Report on Current Developments in Autonomous Marine Vehicles
General Direction of the Field
The field of autonomous marine vehicles is witnessing significant advancements, particularly in the areas of control systems, state estimation, and safety certification. Recent developments are focused on enhancing the robustness and adaptability of these systems to handle complex and unpredictable marine environments. Innovations in adaptive control, reachability analysis, and multi-sensor fusion are driving the field forward, enabling more precise and reliable operations for uncrewed surface vehicles (USVs) and autonomous underwater vehicles (AUVs).
One of the key trends is the integration of advanced control algorithms, such as model reference adaptive control (MRAC), to stabilize and navigate USVs in the presence of disturbances like thruster failures and drag forces. These algorithms are being paired with reachability analysis modules to predict future states and ensure real-time safety certification, thereby enhancing the overall autonomy and reliability of marine vehicles.
State estimation techniques are also evolving, with a growing emphasis on leveraging data from multiple sensors, including those on unmanned aerial vehicles (UAVs), to provide robust and accurate estimates of marine vessel states. This multi-sensor fusion approach is critical for enabling complex tasks such as cooperative landing and object manipulation, even in challenging weather conditions.
Another notable development is the refinement of guidance laws for underactuated autonomous underwater helicopters (AUHs). These improvements are aimed at enhancing path following and docking procedures, with a focus on precise tracking and stability. The incorporation of nonlinear tracking differentiators and anti-saturation controllers is proving to be particularly effective in mitigating issues related to rapid variations and propeller thrust buffet.
Noteworthy Papers
Safe Autonomy for Uncrewed Surface Vehicles Using Adaptive Control and Reachability Analysis: Demonstrates a significant reduction in position error and real-time safety certification through MRAC and reachability analysis.
State Estimation of Marine Vessels Affected by Waves by Unmanned Aerial Vehicles: Introduces a novel 6-DOF nonlinear model and multi-sensor fusion approach, outperforming current state-of-the-art methods.
An Improved ESO-Based Line-of-Sight Guidance Law for Path Following of Underactuated Autonomous Underwater Helicopter With Nonlinear Tracking Differentiator and Anti-saturation Controller: Enhances path following performance and stability through innovative guidance law improvements.
