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Title: A Primitive-Based Approach to Good Seamanship Path Planning for Autonomous Surface Vessels
This paper offers a multi-layer planning approachfor autonomous surface vessels (ASVs) that must adhere togood seamanship practices and the International Regulationsfor Prevention of Collisions at Sea (COLREGS) [1]. The ap-proach combines novel situational awareness logic with motionprimitive-based planners in a receding horizon framework.Further, ship domain and ship arena concepts are used todevelop risk metrics that capture COLREGS compliance andthe notion of good seamanship. By relying on metrics-drivenmotion planning as opposed to rule-based conditions, theproposed framework scales naturally to non-trivial single-vessel and multi-vessel situations. The planner is evaluatedusing adaptive, simulation-based testing to statistically comparethe performance to other standard methods. Finally, proof-of-concept field experiments are presented on a subscale platform  more » « less
Award ID(s):
1931821
PAR ID:
10268280
Author(s) / Creator(s):
;
Date Published:
Journal Name:
IEEE International Conference on Robotics and Automation
ISSN:
1049-3492
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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