GRASP reduces communication in remote control by 12-fold on average (50-fold for continuous actions) by having actors generate actions via guided sampling and local policy learning instead of receiving full actions or rewards.
Edge Computing and Its Application in Robotics: A Survey
3 Pith papers cite this work. Polarity classification is still indexing.
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An experimental evaluation of a QoS-aware Adaptive Task Placement controller in a closed-loop multi-robot Raspberry Pi testbed shows reduced deadline violations and tail latency versus static offloading under stress.
ORICF is a declarative, model-agnostic robotics framework with YAML specs and edge offloading that reduces robot compute utilization by up to 83% and energy by 66% in a ROS2 demo combining ASR, LLM, and CNN.
citing papers explorer
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Remote Action Generation: Remote Control with Minimal Communication
GRASP reduces communication in remote control by 12-fold on average (50-fold for continuous actions) by having actors generate actions via guided sampling and local policy learning instead of receiving full actions or rewards.
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Edge-Based QoS-Aware Adaptive Task Placement: A Closed-Loop Control in Multi-Robot Systems
An experimental evaluation of a QoS-aware Adaptive Task Placement controller in a closed-loop multi-robot Raspberry Pi testbed shows reduced deadline violations and tail latency versus static offloading under stress.
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ORICF -- Open Robotics Inference and Control Framework
ORICF is a declarative, model-agnostic robotics framework with YAML specs and edge offloading that reduces robot compute utilization by up to 83% and energy by 66% in a ROS2 demo combining ASR, LLM, and CNN.