Force-Reflecting Hierarchical Approach for Human-Aided Teleoperation of NRS With Event-Triggered Local Communication

In this article, we present a novel system architecture for teleoperation of the networked robotic system (NRS), involving several slave robots (i.e., followers) interconnected through event-triggered local communication, based on one/several long-distance communication links between a human-operated master robot (i.e., leader) and one/multiple followers. The control objective of such human-aided teleoperation problem is to force the master robot to track the slave ones in a fixed time under the human supervision, and meanwhile to drive all the slave ones to track the master in a fixed time, thus allowing the human operator to flexibly and remotely control the NRS. Another important concern in this article is to improve the telepresence of such system, i.e., to reconstruct the interaction force between followers and the task environment in the side of the human operator. To this end, a novel force-reflecting hierarchical control framework, involving the (local) dissipativity layer, (estimate) event-triggered layer, fixed-time force observer and neuroadaptive observer, is proposed. Based on the tools of hierarchical control analysis and Lyapunov stability, we derive several sufficient conditions for guaranteeing the fixed-time stability of the closed-loop dynamics. Finally, several experiments are performed to illustrate the performance of the proposed results.