Safe Autonomy for Uncrewed Surface Vehicles Using Adaptive Control and Reachability Analysis
Karan Mahesh, Tyler M. Paine, Max L. Greene, Nicholas Rober, Steven, Lee, Sildomar T. Monteiro, Anuradha Annaswamy, Michael R. Benjamin, Jonathan, P. How

TL;DR
This paper presents a safe autonomy framework for uncrewed surface vehicles using adaptive control and reachability analysis, enabling real-time disturbance estimation and safety certification during marine operations.
Contribution
It introduces a combined adaptive control and reachability approach for USV safety and performance assurance in unpredictable marine environments.
Findings
MRAC controller reduced position error by up to 81%.
Reachability module enabled real-time safety certification.
Validated on USV in real-world and simulated scenarios.
Abstract
Marine robots must maintain precise control and ensure safety during tasks like ocean monitoring, even when encountering unpredictable disturbances that affect performance. Designing algorithms for uncrewed surface vehicles (USVs) requires accounting for these disturbances to control the vehicle and ensure it avoids obstacles. While adaptive control has addressed USV control challenges, real-world applications are limited, and certifying USV safety amidst unexpected disturbances remains difficult. To tackle control issues, we employ a model reference adaptive controller (MRAC) to stabilize the USV along a desired trajectory. For safety certification, we developed a reachability module with a moving horizon estimator (MHE) to estimate disturbances affecting the USV. This estimate is propagated through a forward reachable set calculation, predicting future states and enabling real-time…
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Taxonomy
TopicsMaritime Navigation and Safety
