Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/119205
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Title: Self-reconfiguration planning for deformable quadrilateral modular robots
Authors: Gu, J
Gao, H
Xia, Z
Sun, Y
Tian, C
Zhang, D 
Issue Date: Jun-2026
Source: IEEE robotics and automation letters, June 2026, v. 11, no. 6, p. 7300-7307
Abstract: While deformable modular self reconfigurable robots offer enhanced reconfiguration flexibility, strict kinematic constraints present complex self reconfiguration planning challenges. This letter presents a novel self-reconfiguration planning algorithm for deformable quadrilateral MSRRs. 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.
Keywords: Cellular and modular robots
Task and motion planning
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE robotics and automation letters 
EISSN: 2377-3766
DOI: 10.1109/LRA.2026.3685902
Rights: © 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication J. Gu, H. Gao, Z. Xia, Y. Sun, C. Tian and D. Zhang, "Self-Reconfiguration Planning for Deformable Quadrilateral Modular Robots," in IEEE Robotics and Automation Letters, vol. 11, no. 6, pp. 7300-7307, June 2026 is available at https://doi.org/10.1109/LRA.2026.3685902.
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