A Neural-Dynamics-Based Control Scheme for Double-Arm Mobile Robots with Dynamic Neural Network
Year: 2025
Type: article
Abstract: A double-arm mobile robot (DMR) is an advanced robotic system that integrates a mobile platform and double robotic arms. To address the control issue of the DMR, this paper provides its mathematical model and deduces kinematic equations as preliminaries. On this basis, a physically constrained velocity collaborative control (PCVCC) scheme is proposed for kinematic control of the DMR, which adjusts the mobile platform and robotic arms cooperatively using a designed optimization criterion. To explore the optimal solution of the PCVCC scheme, a gradient descent method assisted by velocity compensation is exploited to design a dynamic neural network (DNN) solver. Subsequently, theoretical analyses confirm the global convergence of the DNN solver. Finally, simulations, experiments, and comparisons demonstrate the feasibility and superiority of the proposed method.
Source: Tsinghua Science & Technology
Authors: Diwen Xiong, Liuyi Wen, Mingsheng Shang
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4417491056