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Asheesh Sharma
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Proceedings Papers
Morphological communication for swarms
Open Access
. isal2020, ALIFE 2020: The 2020 Conference on Artificial Life549-557, (July 13–18, 2020) 10.1162/isal_a_00300
Abstract
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Robotic swarms rely on local communication between agents to exhibit cooperative emergent behaviours. Local communication is typically implemented with technologies that require dedicated electronics, that can be expensive and difficult to miniaturise or mass-produce. Computational resources are then needed to transform this information into a robot action following a set of rules, further limiting swarm lifetime (battery) and scalability. In this paper, we propose an alternative approach by using the concept of morphological computation (computation through morphology) for local communication in swarms. In such a swarm, local communication is implemented as simple mass-spring-damper systems between agents, instead of electronics. We test this approach in a simple scenario where a swarm has to squeeze through a narrow gap while floating on water. We tested different types of swarms (with different levels of control) and measured their average performance and energy efficiency. We found that by offloading the majority of communication and information processing to the morphology, swarms can exhibit interesting, emergent, cooperative behaviour to solve the given task.