Coverage control: From heterogeneous robot teams to expressive swarms

Abstract

Coverage control constitutes a canonical multi-robot coordination strategy that allows a collection of robots to distribute themselves over a domain to optimally monitor the relevant features of the environment. This thesis examines two different aspects of the coverage problem. On the one hand, we investigate how coverage should be performed by a multi-robot team with heterogeneous sensor equipment in the presence of qualitatively different types of events or features in the domain, which may evolve over time. To this end, different information exchange strategies among the robots are considered, and the performance of the resulting distributed control laws is compared experimentally on a team of mobile robots. In addition, we present a constraint-based approach that allows the multi-robot team to cover different types of features whose locations in the domain may evolve other time. On the other hand, in the context of swarm robotics in the arts, this thesis investigates how the coverage paradigm, which affords the control of the entire multi-robot team through the high-level specification of density functions, can serve as an effective interaction modality for artists to effectively utilize robotic swarms in different forms of art expression. In particular, we explore the use of coverage, along with other standard multi-robot control algorithms, to create emotionally expressive behaviors for robot theatre applications. Furthermore, the heterogeneous coverage framework developed in this thesis is employed to interactively control desired concentrations of color throughout a canvas for the purpose of artistic multi-robot painting.