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arXiv Robotics — research abstracts· Anais Jeger, Harry Holt, Lennart Puck·· 3 hours agoSignalEditorial score86

Emergent Cooperative Thermoregulation in Lunar Swarm Robotics

Emergent Cooperative Thermoregulation in Lunar Swarm Robotics

Summary

This research explores how a swarm of 20 lunar robots can survive the extreme cold of the lunar night by collectively regulating temperature through emergent behavior, inspired by penguin huddling. A single reinforcement learning policy enables the swarm to aggregate and circulate between sheltered and exposed areas, achieving survival with 37% less energy than a motionless huddle.

Editorial context

This study demonstrates how a swarm of lunar robots can collectively regulate temperature through emergent behavior, inspired by penguin huddling, without requiring explicit spatial coordination or physical contact between robots.

Source: arXiv Robotics — research abstracts · Read original article ↗

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What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Reported numbers

  • stored energy per robot

    >155.6

    View original evidence
    egates, and robots circulate between the sheltered core and the exposed rim, the same pair of behaviors with which emperor penguins survive the Antarctic winter. We measure the survival threshold, the smallest stored energy per robot at which every robot is still alive at sunrise. Across ten runs it is 155.6 +/- 1.3 pcm-h, where one pcm-h is 7.2 kJ of stored heat. That is 37% below a motionless huddle and within 13%
    Open source S4
  • stored energy per robot

    1.3

    View original evidence
    egates, and robots circulate between the sheltered core and the exposed rim, the same pair of behaviors with which emperor penguins survive the Antarctic winter. We measure the survival threshold, the smallest stored energy per robot at which every robot is still alive at sunrise. Across ten runs it is 155.6 +/- 1.3 pcm-h, where one pcm-h is 7.2 kJ of stored heat. That is 37% below a motionless huddle and within 13%
    Open source S4
  • pcm-h

    7.2

    View original evidence
    egates, and robots circulate between the sheltered core and the exposed rim, the same pair of behaviors with which emperor penguins survive the Antarctic winter. We measure the survival threshold, the smallest stored energy per robot at which every robot is still alive at sunrise. Across ten runs it is 155.6 +/- 1.3 pcm-h, where one pcm-h is 7.2 kJ of stored heat. That is 37% below a motionless huddle and within 13%
    Open source S4
  • Robot count

    20 robots

    View original evidence
    ther a swarm can instead use its own members as thermal shielding. We train one policy, shared by all twenty robots, by reinforcement learning with an evolution-strategies estimator. The policy receives a single reward, once, at the end of the night: the mean temperature of the five coldest robots. Nothing in that reward refers to position, spacing, exposure or motion. Two behaviors nonetheless emerge. The swarm aggr
    Open source S3
  • robots

    40

    View original evidence
    of a physics-based lower bound, and at a budget where the motionless huddle loses six robots, every robot survives. The behavior needs no shared spatial reference and no robot-robot contact, and transfers from twenty robots to forty without retraining.
    Open source S5
  • paper: not_reported
  • code: not_reported
  • weights: not_reported
  • dataset: not_reported
Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

egates, and robots circulate between the sheltered core and the exposed rim, the same pair of behaviors with which emperor penguins survive the Antarctic winter. We measure the survival threshold, the smallest stored energy per robot at which every robot is still alive at sunrise. Across ten runs it is 155.6 +/- 1.3 pcm-h, where one pcm-h is 7.2 kJ of stored heat. That is 37% below a motionless huddle and within 13%

Open source S4

ther a swarm can instead use its own members as thermal shielding. We train one policy, shared by all twenty robots, by reinforcement learning with an evolution-strategies estimator. The policy receives a single reward, once, at the end of the night: the mean temperature of the five coldest robots. Nothing in that reward refers to position, spacing, exposure or motion. Two behaviors nonetheless emerge. The swarm aggr

Open source S3

of a physics-based lower bound, and at a budget where the motionless huddle loses six robots, every robot survives. The behavior needs no shared spatial reference and no robot-robot contact, and transfers from twenty robots to forty without retraining.

Open source S5

Source:arXiv Robotics — research abstracts · arxiv.org

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