Morphological communication for swarms

Abstract

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.

State-transfer modeling collective behavior of multi-ball Bernoulli system based on local interaction forces

“…Morphologically communicated swarm robots deform their shape through physical interaction. These researches take the interactions between individuals as a method of communication ( Rubenstein et al, 2014 ; Sharma et al, 2020 ). However, in nature, especially for birds ( Lissaman and Shollenberger, 1970 ) and fish ( Liao et al, 2003 ), the interactions in the swarm include information exchange and dynamic forces that grant them high coordination complexity.…”