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Bounded-DWA: An Efficient Local Planner for Ackermann-driven Vehicles on Sandy Terrain

  • Ke Gong
  • , Zhiyuan Xu
  • , Xinyu Zhang*
  • *此作品的通讯作者
  • East China Normal University
  • Midea Group

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

We present a new dynamic window approach (DWA) for mobile vehicles equipped with Ackermann steering geometry that adheres to Ackermann kinematic constraints. By integrating these constraints with the sampling window in DWA, we can further reduce and bound the sampling range and enhance the efficiency of the DWA when a mobile vehicle moves on sandy terrain. Furthermore, we improve the evaluation function to optimize the selected trajectory. Our algorithm is successfully validated in ROS and Gazebo through comparison with other existing local planner such as the original DWA and TEB algorithms. We also successfully deploy our Bounded-DWA in the application of coverage path planning, where tree-planting robots traverse on sandy terrain.

源语言英语
主期刊名Proceedings of the 2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023
出版商Institute of Electrical and Electronics Engineers Inc.
632-637
页数6
ISBN(电子版)9798350327182
DOI
出版状态已出版 - 2023
活动2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023 - Datong, 中国
期限: 17 7月 202320 7月 2023

出版系列

姓名Proceedings of the 2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

会议

会议2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023
国家/地区中国
Datong
时期17/07/2320/07/23

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