主动利用环境接触简化机器人运动规划
Motion Generation With Environmental Constraints
- 通过有意接触环境降低规划维度和计算复杂度
- 在真实场景中验证了规划效率与执行鲁棒性提升
- 适合需要高适应性的复杂环境机器人任务
机器人运动规划在高维空间和不确定环境中面临挑战，通常需满足无碰撞要求。本文提出环境约束利用（ECE）新方法，通过有意识地与环境接触，降低规划维度和计算复杂度。将ECE融入基于RRT的规划算法后，可引导探索聚焦任务相关区域，并利用接触信息减少不确定性，从而提升执行鲁棒性。在真实世界应用中验证了该方法的实际效益。本工作整合并扩展了先前研究，展示了ECE如何在复杂环境中简化规划、增强适应性与性能。
原文摘要 · Abstract (English)
Robot motion planning faces challenges in high-dimensional spaces and uncertain environments, often constrained by the need for collision-free motions. We advocate an alternative approach, Environmental Constraint Exploitation (ECE), where deliberate contact with the environment simplifies planning by reducing dimensionality and computational complexity. By integrating ECE into motion planning algorithms, we bias exploration to task-relevant regions and leverage contact for uncertainty reduction to improve robustness during execution. We evaluate ECE benefits with RRT-based planners and demonstrate their practical benefits in a real-world application. This work consolidates and extends prior research, showcasing how ECE simplifies motion planning while enhancing adaptability and performance in complex environments.
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