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DART: Diversity-enhanced Autonomy in Robot Teams

Nora Ayanian

Year
2019
Citations
14

Abstract

This paper defines the research area of Diversity-enhanced Autonomy in Robot Teams (DART), a novel paradigm for the creation and design of policies for multi-robot coordination. Although current approaches to multi-robot coordination have been successful in structured, well-understood environments, they have not been successful in unstructured, uncertain environments, such as disaster response. Although robot hardware has advanced significantly in the past decade, the way we solve multi-robot problems has not. Even with significant advances in the field of multi-robot systems, the same problem-solving paradigm has remained: assumptions are made to simplify the problem, and a solution is optimized for those assumptions and deployed to the entire team. This results in brittle solutions that prove incapable if the original assumptions are invalidated. This paper introduces a new multi-robot problem-solving paradigm which uses a diverse set of control policies that work together synergistically within the same team of robots. Such an approach will make multi-robot systems more robust in unstructured and uncertain environments, such as in disaster response, environmental monitoring, and military applications, and allow multi-robot systems to extend beyond the highly structured and highly controlled environments where they are successful today.

Keywords

RobotComputer scienceAutonomyHuman–computer interactionSet (abstract data type)Field (mathematics)Diversity (politics)RoboticsArtificial intelligence

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