhang, and T. Huang, Multi-objective optimal design of a novel 6-DOF spray-painting robot, Robotica, 39(12), 2021, 2268–2282.DOI:
  15. [15] J. Wu, B. Zhang, L. Wang, and G. Yu, An iterative learningmethod for realizing accurate dynamic feedforward control of anindustrial hybrid robot, Science China Technological Sciences,64(6), 2021, 1177–1188. DOI:
  16. [16] R. Edlinger and A. N¨uchter, Terrain prediction witha low-cost LIDAR sensor for mobile robots, ISPRS -International Archives of the Photogrammetry, RemoteSensing and Spatial Information Sciences, 48, 2022, 81–86.DOI:
  17. [17] Y. Wang and X. Wang, Research on SLAM roadsign observation based on particle filter, ComputationalIntelligence and Neuroscience, 2022, 2022, 4478978.DOI:
  18. [18] L. Chen, A. Yang, H. Hu, and W. Naeem, RBPF-MSIS:Toward Rao-Blackwellized particle filter SLAM for autonomousunderwater vehicle with slow mechanical scanning imagingsonar, IEEE Systems Journal, 14(3), 2020, 3301–3312.DOI:
  19. [19] X.J. Li, D. Wang, and D.T. Li, Design of indoor mobilerobot based on ROS and SLAM, Digital Design, 1(11), 2022,19–23.
  20. [20] A.H. Tan, A. Al-Shanoon, H. Lang, and Y. Wang, Mobilerobot docking with obstacle avoidance and visual servoing,International Journal of Robotics and Automation, 38(2), 2023,97–108. DOI:
  21. [21] X.Y. Yang and H. Yan, Rapidly-exploring random treesalgorithm with guided extension, Modern Computer,36, 2020, 58–63. DOI:
  22. [22] G.C. Liu, P.C. Shi, Ni, Xuan, T.N. Liang, An improvedbidirectional rapidly expanding random tree algorithmfor path planning of unmanned vehicles, Journal ofAnhui Polytechnic University, 36(04), 2021, 41–50.DOI:
  23. [23] H.F. Wang, Y.Y. Cui, M.F. Li, and G.Y. Li, Path planningalgorithm for mobile robot based on improved RRT FN,Journal of Northeastern University(Natural Science), 43(9),2022, 1217–1224+1249.
  24. [24] L.J. Chen, W.L. Zhao, and J.J. Lou, RRT-based dynamicavoidance trajectory planning algorithm, Modern Computer,22, 2021, 72–76+80.
  25. [25] L. Hong, C. Song, P. Yang, and W. Cui, Two-layer path plannerfor AUVs based on the improved AAF-RRT algorithm. Journalof Marine Science and Application, 21(1), 2022, 102–115.DOI:
  26. [26] Y. Li, W. Liu, and X. Lei, Charging trajectory planningand motion control for indoor mobile robots, InternationalJournal of Robotics and Automation, 37(6), 2022, 520–528.DOI:

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