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February 12, 2026Science Robotics0 citations

Scalable robot collective resilience by sharing resources

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KHKevin HoldcroftABAnastasia BolotnikovaAMAntoni Jubés Monforte

Key Points

  • The research aims to enhance the reliability and adaptability of modular robots through local resource sharing.
  • Developed a unified methodology for local resource sharing among robots.
  • Implemented local power sharing for balanced energy distribution.
  • Utilized hybrid communication for message spreading across modules.
  • Applied local sensor fusion to propagate system state information among the robot collective.
  • Modular robots successfully completed locomotion tasks despite one module lacking its own resources.
  • Local resource sharing allowed neighboring modules to compensate for deficits in power, sensing, and communication.

Abstract

No system is immune to failure. The compromise between reducing failures and improving adaptability is a recurring problem in robotics. Modular robots exemplify this tradeoff, because the number of modules dictates both the possible functions and the odds of failure. We reverse this trend, improving reliability with an increased number of modules by exploiting redundant resources and sharing them locally. We present a unified methodology for local resource sharing; local power sharing balances energy distribution, hybrid communication spreads messages, and local sensor fusion propagates full system state estimate information among the robot collective. We present the experimental results of our methodology applied to a modular robot, Mori3. Despite one module being deprived of its own resources in terms of power, sensing, and communication, the robot collective can successfully perform a locomotion mission in a challenging environment, thanks to neighboring modules supporting each other via our proposed resource-sharing methodology.

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Cite This Study

Holdcroft et al. (2026) studied this question.

synapsesocial.com/papers/698d6edc5be6419ac0d54c92https://doi.org/10.1126/scirobotics.ady6304
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