62 citations · 84 across the 10 of their papers we have counts for
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Sampling Training Data for Continual Learning Between Robots and the Cloud
Sandeep Chinchali, Evgenya Pergament, Manabu Nakanoya +5
Today's robotic fleets are increasingly measuring high-volume video and LIDAR sensory streams, which can be mined for valuable training data, such as rare scenes of road constructi…
Task-relevant Representation Learning for Networked Robotic Perception
Manabu Nakanoya, Sandeep Chinchali, Alexandros Anemogiannis +3
Today, even the most compute-and-power constrained robots can measure complex, high data-rate video and LIDAR sensory streams. Often, such robots, ranging from low-power drones to…
Network Offloading Policies for Cloud Robotics: a Learning-based Approach
Sandeep Chinchali, Apoorva Sharma, James Harrison +6
Today's robotic systems are increasingly turning to computationally expensive models such as deep neural networks (DNNs) for tasks like localization, perception, planning, and obje…