An Economical Framework for Verification of Swarm-Based Algorithms Using Small, Autonomous Robots

Abstract : We present an economical ($6,000) framework for verifying, in hardware, swarm-based algorithms that were previously developed in computer simulation of large numbers of weapons engaging a plurality of highly maneuverable targets. This framework consists of a maximum of 10 small, autonomous, ground robots and an overhead vision tracking system that mimics both global positioning system (GPS) localization and peer-to-peer robot communications. Robots maintain a cohesive network formation by balancing a virtual system of interconnecting spring forces. The use of an optimal target-weapon pairing algorithm and interception methods enable weapons to intercept targets while minimizing global transit distance. Experimental results indicate that network formation occurs, on the average, in less than 25 seconds for a sixnode robotic swarm. Thus our framework provides an economical, simple, quick, and reliable way of investigating the interaction among the mobile nodes of a robotic swarm using embedded algorithms.