基于速度约束的无人机高速避障控制，100Hz实时运行
RVC-NMPC: Nonlinear Model Predictive Control with Reciprocal Velocity Constraints for Mutual Collision Avoidance in Agile UAV Flight
- 用可观察速度信息构建动态避碰约束，无需额外通信
- 100Hz高帧率运行，支持高达25m/s的敏捷飞行
- 适用于多机协同、高动态场景，实测31%飞行效率提升
本文提出一种基于非线性模型预测控制（NMPC）与时间依赖互惠速度约束（RVCs）的相互避障方法。该方法仅依赖对其他机器人可观测的信息，无需大量通信。通过高效计算RVCs，并直接将约束融入控制器级的NMPC问题，整个系统实现100 Hz的运行频率。结合被控无人飞行器（UAV）的非线性动力学建模，这一高处理速率使其适用于敏捷飞行。在最多10架无人机、速度达25 m/s的复杂仿真场景及真实实验中进行了评估，实验最大加速度达30 m/s²。与现有最优方法相比，在挑战性场景下飞行时间减少31%，且所有测试均保持无碰撞导航。
原文摘要 · Abstract (English)
This paper presents an approach to mutual collision avoidance based on Nonlinear Model Predictive Control (NMPC) with time-dependent Reciprocal Velocity Constraints (RVCs). Unlike most existing methods, the proposed approach relies solely on observable information about other robots, eliminating the need for excessive communication. The computationally efficient algorithm for computing RVCs, together with the direct integration of these constraints into the NMPC problem formulation at the controller level, allows the whole pipeline to run at 100 Hz. This high processing rate, combined with modeled nonlinear dynamics of the controlled Uncrewed Aerial Vehicles (UAVs), is a key feature that facilitates the use of the proposed approach for agile UAV flight. The proposed approach was evaluated through extensive simulations emulating real-world conditions in scenarios involving up to 10 UAVs and velocities of up to 25 m/s, and in real-world experiments with accelerations up to 30 m/s$^2$. Comparison with the state of the art shows 31% improvement in terms of flight time reduction in challenging scenarios, while maintaining a collision-free navigation in all trials.
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