Web: http://arxiv.org/abs/2205.05748

May 13, 2022, 1:11 a.m. | Sabrina M. Neuman, Brian Plancher, Bardienus P. Duisterhof, Srivatsan Krishnan, Colby Banbury, Mark Mazumder, Shvetank Prakash, Jason Jabbour, Aleksan

cs.LG updates on arXiv.org arxiv.org

Machine learning (ML) has become a pervasive tool across computing systems.
An emerging application that stress-tests the challenges of ML system design is
tiny robot learning, the deployment of ML on resource-constrained low-cost
autonomous robots. Tiny robot learning lies at the intersection of embedded
systems, robotics, and ML, compounding the challenges of these domains. Tiny
robot learning is subject to challenges from size, weight, area, and power
(SWAP) constraints; sensor, actuator, and compute hardware limitations;
end-to-end system tradeoffs; and a …

arxiv challenges learning machine machine learning robot robots

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