Parameters related to dynamic obstacles.

With the rapid deployment of autonomous micro-UAVs in dynamic environments, path planning must ensure both safety and real-time performance under stringent onboard computational constraints. This paper proposes a dynamic path planning method based on the reciprocal velocity obstacles algorithm, enabling micro-UAVs to safely and efficiently accomplish flight tasks in complex environments. In three-dimensional space, we introduce the Velocity-Obstacle Spherical Crown (VOSC) model to delineate safe and feasible velocity boundaries, thereby ensuring reliable avoidance of moving obstacles. Within this velocity domain, a minimum-deflection-angle replanning strategy generates smooth and dynamically feasible trajectories. For multi-obstacle scenarios, we design a critical-curve-based avoidance scheme that allows the UAV to flexibly select feasible maneuvers along the curve, improving efficiency and robustness. Simulation results demonstrate that, compared with traditional methods, the proposed approach significantly reduces planning time while enhancing trajectory smoothness. Moreover, the algorithm runs online on micro-UAV hardware, highlighting its potential for warehouse navigation, low-altitude urban transport, and other real-time missions.

随着自主微型无人机（autonomous micro-UAVs）在动态环境中的快速部署，路径规划需在严苛的机载计算约束下，同时保障安全性与实时性。本文提出一种基于互逆速度障碍物算法的动态路径规划方法，可使微型无人机在复杂环境中安全高效地完成飞行任务。三维空间中，本文引入速度障碍物球冠（Velocity-Obstacle Spherical Crown，VOSC）模型来划定安全可行的速度边界，从而确保可靠规避移动障碍物。在该速度域内，最小偏转角重规划策略可生成平滑且满足动态可行性的航迹。针对多障碍物场景，本文设计了一种基于关键曲线的避障方案，允许无人机沿曲线灵活选择可行机动动作，提升了规划效率与鲁棒性。仿真结果表明，与传统方法相比，本文所提方法可显著缩短规划时长，同时提升航迹平滑性。此外，该算法可在微型无人机硬件上在线运行，展现出其在仓库导航、城市低空运输及其他实时任务中的应用潜力。