轻量级无人机规划器,实现最快飞行且计算负担最低。
Primitive-Planner: An Ultra Lightweight Quadrotor Planner with Time-optimal Primitives
- 构建时间最优的运动基元库,离线生成动力学可行轨迹
- 提出确定性耗时的快速碰撞检测方法,不依赖采样密度
- 基于用户需求选最优安全轨迹,适合实时嵌入式系统
四旋翼飞行器轨迹规划需兼顾轨迹质量与系统轻量化。本文提出一种超轻量级四旋翼规划器,采用时间最优基元。首先,构建新型运动基元库,离线生成时间最优且动力学可行的轨迹;其次,提出一种确定性耗时的快速碰撞检测方法,其计算时间独立于基元采样分辨率;最后,根据用户定义要求,在安全基元中选择最小代价轨迹执行。局部轨迹间的转换关系保证全局轨迹平滑性。该规划器极大减少在线计算开销,同时确保高质量轨迹。基准对比显示,本方法在计算负载最低的前提下实现最短飞行时间和距离。真实世界实验验证了方法的鲁棒性。
原文摘要 · Abstract (English)
It is a significant requirement for a quadrotor trajectory planner to simultaneously guarantee trajectory quality and system lightweight. Many researchers focus on this problem, but there's still a gap between their performance and our common wish. In this paper, we propose an ultra lightweight quadrotor planner with time-optimal primitives. Firstly, a novel motion primitive library is proposed to generate time-optimal and dynamical feasible trajectories offline. Secondly, we propose a fast collision checking method with a deterministic time consumption, independent of the sampling resolution of the primitives. Finally, we select the minimum cost trajectory to execute among the safe primitives based on user-defined requirements. The propsed transformation relation between the local trajectories ensures the smoothness of the global trajectory. The planner reduces unnecessary online computing power consumption as much as possible, while ensuring a high-quality trajectory. Benchmark comparisons show that our method can generate the shortest flight time and distance of trajectory with the lowest computation overload. Challenging real-world experiments validate the robustness of our method.
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