AI steers adaptive control systems
A new study led by Flinders University and French researchers has now used a novel bio-inspired computing artificial intelligence solution to improve the potential of Unmanned Underwater Vehicles (UUVs) and other adaptive control systems to operate more reliability in rough seas and other unpredictable conditions.
This innovative approach, using the Biologically-Inspired Experience Replay (BIER) method, aims to overcome data inefficiency and performance degradation by leveraging incomplete but valuable recent experiences, explains first author Dr Thomas Chaffre. The method incorporates two memory buffers, one focusing on recent state-action pairs and the other emphasising positive rewards. To test the effectiveness of the proposed method, researchers conducted simulated scenarios using a robot operating system (ROS)-based UUV simulator and gradually increasing scenarios’ complexity.