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Main Authors: Krawciw, Alexander, Antonyshyn, Luka, Lilge, Sven, Olmedo, Nicolas, Rehmatullah, Faizan, Desjardins-Goulet, Maxime, Toupin, Pascal, Barfoot, Timothy D.
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2510.18766
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author Krawciw, Alexander
Antonyshyn, Luka
Lilge, Sven
Olmedo, Nicolas
Rehmatullah, Faizan
Desjardins-Goulet, Maxime
Toupin, Pascal
Barfoot, Timothy D.
author_facet Krawciw, Alexander
Antonyshyn, Luka
Lilge, Sven
Olmedo, Nicolas
Rehmatullah, Faizan
Desjardins-Goulet, Maxime
Toupin, Pascal
Barfoot, Timothy D.
contents A future lunar habitat, as part of the Artemis program, will require a significant amount of logistics infrastructure. Cargo that is transported to the Moon will need to be moved from a landing site to other key locations that may be up to 5 km away. Teach and repeat navigation is well suited to this task as utility rovers will need to repeat these cargo routes many times. One of the most significant challenges involves the modules that will be assembled together to form the habitat. Canada is studying potential Lunar Utility Vehicle (LUV) designs to carry these large payloads between the landing site and the location of the habitat. As the details of the cargo continue to evolve, using two, smaller LUVs to carry cargo together would provide high capacity and mission flexibility. In this paper, we develop and implement a distributed model-predictive controller that allows vehicles to carry cargo that is shared between them. The algorithm is compared to baselines in small-scale before being implemented onboard two 800 kg path-to-flight rovers and field tested carrying a 475 kg cargo between them. A custom cargo coupling decouples the kinematics of each vehicle while fully supporting the cargo's mass. In our field test, the rovers maintain a relative separation error of 9.2 cm and maximum error of 33.4 cm. This multi-vehicle control architecture retains the high-quality path tracking of lidar teach and repeat for each rover. We demonstrate that kinematic freedom of the vehicles allows a single controller to provide mission improvements for other operations as well.
format Preprint
id arxiv_https___arxiv_org_abs_2510_18766
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Sharing the Load: Autonomous Multi-Rover Cargo Transport
Krawciw, Alexander
Antonyshyn, Luka
Lilge, Sven
Olmedo, Nicolas
Rehmatullah, Faizan
Desjardins-Goulet, Maxime
Toupin, Pascal
Barfoot, Timothy D.
Robotics
A future lunar habitat, as part of the Artemis program, will require a significant amount of logistics infrastructure. Cargo that is transported to the Moon will need to be moved from a landing site to other key locations that may be up to 5 km away. Teach and repeat navigation is well suited to this task as utility rovers will need to repeat these cargo routes many times. One of the most significant challenges involves the modules that will be assembled together to form the habitat. Canada is studying potential Lunar Utility Vehicle (LUV) designs to carry these large payloads between the landing site and the location of the habitat. As the details of the cargo continue to evolve, using two, smaller LUVs to carry cargo together would provide high capacity and mission flexibility. In this paper, we develop and implement a distributed model-predictive controller that allows vehicles to carry cargo that is shared between them. The algorithm is compared to baselines in small-scale before being implemented onboard two 800 kg path-to-flight rovers and field tested carrying a 475 kg cargo between them. A custom cargo coupling decouples the kinematics of each vehicle while fully supporting the cargo's mass. In our field test, the rovers maintain a relative separation error of 9.2 cm and maximum error of 33.4 cm. This multi-vehicle control architecture retains the high-quality path tracking of lidar teach and repeat for each rover. We demonstrate that kinematic freedom of the vehicles allows a single controller to provide mission improvements for other operations as well.
title Sharing the Load: Autonomous Multi-Rover Cargo Transport
topic Robotics
url https://arxiv.org/abs/2510.18766