A Minimalistic Approach to Segregation in Robot Swarms
This addresses segregation challenges in robot swarms for applications like sorting or organization, but it is incremental as it builds on existing decentralized approaches with simplified assumptions.
The paper tackles the problem of achieving segregation into multiple groups in robot swarms using a decentralized algorithm, and it results in a thorough analysis of parameter spaces and conditions for guaranteed convergence with minimalistic assumptions.
We present a decentralized algorithm to achieve segregation into an arbitrary number of groups with swarms of autonomous robots. The distinguishing feature of our approach is in the minimalistic assumptions on which it is based. Specifically, we assume that (i) Each robot is equipped with a ternary sensor capable of detecting the presence of a single nearby robot, and, if that robot is present, whether or not it belongs to the same group as the sensing robot; (ii) The robots move according to a differential drive model; and (iii) The structure of the control system is purely reactive, and it maps directly the sensor readings to the wheel speeds with a simple 'if' statement. We present a thorough analysis of the parameter space that enables this behavior to emerge, along with conditions for guaranteed convergence and a study of non-ideal aspects in the robot design.