为四旋翼设计动态环境下的安全轨迹规划,95%成功率超现有方法
Safe Interval Motion Planning for Quadrotors in Dynamic Environments
- 分两阶段:先图搜索找安全区间,再用梯度优化生成轨迹
- 在不同障碍密度环境中成功率超95%,优于现有方法
- 适合需实时避障的无人机应用,如复杂城市飞行
动态环境中四旋翼的轨迹生成面临显著挑战,主要源于时空域的非凸性。现有方法多假设静态环境或难以实现实时最优解。本文提出一种高效的动态环境安全区间运动规划框架。安全区间指某配置在特定时间窗口内安全。方法采用两阶段流程:前端图搜索构建动态连通可视图,后端基于梯度优化。通过在安全区间与时间走廊中引入低阶动力学约束,确保解的完备性与最优性。为避免局部极小,提出均匀时间可视变形(UTVD)以完整评估时空拓扑等价性。轨迹用B-Spline曲线表示,结合梯度优化实现对静态与动态障碍物的规避。仿真与真实实验表明,该方法在不同障碍密度环境下成功率超过95%,性能优于其他方法,具备在高度动态环境中实际部署的潜力。
原文摘要 · Abstract (English)
Trajectory generation in dynamic environments presents a significant challenge for quadrotors, particularly due to the non-convexity in the spatial-temporal domain. Many existing methods either assume simplified static environments or struggle to produce optimal solutions in real-time. In this work, we propose an efficient safe interval motion planning framework for navigation in dynamic environments. A safe interval refers to a time window during which a specific configuration is safe. Our approach addresses trajectory generation through a two-stage process: a front-end graph search step followed by a back-end gradient-based optimization. We ensure completeness and optimality by constructing a dynamic connected visibility graph and incorporating low-order dynamic bounds within safe intervals and temporal corridors. To avoid local minima, we propose a Uniform Temporal Visibility Deformation (UTVD) for the complete evaluation of spatial-temporal topological equivalence. We represent trajectories with B-Spline curves and apply gradient-based optimization to navigate around static and moving obstacles within spatial-temporal corridors. Through simulation and real-world experiments, we show that our method can achieve a success rate of over 95% in environments with different density levels, exceeding the performance of other approaches, demonstrating its potential for practical deployment in highly dynamic environments.
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