Cooperative trajectory planning algorithm of USV-UAV with hull dynamic constraints

TL;DR

This paper presents a cooperative trajectory planning system for USV-UAV that integrates real-time obstacle mapping, hull dynamic constraints, and energy-efficient control to enable safe, smooth, and locally optimal navigation in complex environments.

Contribution

It introduces a novel cooperative planning algorithm combining UAV-based mapping, hull dynamic constraints, and NMPC control for USV trajectory optimization.

Findings

Trajectory is locally optimal and accurately tracked.

System effectively navigates complex obstacle environments.

Energy consumption is minimized during USV motion.

Abstract

Efficient trajectory generation in complex dynamic environments remains an open problem in the unmanned surface vehicle (USV). The perception of the USV is usually interfered with by the swing of the hull and the ambient weather, making it challenging to plan the optimal USV trajectories. In this paper, a cooperative trajectory planning algorithm for the coupled USV-UAV system is proposed to ensure that USV can execute a safe and smooth path in the process of autonomous advance in multi-obstacle maps. Specifically, the unmanned aerial vehicle (UAV) plays the role of a flight sensor, providing real-time global map and obstacle information with a lightweight semantic segmentation network and 3D projection transformation. And then, an initial obstacle avoidance trajectory is generated by a graph-based search method. Concerning the unique under-actuated kinematic characteristics of the USV, a numerical optimization method based on hull dynamic constraints is introduced to make the trajectory easier to be tracked for motion control. Finally, a motion control method based on NMPC with the lowest energy consumption constraint during execution is proposed. Experimental results verify the effectiveness of the whole system, and the generated trajectory is locally optimal for USV with considerable tracking accuracy.