Self-Reconfiguration Planning for Deformable Quadrilateral Modular Robots

📅 2026-01-27
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🤖 AI Summary
This work addresses the challenges of connection stability and physical feasibility in self-reconfiguration of deformable quadrilateral modular robots. The authors propose a novel planning algorithm based on virtual graph modeling and a Dependency Reversal Tree (DRTree). The virtual graph generates connect/disconnect actions that satisfy kinematic constraints, while the DRTree explicitly encodes inter-action dependencies to guarantee both stability and feasibility of the reconfiguration sequence. Notably, this is the first method to prove the existence of stable, motion-feasible reconfiguration sequences for nonlinear topologies involving seven or more modules. Experimental results demonstrate that the proposed approach outperforms an improved BiRRT algorithm in both efficiency and stability, and its practical deployability is validated on a real modular robot platform.

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📝 Abstract
For lattice modular self-reconfigurable robots (MSRRs), maintaining stable connections during reconfiguration is crucial for physical feasibility and deployability. This letter presents a novel self-reconfiguration planning algorithm for deformable quadrilateral MSRRs that guarantees stable connection. The method first constructs feasible connect/disconnect actions using a virtual graph representation, and then organizes these actions into a valid execution sequence through a Dependence-based Reverse Tree (DRTree) that resolves interdependencies. We also prove that reconfiguration sequences satisfying motion characteristics exist for any pair of configurations with seven or more modules (excluding linear topologies). Finally, comparisons with a modified BiRRT algorithm highlight the superior efficiency and stability of our approach, while deployment on a physical robotic platform confirms its practical feasibility.
Problem

Research questions and friction points this paper is trying to address.

self-reconfiguration
modular robots
stable connection
deformable quadrilateral
lattice MSRRs
Innovation

Methods, ideas, or system contributions that make the work stand out.

self-reconfiguration planning
modular robots
stable connection
Dependence-based Reverse Tree
virtual graph representation
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Jie Gu
Jie Gu
Professor of Electrical Engineering and Computer Science, Northwestern University
VLSI DesignMixed-signal DesignEmerging Technology IntegrationComputer Architecture
H
Hongrun Gao
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
Z
Zhihao Xia
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
Y
Yirun Sun
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
C
Chunxu Tian
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
Dan Zhang
Dan Zhang
Professor, The Hong Kong Polytechnic University
roboticsparallel kinematic machinesmechatronicsmanufacturing systems