Real-time cooperative kinematic control for multiple robots in distributed scenarios with dynamic neural networks

This work investigates the real-time cooperative kinematic control for multiple robots in distributed sce-narios. The information interaction among robots is described as a directed topology in which each robotic manipulator is connected to specified nodes. Besides, a performance index of minimum joint velocity norm is introduced to regulate the robots' motion. Combining with the performance index and integrating the related constraints, a control scheme is developed to guide the behavior of robots with an error feedback term leveraged to improve the real-time execution accuracy of tasks. Moreover, considering that the involved parameters are time-dependent, a dynamic neural-network-assisted solver is constructed to solve the control scheme online. In the end, simulations and illustrative experiments on the virtual robot experiment platform (V-REP) are conducted by a set of UR5 robots to execute tasks in a switchable directed topology, where the corresponding results demonstrate the effectiveness of the pro-posed scheme. (c) 2021 Elsevier B.V. All rights reserved.