Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Analysis of Automatic through Autonomous – Unmanned Ground Vehicles (A-UGVs) Towards Performance Standards

Published

Author(s)

Soocheol Yoon, Roger V. Bostelman

Abstract

Automatic through Autonomous - Unmanned Ground Vehicles (A-UGVs), as termed by ASTM F45 for driverless industrial vehicles, have much potential for use in manufacturing operations thanks to these vehicle's versatility and flexibility. To utilize A-UGVs efficiently and effectively, it is needed to specify how the vehicle will be used, in what environment, and how best to control it. By understanding the detailed performance of the A-UGV and the facility environment, the vehicle can potentially operate with maximized productivity. In this paper, various parameters of the A-UGV are analyzed to measure navigation and obstacle avoidance performance. A-UGV aspects related to various facility environments are defined in structural form with organic relations. Performance test methods were developed and verified in a mock facility environment combining ramps and obstacles to measure navigation and obstacle avoidance performance.
Proceedings Title
2019 IEEE International Symposium on RObotic and SEnsors Environments (ROSE). ROSE 2019
Conference Dates
June 17-18, 2019
Conference Location
Ottawa, Ontario, CA

Keywords

Automatic through Autonomous – Unmanned Ground Vehicles (A-UGVs), vehicle environment, vehicle performance, test methods

Citation

Yoon, S. and Bostelman, R. (2019), Analysis of Automatic through Autonomous – Unmanned Ground Vehicles (A-UGVs) Towards Performance Standards, 2019 IEEE International Symposium on RObotic and SEnsors Environments (ROSE). ROSE 2019, Ottawa, Ontario, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927496 (Accessed April 26, 2024)
Created July 17, 2019, Updated April 14, 2022