Human-in-the-Loop Task-Space Coordination Control for Heterogeneous Robotic Systems with Delayed Network

• Published in: 2021 American Control Conference (ACC) pp. 2751 - 2756
• Main Authors: Ngo, Van-Tam, Liu, Yen-Chen
• Format: Conference Proceeding
• Language: English
• Published: American Automatic Control Council 25.05.2021
• Subjects: Adaptation models; Adaptive systems; coordination control; Delay effects; distributed synchronization; Heuristic algorithms; Human-in-the-loop system; networked Euler-Lagrange systems; Neural networks; Robot kinematics; Robust control; task-space control
• DOI: 10.23919/ACC50511.2021.9483398

In this paper, we propose a distributed control algorithm for an operator to remotely interact with a network of multiple robotic systems to exploit the advantage of complementary capabilities of humans and networked robots. A controller that combines adaptive neural network, task-space synchronization, and robust control algorithm, is proposed to account for several practical issues such as uncertain dynamic model, disturbance, and time delays communication. On the basis of Lyapunov technique, the system stability and boundedness of tracking errors are proven. Semi-experiments with a network of heterogeneous robotic systems are carried to verify and demonstrate the efficacy/potency of the proposed control framework.