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For mobile robots, mobile manipulators, and autonomous vehicles to safely navigate around populous places such as streets and warehouses, human observers must be able to understand their navigation intent. One way to enable such understanding is by visualizing this intent through projections onto the surrounding environment. But despite the demonstrated effectiveness of such projections, no open codebase with an integrated hardware setup exists. In this work, we detail the empirical evidence for the effectiveness of such directional projections, and share a robot-agnostic implementation of such projections, coded in C++ using the widely-used Robot Operating System (ROS) and rviz. Additionally, we demonstrate a hardware configuration for deploying this software, using a Fetch robot, and briefly summarize a full-scale user study that motivates this configuration. The code, configuration files (roslaunch and rviz files), and documentation are freely available on GitHub at https://github.com/umhan35/arrow_projection.
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Robofleet: Open Source Communication and Management for Fleets of Autonomous Robots
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 heterogenous 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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- Award ID(s):
- 2046955
- PAR ID:
- 10318550
- Date Published:
- Journal Name:
- 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IROS51168.2021.9635830
