Graph-Based Dynamics and Network Control of a Single Articulated Robotic System
Jonathan Lane, Nak-seung Patrick Hyun
- Year
- 2025
- Access
- Open access
Abstract
Extensive research on graph-based dynamics and control of multi-agent systems has successfully demonstrated control of robotic swarms, where each robot is perceived as an independent agent virtually connected by a network topology. The strong advantage of the network control structure lies in the decentralized nature of the control action, which only requires the knowledge of virtually connected agents. In this paper, we seek to expand the ideas of virtual network constraints to physical constraints on a class of tree-structured robots which we denote as single articulated robotic (SAR) systems. In our proposed framework, each link can be viewed as an agent, and each holonomic constraint connecting links serves as an edge. By following the first principles of Lagrangian dynamics, we derive a consensus-like matrix-differential equation with weighted graph and edge Laplacians for the dynamics of a SAR system. The sufficient condition for the holonomic constraint forces becoming independent to the control inputs is derived. This condition leads to a decentralized leader-follower network control framework for regulating the relative configuration of the robot. Simulation results demonstrate the effectiveness of the proposed control method.
Keywords
Related papers
Dynamic reconfiguration in multi-robot agent systems using embedded language models
Shokhikha Amalana Murdivien, Jongsu Park, Jumyung Um
Robotics and Computer-Integrated Manufacturing · 2026
Hierarchical decision-making for UAVs’ game via LLM enhanced multi-agent reinforcement learning
Xinyu Dong, Bo Li, Guangyu Zhang +2 more
Aerospace Science and Technology · 2026
Formation optimization and obstacle avoidance decision-making methods for cooperative coverage search of multi-UUVs in underwater wreck areas
Haomiao Yu, Zeyuan Zhang, Yantian Ma
Robotics and Autonomous Systems · 2026
Human-in-the-Loop Swarms: A Bionic Swarm Approach to Real-World Soil Mapping
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu +3 more
2026