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

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 efficienc...

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Bibliographic Details
Published in2023 IEEE International Conference on Real-time Computing and Robotics (RCAR) pp. 632 - 637
Main Authors Gong, Ke, Xu, Zhiyuan, Zhang, Xinyu
Format Conference Proceeding
LanguageEnglish
Published IEEE 17.07.2023
Subjects
Heuristic algorithms
Kinematics
Navigation
Planning
Real-time systems
Shape
Trajectory
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DOI10.1109/RCAR58764.2023.10249383

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Summary: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.
DOI:10.1109/RCAR58764.2023.10249383