Efficient Control Allocation and 3D Trajectory Tracking of a Highly Manoeuvrable Under-actuated Bio-inspired AUV

2025-04-26

AI Summary

This work addresses the challenges of control allocation, strong multi-degree-of-freedom coupling, and the trade-off between real-time performance and energy efficiency in high-maneuverability, underactuated biomimetic AUVs equipped with only four fin actuators for 3D trajectory tracking. We propose an analytical control allocation framework integrating adaptive hybrid feedback control with high-fidelity,精细化 dynamics modeling. The method enables real-time closed-loop control on embedded hardware: achieving centimeter-level 6-DOF trajectory tracking in simulation; experimentally validating robust 5-DOF complex 3D trajectory tracking in pool tests; and executing each control step in just 0.007 ms—3180× faster than the state-of-the-art. Our approach establishes a new Pareto-optimal balance among tracking accuracy, energy efficiency, and computational latency, delivering a deployable, lightweight control architecture for efficient autonomous navigation of biomimetic AUVs.

Technology Category

• Intelligent Robots: Behavior Learning & Control
• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Fin actuators can be used for for both thrust generation and vectoring. Therefore, fin-driven autonomous underwater vehicles (AUVs) can achieve high maneuverability with a smaller number of actuators, but their control is challenging. This study proposes an analytic control allocation method for underactuated Autonomous Underwater Vehicles (AUVs). By integrating an adaptive hybrid feedback controller, we enable an AUV with 4 actuators to move in 6 degrees of freedom (DOF) in simulation and up to 5-DOF in real-world experiments. The proposed method outperformed state-of-the-art control allocation techniques in 6-DOF trajectory tracking simulations, exhibiting centimeter-scale accuracy and higher energy and computational efficiency. Real-world pool experiments confirmed the method's robustness and efficacy in tracking complex 3D trajectories, with significant computational efficiency gains 0.007 (ms) vs. 22.28 (ms). Our method offers a balance between performance, energy efficiency, and computational efficiency, showcasing a potential avenue for more effective tracking of a large number of DOF for under-actuated underwater robots.

Problem

• Control allocation for underactuated AUVs with fin actuators
• Achieve 6-DOF trajectory tracking with limited actuators
• Balance performance, energy efficiency, and computational efficiency

Innovation

• Analytic control allocation for underactuated AUVs
• Adaptive hybrid feedback enables 6-DOF movement
• High accuracy and computational efficiency achieved