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Modular robots can enhance reliability by sharing resources locally. This approach allows a robot collective to overcome module failures and successfully complete missions, even with limited individual module capabilities.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • System Reliability

Background:

  • Modular robots face a trade-off between functionality and failure rates, where more modules increase complexity and potential failure points.
  • Existing systems struggle to balance adaptability with robust performance in the face of inevitable component failures.
  • The number of modules in robotic systems directly impacts both their functional capabilities and their susceptibility to failure.

Purpose of the Study:

  • To develop a novel methodology for enhancing the reliability of modular robots.
  • To investigate the effectiveness of local resource sharing in mitigating the impact of module failures.
  • To demonstrate that increased modularity can lead to improved system robustness through redundancy.

Main Methods:

  • A unified methodology for local resource sharing was developed, encompassing local power sharing, hybrid communication, and local sensor fusion.
  • Local power sharing was implemented to balance energy distribution among modules.
  • Hybrid communication protocols were used to efficiently spread messages across the robot collective.
  • Local sensor fusion was employed to propagate comprehensive system state information.

Main Results:

  • The proposed resource-sharing methodology was experimentally validated on the Mori3 modular robot.
  • Despite one module being deprived of power, sensing, and communication, the robot collective successfully executed a locomotion mission.
  • The experimental results demonstrated the capability of neighboring modules to support each other through resource sharing.
  • The system exhibited enhanced resilience and adaptability in a challenging environment.

Conclusions:

  • Local resource sharing is an effective strategy for improving the reliability of modular robotic systems.
  • Increased modularity, when coupled with intelligent resource management, can enhance system robustness rather than diminishing it.
  • The developed methodology enables modular robots to overcome individual module failures and maintain mission performance through collective support.