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Target following with motion prediction for unmanned surface vehicle operating in cluttered environments

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Abstract

The capability of following a moving target in an environment with obstacles is required as a basic and necessary function for realizing an autonomous unmanned surface vehicle (USV). Many target following scenarios involve a follower and target vehicles that may have different maneuvering capabilities. Moreover, the follower vehicle may not have prior information about the intended motion of the target boat. This paper presents a trajectory planning and tracking approach for following a differentially constrained target vehicle operating in an obstacle field. The developed approach includes a novel algorithm for computing a desired pose and surge speed in the vicinity of the target boat, jointly defined as a motion goal, and tightly integrates it with trajectory planning and tracking components of the entire system. The trajectory planner generates a dynamically feasible, collision-free trajectory to allow the USV to safely reach the computed motion goal. Trajectory planning needs to be sufficiently fast and yet produce dynamically feasible and short trajectories due to the moving target. This required speeding up the planning by searching for trajectories through a hybrid, pose-position state space using a multi-resolution control action set. The search in the velocity space is decoupled from the search for a trajectory in the pose space. Therefore, the underlying trajectory tracking controller computes desired surge speed for each segment of the trajectory and ensures that the USV maintains it. We have carried out simulation as well as experimental studies to demonstrate the effectiveness of the developed approach.

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Acknowledgments

This work was supported by the U.S. Office of Naval Research under Grants N00014-10-1-0585 and N00014-12-1-0494, managed by R. Brizzolara. Opinions expressed in this paper are those of the authors and do not necessarily reflect opinions of the sponsors. In addition, we would like to thank Dr. David Akin for allowing us to perform experiments in the Neutral Buoyancy Research Facility (NBRF) at the University of Maryland.

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Švec, P., Thakur, A., Raboin, E. et al. Target following with motion prediction for unmanned surface vehicle operating in cluttered environments. Auton Robot 36, 383–405 (2014). https://doi.org/10.1007/s10514-013-9370-z

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