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.
As manipulators are increasingly used in intelligent manufacturing, agricultural harvesting, and medical applications, efficient motion planning in complex environments has become essential. However, high-degree-of-freedom planning in continuous joint space is often limited by high search complexity, inefficient explor...
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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