The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden,  Designing and controlling simple collective robot behaviors often requires complex range and bearing sensors and peerto-peer communication strategies. Recent work studying swarms robots that have no computational power has shown that complex behaviors such as aggregation and clustering items can be produced from extremely simple control policies and sensing capability. We extend previous work on computation-free swarm behaviors and show that it is possible to evolve simple control policies to form a perimeter around a target, rendezvous to a specific location, and perform foraging. We also demonstrate that simple manipulations of the environment provide a form of stigmergic control, whereby these collective behavior can be controlled. The robustness and expressiveness of these behaviors, combined with the simple requirements for control and sensing, demonstrate the feasibility of implementing swarm behaviors at small scales or in extreme environments.  SUBJECT TERMS Designing and controlling simple collective robot behaviors often requires complex range and bearing sensors and peerto-peer communication strategies. Recent work studying swarms robots that have no computational power has shown that complex behaviors such as aggregation and clustering items can be produced from extremely simple control policies and sensing capability. We extend previous work on computation-free swarm behaviors and show that it is possible to evolve simple control policies to form a perimeter around a target, rendezvous to a specific location, and perform foraging. We also demonstrate that simple manipulations of the environment provide a form of stigmergic control, whereby these collective behavior can be controlled. The robustness and expressiveness of these behaviors, combined with the simple requirements for control and sensing, demonstrate the feasibility of implementing swarm behaviors at small scales or in extreme environments.
Recent work shows that complex collective behaviours can be achieved on computation-free robots, such as aggregation and foraging REF .
Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm.
EAI Endorsed Trans. Collaborative Computing
EAI Endorsed Trans. Collaborative Computing
Computer Science Engineering