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Related Experiment Video

Updated: Jul 15, 2025

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A Graph-Based Hybrid Reconfiguration Deformation Planning for Modular Robots.

Ruopeng Wei1, Yubin Liu1, Huijuan Dong1

  • 1State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China.

Sensors (Basel, Switzerland)
|September 28, 2023
PubMed
Summary

This study presents a hybrid algorithm for self-reconfigurable modular robots to plan reconfiguration. The algorithm efficiently transforms robot configurations by decomposing them into subconfigurations, enabling effective robotic system planning.

Keywords:
mobile roboticsmodular roboticspath planning for multiple mobile robotsreconfiguration deformationself-reconfigurationswarm robotics

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Self-reconfigurable modular robots can change their structure by altering module connections.
  • Planning the sequence of movements for these robots to reach a new configuration is a complex challenge.

Purpose of the Study:

  • To develop a novel hybrid algorithm for reconfiguration deformation planning in modular robots.
  • To enable efficient transformation between initial and goal configurations for modular robotic systems.

Main Methods:

  • A hybrid algorithm is proposed, decomposing configurations into subconfigurations with maximum commonality.
  • Distributed dynamic mapping of free vertices is implemented.
  • Module mapping relationships are used to generate reconfiguration actions.

Main Results:

  • The algorithm effectively plans reconfiguration sequences for modular robots.
  • Simulation and experimental results demonstrate the algorithm's effectiveness.

Conclusions:

  • The proposed hybrid algorithm offers an efficient solution for the reconfiguration deformation planning problem.
  • This work advances the capabilities of self-reconfigurable modular robotic systems.