arXiv:2603.00759cs.RO2026-03

在线生成动态环境下的无碰撞轨迹,支持实时调整与安全保证。

Online Generation of Collision-Free Trajectories in Dynamic Environments

  • 将任意路径转为满足加速度和急动度限制的分段五次/四次样条
  • 在动态障碍物速度受限条件下,提供有限时间内的停止安全保证
  • 适用于机器人实时避障,尤其适合频繁改变目标的场景

本文提出一种在线方法,可将任意几何路径(如由RRT、PRM或ARA*等规划器生成)转换为满足运动学约束、急动度受限的可行轨迹。该方法生成一系列五次/四次样条,可在用户指定控制频率下离散并流式传输至底层控制器。该方法支持在任意时刻重新触发,从当前机器人状态生成到目标状态或序列的新轨迹,具备实时适应环境变化的能力。在障碍物速度有界假设下,该方法在有限时间内提供条件停止安全性保障,同时允许路径存在可控的几何偏差。显式考虑了加速度与急动度等运动学约束。通过对比仿真验证,该方法在平滑性、计算时间与实时性能方面表现优异,尤其在目标状态变更频率高达1 kHz时优势明显。真实机器人实验表明其适用于包含人类等动态障碍的实际场景。

原文摘要 · Abstract (English)

In this paper, we present an online method for converting an arbitrary geometric path, represented by a sequence of states, and generated by any planner (e.g., sampling-based planners such as RRT or PRM, search-based planners such as ARA*, etc.), into a kinematically feasible, jerk-limited trajectory. The method generates a sequence of quintic/quartic splines that can be discretized at a user-specified control rate and streamed to a low-level robot controller. Our approach enables real-time adaptation to environmental changes and can be re-invoked at any instant to generate a new trajectory from the robot's current state to a desired target state or sequence of states. Under a bounded-obstacle-velocity assumption, the method provides conditional stopping-safety guarantees over a finite time interval in dynamic environments, while allowing bounded geometric deviation from the original path. Kinematic constraints, including jerk limits, are explicitly considered. We validate the approach in a comparative simulation study against a competing method, demonstrating favorable behavior w.r.t. smoothness, computational time, and real-time performance, particularly with frequent target-state changes (up to 1 [kHz]). Real-robot experiments demonstrate applicability in real-world scenarios, including scenarios with a human as an obstacle.

轨迹生成动态避障实时控制

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