双向RRT算法解决混合系统运动规划，提升计算效率与轨迹连续性。
HyRRT-Connect: Bidirectional Motion Planning for Hybrid Dynamical Systems
- 双向探索混合时间空间，正向与反向同步推进直至重叠。
- 通过重构反向路径消除轨迹间断，确保满足混合动力学约束。
- 适用于需要精确动态建模的机器人系统，如跳跃球和步行机器人。
本文提出一种双向快速探索随机树（HyRRT-Connect）算法，用于求解混合系统的运动规划问题。该算法在混合时间空间中同时进行正向与反向传播，直至两者结果出现重叠。随后，通过反转并拼接定义在混合时间域上的函数，构建满足给定混合动力学的运动规划。为解决因允许正向与反向部分轨迹间存在距离而引起的流线不连续问题，采用从正向轨迹终点出发的前向混合时间仿真重构反向部分轨迹，有效消除不连续性。该算法应用于受驱动弹跳球系统与步行机器人实例，验证了其在计算性能上的改进。
原文摘要 · Abstract (English)
This paper proposes a bidirectional rapidly-exploring random trees (RRT) algorithm to solve the motion planning problem for hybrid systems. The proposed algorithm, called HyRRT-Connect, propagates in both forward and backward directions in hybrid time until an overlap between the forward and backward propagation results is detected. Then, HyRRT-Connect constructs a motion plan through the reversal and concatenation of functions defined on hybrid time domains, ensuring that the motion plan satisfies the given hybrid dynamics. To address the potential discontinuity along the flow caused by tolerating some distance between the forward and backward partial motion plans, we reconstruct the backward partial motion plan by a forward-in-hybrid-time simulation from the final state of the forward partial motion plan. effectively eliminating the discontinuity. The proposed algorithm is applied to an actuated bouncing ball system and a walking robot example to highlight its computational improvement.
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