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群制御arXiv:2103.06993

Robofleet:自律ロボット群のためのオープンソース通信・管理システム

Robofleet: Open Source Communication and Management for Fleets of Autonomous Robots

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複数ロボットと遠隔操作者間の通信・監視・タスク指示を、ネットワーク変動への耐性とセキュリティ制御を備えた軽量オープンソースシステムとして実現した。

著者: Kavan Singh Sikand, Logan Zartman, Sadegh Rabiee, Joydeep Biswas

分類: cs.RO

原文アブストラクト

Long-term deployment of a fleet of mobile robots requires reliable and secure two-way communication channels between individual robots and remote human operators for supervision and tasking. Existing open-source solutions to this problem degrade in performance in challenging real-world situations such as intermittent and low-bandwidth connectivity, do not provide security control options, and can be computationally expensive on hardware-constrained mobile robot platforms. In this paper, we present Robofleet, a lightweight open-source system which provides inter-robot communication, remote monitoring, and remote tasking for a fleet of ROS-enabled service-mobile robots that is designed with the practical goals of resilience to network variance and security control in mind. Robofleet supports multi-user, multi-robot communication via a central server. This architecture deduplicates network traffic between robots, significantly reducing overall network load when compared with native ROS communication. This server also functions as a single entrypoint into the system, enabling security control and user authentication. Individual robots run the lightweight Robofleet client, which is responsible for exchanging messages with the Robofleet server. It automatically adapts to adverse network conditions through backpressure monitoring as well as topic-level priority control, ensuring that safety-critical messages are successfully transmitted. Finally, the system includes a web-based visualization tool that can be run on any internet-connected, browser-enabled device to monitor and control the fleet. We compare Robofleet to existing methods of robotic communication, and demonstrate that it provides superior resilience to network variance while maintaining performance that exceeds that of widely-used systems.

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