Multi-Robot Data Gathering Under Buffer Constraints and Intermittent Communication
Meng Guo, Michael M. Zavlanos

TL;DR
This paper presents a distributed coordination approach for heterogeneous robots to gather data under buffer and intermittent communication constraints, ensuring task satisfaction without continuous connectivity.
Contribution
It introduces a novel distributed motion and communication scheme that guarantees local task fulfillment while managing buffer limits and limited communication range.
Findings
The method effectively coordinates robots to prevent buffer overflow.
It outperforms existing approaches requiring constant network connectivity.
Numerical simulations and experiments validate the approach's effectiveness.
Abstract
We consider a team of heterogeneous robots which are deployed within a common workspace to gather different types of data. The robots have different roles due to different capabilities: some gather data from the workspace (source robots) and others receive data from source robots and upload them to a data center (relay robots). The data-gathering tasks are specified locally to each source robot as high-level Linear Temporal Logic (LTL) formulas, that capture the different types of data that need to be gathered at different regions of interest. All robots have a limited buffer to store the data. Thus the data gathered by source robots should be transferred to relay robots before their buffers overflow, respecting at the same time limited communication range for all robots. The main contribution of this work is a distributed motion coordination and intermittent communication scheme that…
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Taxonomy
TopicsOpportunistic and Delay-Tolerant Networks · Distributed Control Multi-Agent Systems · Mobile Ad Hoc Networks
