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Network Offloading Policies for Cloud Robotics: a Learning-based Approach
[article]
2019
arXiv
pre-print
Today's robotic systems are increasingly turning to computationally expensive models such as deep neural networks (DNNs) for tasks like localization, perception, planning, and object detection. However, resource-constrained robots, like low-power drones, often have insufficient on-board compute resources or power reserves to scalably run the most accurate, state-of-the art neural network compute models. Cloud robotics allows mobile robots the benefit of offloading compute to centralized servers
arXiv:1902.05703v1
fatcat:luhs2ejunrayth5jid5uxhs744