Karl von Ellenrieder

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We present a model-predictive trajectory planning algorithm for following a target boat by an autonomous unmanned surface vehicle (USV) in an environment with static obstacle regions and civilian boats. The planner developed in this work is capable of making a balanced trade-off among the following, possibly conflicting criteria: the risk of losing the(More)
We introduce a model-predictive trajectory planning algorithm for unmanned surface vehicles (USVs) operating in congested civilian traffic. The planner reasons about the availability of contingency maneuvers needed in case of any of the civilian vessels breaches the International Regulations for the Prevention of Collisions at Sea (COLREGs). Our exploratory(More)
— Achieving persistent autonomy requires un-manned surface vehicles (USVs) to be able to deal with a wide variety of complex planning situations. In this paper, we introduce a model-predictive, local trajectory planning algorithm for USVs operating in congested and highly dynamic traffic. The planner generalizes the Velocity Obstacle concept to systems with(More)
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