Abstract
Industry 4.0 applications rely on mobile robotic agents that execute many complex tasks that have strict safety and time requirements. Under this setting, the Edge Computing service delivery model allows the robotic agents to offload their computationally intensive tasks to powerful computing infrastructure in their vicinity. In this study, we propose a novel switching offloading mechanism for such robotic applications. In particular, we design opportunistic offloading strategies for the path planning and localization services of mobile robots. The offloading decision is based on the uncertainty of the robot's pose, the resource availability at the Edge of the network and the difficulty of the path planning. Our switching offloading framework is implemented and evaluated using a robot in a real Edge Computing testbed, where the trade-off between execution time and the successful completion of the robot trajectory is highlighted.
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