A Multimodal Optimal Control Approach for Fast Obstacle Avoidance of UAVs

The obstacle avoidance and control of uncrewed aerial vehicles (UAVs) in cluttered environments is a significant challenge. Existing UAV planning and obstacle avoidance systems can only fly at moderate speeds or at high speeds over empty or sparse fields. In this article, we propose a multimodal optimal control method for obstacle avoidance of UAVs. Firstly, we propose a novel multiple topological path search method that generates multiple distinct paths. Then, a gradient-based parallel trajectory generation method is proposed, and the best trajectory is selected. With these innovations, the system has an excellent real-time performance with only milliseconds of latency in each iteration. The multimodal trajectories enable the control commands closer to the global optimum in both temporal and spatial domains. Finally, extensive validations demonstrate the effectiveness of our proposed system.