Robot operating system 2 navigation stack in action: automating a Caterpillar 621G for pavement testing

Collin Hays; Desmond Benton; Brian Robinson; Kevin Hall; Scott Craft; Rodney Wade; John Jetton; Caleb Spencer; Woody English; Robert Diltz

doi:10.1117/12.3013525

7 June 2024 Robot operating system 2 navigation stack in action: automating a Caterpillar 621G for pavement testing

Collin Hays, Desmond Benton, Brian Robinson, Kevin Hall, Scott Craft, Rodney Wade, John Jetton, Caleb Spencer, Woody English, Robert Diltz

Author Affiliations +

Proceedings Volume 13055, Unmanned Systems Technology XXVI; 1305502 (2024) https://doi.org/10.1117/12.3013525
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Pavements used for construction and repair of airfield surfaces must be rigorously tested before use in the field. This testing is typically accomplished by trafficking simulated aircraft landing gear payloads across an experimental pavement test patch and measuring deflection, cracking, and other effects on the pavement and aggregate subbase. The landing gear payload is heavily weighted to simulate the pressures of landing and taxiing, and a large tractor pulls the landing gear repeatedly over the test patch while executing an intricate trafficking pattern to distribute the load on the patch in the desired manner. In conventional testing, a human drives the test vehicle, called a load cart, forward and backward over the experimental patch up to about 1000 times while carefully following a set of closely spaced lane markings. This is a dull job that is ripe for automation. One year ago, at this conference, we presented results of kitting the load cart, consisting of the tractor from a Caterpillar 621G scraper and a custom trailer carrying the landing gear simulacrum, with a custom vehicle interface and bringing it under tele-operation. In this paper, we describe the results of fully automating the load cart pavements test vehicle using the Robot Operating System 2 Navigation Stack. The solutions works without GPS, line following, or external tracking systems and involves minimal modifications to the vehicle. Using lidar and Adaptive Monte Carlo localization, the team achieved better than 6" cross-track accuracy with a lumbering, 300,000-pound vehicle.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Collin Hays, Desmond Benton, Brian Robinson, Kevin Hall, Scott Craft, Rodney Wade, John Jetton, Caleb Spencer, Woody English, and Robert Diltz "Robot operating system 2 navigation stack in action: automating a Caterpillar 621G for pavement testing", Proc. SPIE 13055, Unmanned Systems Technology XXVI, 1305502 (7 June 2024); https://doi.org/10.1117/12.3013525

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