Distributed Cooperative Kinematic Control of Multiple Robotic Manipulators With an Improved Communication Efficiency

An efficiency-oriented solution is theoretically a preferred choice to support the efficient operation of a system. Although some studies on the multimanipulator system share the load of the control center by transforming the network topology, the whole system often suffers an increased communication burden. In this article, a multimanipulator cooperative control scheme with an improved communication efficiency is proposed to allocate limited communication resources reasonably. The entire control process is formulated from the perspective of the game theory, and finally, evolved into a problem of finding a Nash equilibrium with time-varying parameters. Then, a neural network solver is designed to update the strategies of manipulators. Theoretical analysis supports the convergence and robustness of the solver. In addition, Zeno behavior does not occur under the domination of the control strategy. Finally, simulative results reveal that the proposed control strategy has advantages over the traditional periodic control in communication.

Automated summary

In this article, a multimanipulator cooperative control scheme with improved communication efficiency is proposed. The scheme formulates the entire control process from the perspective of game theory and uses a neural network solver to update the strategies of manipulators. Theoretical analysis and simulation results support the superiority of the proposed control strategy.