Mode Switching Optimal Control for Mobile Dual-Manipulator Collaborative Robots Based on Dynamic Neural Network

In recent years, the new generation of robots, represented by dual-manipulator collaborative robots, has gained significant attention and research from numerous scholars. However, among numerous repetitive motion schemes for mobile robotic manipulators, the issue of task execution by the mobile robotic manipulator during repetitive motion has not been addressed. Especially in engineering applications, the application scenarios of a robot performing multi-step processes are very common. In this paper, mode switching control scheme of mobile dual-manipulator cooperative robots (MDMCR) is proposed based on dynamic neural network (DNN) to study motion control firstly. Then, the collaborative index of dual-arm robots is introduced, dividing the working modes of mobile manipulators into tracking and collaborative transport modes. The novelty of the proposed method is emphasised to ensure the safety, reliability, and stability of the mobile chassis motion control, while simultaneously achieving collaborative control between the robotic manipulators. This further enriches the theoretical framework of cooperative control for MDMCR.