Xianwen Yu, Yaqi Liu, and Luchao Kui
[1] X. Cao, X. Zou, C. Jia, M. Chen, and Z. Zeng, RRT-basedpath planning for an intelligent litchi-picking manipulator,Computers and Electronics in Agriculture, 156, 2019, 105–118. [2] S. Aggarwal and N. Kumar, Path planning techniques forunmanned aerial vehicles: A review, solutions, and challenges,Computer Communications, 149, 2020, 270–299. [3] X. Huang, Q. Cao, and X. Zhu, Mixed path planning formulti-robots in structured hospital environment, The Journalof Engineering, 2019(14), 2019, 512–516. [4] D. Lyu, Z. Chen, Z. Cai, and S. Piao, Robot path planningby leveraging the graph-encoded Floyd algorithm, FutureGeneration Computer Systems, 122, 2021 204–208. [5] J. Ji, A. Khajepour, W. W. Melek, and Y. Huang,Path planning and tracking for vehicle collision avoidancebased on model predictive control with multiconstraints,IEEE Transactions on Vehicular Technology, 66(2), 2017,952–964. [6] T. Huang, P. Yang, K. Yang, and Y. Zhu, Navigationof mobilerobot in unknown environment based on TSneuro-fuzzysystem, International Journal of Robotics andAutomation, 30(4), 2015, 384396. [7] L. Wang and C. Luo, A hybrid genetic Tabu search algorithmfor mobile robot to solve AS/RS path planning, InternationalJournal of Robotics and Automation, 33(2), 2018, 161–168. [8] N. Chang, P. Cheng, C. Feng, L. Wang, and Y. Li, Researchprogress of off-road path optimisation algorithm for equipment,Optics and Precision Engineering, 31(5), 2023, 776–792. [9] A.K. Guruji, H. Agarwal H and D. K. Parsediya, Time-efficientA algorithm for robot path planning, Procedia Technology,23, 2016, 144–149. [10] X. Mao, Z. He, Y. Wang, H. Zhang, H. Zhong J. Yi, Z. Tao,and N. Chen, Review of research and applications on pathplanning technology for power inspection robots, Control andDecision, 38(11) 2023, 3009–3024. [11] Y. Lin and S. Saripalli, Sampling-based path planning forUAV collision avoidance, IEEE Transactions on IntelligentTransportation Systems, 18(11), 2017, 3179–3192. [12] Y. Feng, Z. Zhou, Y. Shen, and L. Wang, Obstacle avoidancepath planning based on improved RRT algorithm, ChineseJournal of Engineering Design, 30(6), 2023, 707–716. [13] W. Xu, Y. Yang, L. Yu, and L. Zhu, A global path planningalgorithm based on improved RRT, Control and Decision,37(4), 2022, 829–838. [14] Z. Wu, Y. Chen, J. Liang, B. He, and Y. Wang, ST-FMT:A fast optimal global motion planning for mobile robot, IEEETransactions on Industrial Electronics, 69(4), 2022, 3854–3864. [15] L. Feng, H. Liang, M. Du, and B. Yu, Guiding-area RRTpath planning algorithm based on A for intelligent vehicle,Computer Systems & Applications, 26(8), 2017, 127–133. [16] B. Han, T. Qu, X. Tong, J. Jiang, S. Zliatanova, H. Wang,and C. Cheng, Grid-optimised UAV indoor path planningalgorithms in a complex environment, International Journalof Applied Earth Observation and Geoinformation, 111, 2022,102857. [17] M. Jia, B. Feng, P. Wu, K. Zhang, and S. Sang, A path planningfor cultural tourism service robot combining improved Aalgorithm and improved dynamic window approach, Journalof Graphics, 45(3), 2024, 505–515. [18] S. Duan, Q. Wang, X. Han, and R. Gui, Improved A algorithmfor safety insured optimal path with smoothed corner turns,Journal of Mechanical Engineering, 56(18), 2020, 205–215. [19] J. Li, Q. Li, X. Zhang, M. H. Zin, and Y. Cai, Improvedbidirectional A quadratic path planning algorithm formobile robots, Journal of System Simulation, 37(2), 2025,498–507. [20] H. Min, X. Xiong, P. Wang, and Y. Yu, Autonomous drivingpath planning algorithm based on improved A algorithmin unstructured environment, Proceedings of the Institutionof Mechanical Engineers, Part-D: Journal of AutomobileEngineering, 235(2–3), 2021, 513–526. [21] M. Davoodi, F. Panahi, A. Mohades, and S. N. Hashemi, Clearand smooth path planning, Applied Soft Computing, 32, 2015,568–579. [22] X. Zhou, Z. Yi, Y. Liu, K. Huang, and H. Huang, Survey onpath and view planning for UAVs, Virtual Reality & IntelligentHardware, 2(1), 2020, 56–69. [23] X. Zhong, J. Tian, H. Hu, and X. Peng, Hybrid path planningbased on safe A algorithm and adaptive window approach formobile robot in large-scale dynamic environment, Journal ofIntelligent & Robotic Systems, 99(1), 2020, 65–77. [24] S. Bayili and F. Polat, Limited-damage A: A path searchalgorithm that considers damage as a feasibility criterion,Knowledge-Based Systems, 24(4), 2011, 501–512. [25] Y. Liu, S. Guo, S. Tang, X. Zhang, and T. Li, Path planningbased on fusion of improved A and ROA-DWA for robot,Journal of Zhejiang University (Engineering Science), 58(2),2024, 360–369.27 [26] R. A. Saeed, D. R. Recupero, and P. Remagnino, A boundarynode method for path planning of mobile robots, Robotics andAutonomous Systems, 123, 2020, 103320. [27] T. Zhang, Z. Chen, Y. Li, P. Fang, N. Lu, and H. Gong,Research on robot obstacle avoidance based on improved Aalgorithm and dynamic window method, Instrument Techniqueand Sensor, 2023(4), 2023, 102–106. [28] Q. Song, S. Li, J. Yang, Q. Bai, J. Hu, X. Zhang, and A. Zhang,Intelligent optimisation algorithm-based path planning for amobile robot, Computational Intelligence and Neuroscience,2021, 2021, 1–17. [29] J. Yao, Path planning algorithm of indoor mobile robot basedon ROS system, in Proceeding of the International Conferenceon Image Processing and Computer Applications, Changchun,2023, 523–529. [30] X. Wang, J. Lu, F. Ke, X. Wang, and W. Wang, Researchon AGV task path planning based on improved A algorithm,Virtual Reality & Intelligent Hardware, 5(3), 2023, 249–265. [31] S. Koenig and M. Likhachev, Dlite, in Proceeding of the 18thNational Conference on Artificial Intelligence and FourteenthConference on Innovative Applications of Artificial Intelligence,Edmonton, AB, 2022, 476–483. [32] X. Li, Y. Lu, X. Zhao, X. Deng, and Z. Xie, Path planning forintelligent vehicles based on improved Dlite, The Journal ofSupercomputing, 80(1), 2024, 1294–1330.
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