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JRM Vol.37 No.1 pp. 191-202
doi: 10.20965/jrm.2025.p0191
(2025)

Paper:

Relative Posture Estimation of Multiple Linked Omni-Directional Mobile Robots Using Only Wheel Encoders and Passive Movements

Ryoma Sakata*, Jumpei Takemoto**, and Takashi Tsubouchi*

*Degree Programs in Systems and Information Engineering, Graduate School of Science and Technology, University of Tsukuba
1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan

**Kandenko Company
4-8-33 Shibaura, Minato-ku, Tokyo 108-8533, Japan

Received:
June 27, 2024
Accepted:
October 8, 2024
Published:
February 20, 2025
Keywords:
omni-directional mobile robot, multi robots, wheel encoder, cooperative transportation
Abstract

This study addressed the problem of estimating the relative postures of two robots constrained by materials. The constrained robots were passively guided by human operators, and the relative postures were estimated using only encoder information from the wheels of each robot. This method relies solely on the encoder information and does not utilize additional sensors for relative posture estimation. A significant advantage of this method is cost-effectiveness and reduced maintenance requirements, as the robots do not need to be equipped with multiple types of sensors. The motivation for this research was to enable multiple omni-directional mobile robots to collaboratively transport long objects in confined spaces, such as those found at construction sites. Experimental results demonstrate that the relative distance between two robots can be estimated with an error of approximately 2%, and the relative posture with an error of approximately 2°. These results represent a notable improvement in the measurement accuracy compared to those obtained previously by the authors.

The operation of relative posture estimation

The operation of relative posture estimation

Cite this article as:
R. Sakata, J. Takemoto, and T. Tsubouchi, “Relative Posture Estimation of Multiple Linked Omni-Directional Mobile Robots Using Only Wheel Encoders and Passive Movements,” J. Robot. Mechatron., Vol.37 No.1, pp. 191-202, 2025.
Data files:
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Last updated on Mar. 04, 2025