Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm

Journal Title: EAI Endorsed Transactions on Collaborative Computing - Year 2016, Vol 2, Issue 8

Abstract

Designing and controlling the collective behavior of a swarm often requires complex range, bearing sensors, and peer-to-peer communication strategies. Recent work studying swarm of robots that have no computational power has shown that complex behaviors such as aggregation and object clustering 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 can be used to control, these collective behaviors. 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.

Authors and Affiliations

Matthew Johnson, Daniel Brown

Keywords

Related Articles

Impact on procurement and training by research on the interaction design of medical devices

We present a case study of how research can influence practice in the procurement of healthcare technology based on the CHI+MED project. CHI+MED is concerned with interaction design and the safety of medical devices. It...

Tracing Coordination and Cooperation Structures via Semantic Burst Detection

Developing technologies that support collaboration requires understanding how knowledge and expertise are shared and distributed among community members. We explore two forms of knowledge distribution structures, coordin...

Reinforcement Learning with Internal Reward for Multi-Agent Cooperation: A Theoretical Approach

This paper focuses on a multi-agent cooperation which is generally difficult to be achieved without sufficient information of other agents, and proposes the reinforcement learning method that introduces an internal rewar...

A Scheme for Collaboratively Processing Nearest Neighbor Queries in Oblivious Storage

Security concerns are a substantial impediment to the wider deployment of cloud storage. There are two main concerns on the confidentiality of outsourced data: i) protecting the data, and ii) protecting the access patter...

Harnessing Context for Vandalism Detection in Wikipedia

The importance of collaborative social media (CSM) applications such as Wikipedia to modern free societies can hardly be overemphasized. By allowing end users to freely create and edit content, Wikipedia has greatly faci...

Download PDF file
  • EP ID EP45719
  • DOI http://dx.doi.org/10.4108/eai.3-12-2015.2262390
  • Views 281
  • Downloads 0

How To Cite

Matthew Johnson, Daniel Brown (2016). Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm. EAI Endorsed Transactions on Collaborative Computing, 2(8), -. https://europub.co.uk/articles/-A-45719