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Mobility-Aware Computation Offloading for Swarm Robotics using Deep Reinforcement Learning

arXiv 2308.11154 ↗First posted 22 Aug 2023cs.RO cs.LG cs.SYcited by 0

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Abstract (arXiv)

Swarm robotics is envisioned to automate a large number of dirty, dangerous, and dull tasks. Robots have limited energy, computation capability, and communication resources. Therefore, current swarm robotics have a small number of robots, which can only provide limited spatio-temporal information. In this paper, we propose to leverage the mobile edge computing to alleviate the computation burden. We develop an effective solution based on a mobility-aware deep reinforcement learning model at the edge server side for computing scheduling and resource. Our results show that the proposed approach can meet delay requirements and guarantee computation precision by using minimum robot energy.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 22 Aug 2023.

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3 of 9 references.

References · 3

  1. 2019Network Offloading Policies for Cloud Robotics: a Learning-based Approachcited by 17
  2. 2017Learning-Based Computation Offloading for IoT Devices with Energy Harvestingcited by 15
  3. 2018UAV-Enabled Mobile Edge Computing: Offloading Optimization and Trajectory Designcited by 4

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