Collective robotic systems are biologically-inspired and exhibit behaviors found in spatial swarms (e.g., fish), colonies (e.g., ants), or a combination of both (e.g., bees). Collective robotic system popularity continues to increase due to their apparent global intelligence and emergent behaviors. Many applications can benefit from the incorporation of collectives, including...
Artificial collectives are useful for accomplishing tasks that require teamwork from multiple simple robots. Multiple robot and collective testbeds have been developed, yet none stay committed to leverage the local interactions, group size, and imperfect information assumptions that strengthen biological collectives. A review of the collective and multiple robot literature,...
This dissertation incorporates coalition formation and probabilistic planning towards a domain-independent automated planning solution scalable to multiple heterogeneous robots in complex domains. The first research direction investigates the effectiveness of Task Fusion and introduces heuristics that improve task allocation and result in better quality plans, while requiring lower computational cost...