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. While 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. The reason for this is not due to limitations in robot hardware, which has advanced significantly in the past decade, but in how multi-robot problems are solved. 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 relies on a diverse set of control policies that work together synergistically to make multi-robot systems more resilient in unstructured and uncertain environments.
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Acknowledgements
This work was supported by NSF CAREER (IIS-1553726) and the Okawa Foundation Research Award. Special thanks to Gaurav Sukhatme, M. Ani Hsieh, and Fei Sha for conversations and guidance in formulating this line of research.
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Ayanian, N. (2020). DART: Diversity-Enhanced Autonomy in Robot Teams. In: Amato, N., Hager, G., Thomas, S., Torres-Torriti, M. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-28619-4_2
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