TL;DR
This paper proposes IBPAS-RRT*, an adaptive bidirectional RRT* algorithm with joint-space potential field guidance that incorporates obstacle and goal information into joint-space tree expansion, thereby avoiding repeated inverse kinematics calls during planning.
The experimental results demonstrate that the proposed Field-guided RRT achieves a better balance among path efficiency, planning time, obstacle-clearance maintenance, and trajectory execution capability compared with conventional RRT-based methods.
A hybrid path planning algorithm that integrates an improved Bidirectional Rapidly-exploring Random Tree (BI-RRT) for global guidance with an enhanced Dynamic Window Approach (DWA) for local execution that improves search efficiency and maintains 100% success rate across tested environments.
Path planning is a critical component of autonomous driving, particularly in complex unstructured environments characterized by the absence of clearly defined drivable corridors and the presence of irregular obstacles. A widely adopted two-stage framework under such conditions involves generating an initial path follow...
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