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Unmanned surface vessels (USVs) are widely used in ocean exploration andenvironmental protection fields. To ensure that USV can successfully performits mission, trajectory planning and motion tracking are the two most criticaltechnologies. In this paper, we propose a novel trajectory generation andtracking method for USV based on optimization theory. Specifically, the USVdynamic model is described with differential flatness, so that the trajectorycan be generated by dynamic RRT* in a linear invariant system expression formunder the objective of optimal boundary value. To reduce the sample number andimprove efficiency, we adjust the trajectory through local optimization. Thedynamic constraints are considered in the optimization process so that thegenerated trajectory conforms to the kinematic characteristics of theunder-actuated hull, and makes it easier to be tracked. Finally, motiontracking is added with model predictive control under a sequential quadraticprogramming problem. Experimental results show the planned trajectory is morein line with the kinematic characteristics of USV, and the tracking accuracyremains a higher level.

Efficient Trajectory Planning and Control for USV with Vessel Dynamics and Differential Flatness