@inproceedings{tsolakis_colregs-aware_2022,
	title = {{COLREGs}-aware {Trajectory} {Optimization} for {Autonomous} {Surface} {Vessels}},
	url = {paper=https://r2clab.com/wp-content/uploads/2022/08/COLREGs_aware_Trajectory_Optimization_for_Autonomous_Surface_Vessels_final.pdf video=https://www.youtube.com/watch?v=bsmOtoxRZKU},
	abstract = {This paper presents a rule-compliant trajectory optimization method for the
guidance and control of autonomous surface vessels. The method builds on Model Predictive
Contouring Control and incorporates the International Regulations for Preventing Collisions at
Sea—known as COLREGs—relevant for motion planning. We use these traffic rules to derive
a trajectory optimization algorithm that guarantees safe navigation in mixed-traffic conditions,
that is, in traffic environments with human operated vessels. The choice of an optimizationbased approach enables the formalization of abstract verbal expressions, such as traffic rules,
and their incorporation in the trajectory optimization algorithm along with the dynamics and
other constraints that dictate the system’s evolution over a sufficiently long receding horizon.
The ability to plan considering different types of constraints over a long horizon in a unified
manner leads to a proactive motion planner that mimics rule-compliant maneuvering behavior.
The efficacy of the derived algorithm is validated in different simulation scenarios.},
	booktitle = {14th {IFAC} {Conference} on {Control} {Applications} in {Marine} {Systems} ({CAMS})},
	publisher = {IFAC},
	author = {Tsolakis, A. and Benders, D. and de Groot, O. and Negenborn, R. R. and Reppa, V. and Ferranti, L.},
	year = {2022},
	note = {Finalist for the IFAC CAMS Young Author Award},
	keywords = {key\_collision\_avoidance, key\_maritime, key\_motion\_planning, key\_mpc},
}

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The choice of an optimizationbased approach enables the formalization of abstract verbal expressions, such as traffic rules, and their incorporation in the trajectory optimization algorithm along with the dynamics and other constraints that dictate the system’s evolution over a sufficiently long receding horizon. The ability to plan considering different types of constraints over a long horizon in a unified manner leads to a proactive motion planner that mimics rule-compliant maneuvering behavior. 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