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Stochastic Jumping Robots for Large‐Scale Environmental Sensing

Julian Hird, Andrew T. Conn, Sabine Hauert

发表年份
2022
引用次数
2
访问权限
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摘要

Single‐use jumping robots that are mass‐producible and biodegradable could be quickly released for environmental sensing applications. Such robots would be pre‐loaded to perform a set number of jumps, in random directions and with random distances, removing the need for onboard energy and computation. Stochastic jumpers build on embodied randomness and large‐scale deployments to perform useful work. This paper introduces simulation results showing how to construct a large group of stochastic jumpers to perform environmental sensing, and the first demonstration of robot prototypes that can perform a set number of sequential jumps, have full‐body sensing, and are well suited to be made biodegradable. An interactive preprint version of the article can be found at: https://www.authorea.com/doi/full/10.22541/au.163525369.97561426 .

关键词

RandomnessRobotPreprintComputer scienceSet (abstract data type)Scale (ratio)ComputationConstruct (python library)JumpingSimulation

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