Online Search-Based Collision-Inclusive Motion Planning and Control for Impact-Resilient Mobile Robots
نویسندگان
چکیده
This article focuses on the emerging paradigm shift of collision-inclusive motion planning and control for impact-resilient mobile robots, develops a unified hierarchical framework navigation in unknown partially observable cluttered spaces. At lower level, we develop deformation recovery trajectory replanning strategy that handles collisions may occur at run time, locally. The low-level system actively detects (via embedded Hall effect sensors robot built in-house), enables to recover from them, locally adjusts postimpact trajectory. Then, higher propose search-based algorithm determine how best utilize potential improve certain metrics, such as energy computational time. Our method builds upon A* with jump points. We generate novel heuristic function, collision checking adjustment technique, thus making converge faster reach goal by exploiting utilizing possible collisions. overall generated combining global local strategy, well individual components this framework, are tested extensively both simulation experimentally. An ablation study draws links related state-of-the-art collision-avoidance planners (for framework), sampling-based level). Results demonstrate our method's efficacy environments isolated obstacles class robots operating 2-D.
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ژورنال
عنوان ژورنال: IEEE Transactions on Robotics
سال: 2023
ISSN: ['1552-3098', '1941-0468', '1546-1904']
DOI: https://doi.org/10.1109/tro.2022.3211131