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

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 synchronizat...

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Bibliographic Details
Published in2021 American Control Conference (ACC) pp. 2751 - 2756
Main Authors Ngo, Van-Tam, Liu, Yen-Chen
Format Conference Proceeding
LanguageEnglish
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
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Summary: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.
ISSN:2378-5861
DOI:10.23919/ACC50511.2021.9483398