基于RRT*的最优路径规划，满足时序逻辑约束。
RRT* Based Optimal Trajectory Generation with Linear Temporal Logic Specifications under Kinodynamic Constraints
- 结合时序逻辑鲁棒性与运动约束，递归计算路径成本
- 生成兼具最优性与可执行性的轨迹，支持复杂环境
- 适合需形式化逻辑保证的机器人路径规划场景
本文提出一种基于RRT*的新型策略，用于生成满足时序逻辑（LTL）规范的运动学动力学可行路径。该方法将线性时序逻辑（LTL）的鲁棒性度量与系统运动约束相结合，确保生成的轨迹既最优又可执行。我们设计了一种代价函数，递归计算时序逻辑规范的鲁棒性，并对时间和控制努力进行惩罚，平衡路径可行性与逻辑正确性。通过在复杂环境中的仿真与真实实验验证，结果表明该方法能有效生成鲁棒且实用的运动规划方案。本工作推动了运动规划算法在更复杂现实场景中的应用。
原文摘要 · Abstract (English)
In this paper, we present a novel RRT*-based strategy for generating kinodynamically feasible paths that satisfy temporal logic specifications. Our approach integrates a robustness metric for Linear Temporal Logics (LTL) with the system's motion constraints, ensuring that the resulting trajectories are both optimal and executable. We introduce a cost function that recursively computes the robustness of temporal logic specifications while penalizing time and control effort, striking a balance between path feasibility and logical correctness. We validate our approach with simulations and real-world experiments in complex environments, demonstrating its effectiveness in producing robust and practical motion plans. This work represents a significant step towards expanding the applicability of motion planning algorithms to more complex, real-world scenarios.
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