Cross-platform Learning-based Fault Tolerant Surfacing Controller for Underwater Robots

TL;DR

This paper introduces a reinforcement learning-based fault-tolerant surfacing controller for underwater robots that adapts across different platforms and failure scenarios, validated through simulations and real-world experiments.

Contribution

It presents a novel cross-platform RL controller with transfer learning capabilities that improves fault tolerance and generalization for diverse underwater robots.

Findings

Achieved 85.7% success rate in real-world tests.

Demonstrated effective transfer of policies from simulation to physical robots.

Outperformed baseline controllers in stability and success rate.

Abstract

In this paper, we propose a novel cross-platform fault-tolerant surfacing controller for underwater robots, based on reinforcement learning (RL). Unlike conventional approaches, which require explicit identification of malfunctioning actuators, our method allows the robot to surface using only the remaining operational actuators without needing to pinpoint the failures. The proposed controller learns a robust policy capable of handling diverse failure scenarios across different actuator configurations. Moreover, we introduce a transfer learning mechanism that shares a part of the control policy across various underwater robots with different actuators, thus improving learning efficiency and generalization across platforms. To validate our approach, we conduct simulations on three different types of underwater robots: a hovering-type AUV, a torpedo shaped AUV, and a turtle-shaped robot (U-CAT). Additionally, real-world experiments are performed, successfully transferring the learned policy from simulation to a physical U-CAT in a controlled environment. Our RL-based controller demonstrates superior performance in terms of stability and success rate compared to a baseline controller, achieving an 85.7 percent success rate in real-world tests compared to 57.1 percent with a baseline controller. This research provides a scalable and efficient solution for fault-tolerant control for diverse underwater platforms, with potential applications in real-world aquatic missions.