Cooperative Payload Estimation by a Team of Mocobots

For high-performance autonomous manipulation of a payload by a mobile manipulator team, or for collaborative manipulation with the human, robots should be able to discover where other robots are attached to the payload, as well as the payload's mass and inertial properties. In this paper, we describe a method for the robots to autonomously discover this information. The robots cooperatively manipulate the payload, and the twist, twist derivative, and wrench data at their grasp frames are used to estimate the transformation matrices between the grasp frames, the location of the payload's center of mass, and the payload's inertia matrix. The method is validated experimentally with a team of three mobile cobots, or mocobots.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-08-11
DOI
https://doi.org/10.1109/lra.2025.3597893
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

Cooperative Payload Estimation by a Team of Mocobots

H. Zhang, Matthew L. Elwin, Kevin Lynch, Cindy Liu et al.
IEEE Robotics and Automation Letters
Robotic Path Planning Algorithms
article

Cooperative Payload Estimation by a Team of Mocobots

H. Zhang, Matthew L. Elwin, Kevin Lynch, Cindy Liu, Randy A. Freeman
article en

Abstract

For high-performance autonomous manipulation of a payload by a mobile manipulator team, or for collaborative manipulation with the human, robots should be able to discover where other robots are attached to the payload, as well as the payload's mass and inertial properties. In this paper, we describe a method for the robots to autonomously discover this information. The robots cooperatively manipulate the payload, and the twist, twist derivative, and wrench data at their grasp frames are used to estimate the transformation matrices between the grasp frames, the location of the payload's center of mass, and the payload's inertia matrix. The method is validated experimentally with a team of three mobile cobots, or mocobots.

IEEE Robotics and Automation LettersVol. 10(10)
Northwestern University (US)
Openalex Percentile: Top 81%
Robotic Path Planning Algorithms
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