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Pig weight prediction system using RGB-D sensor and AR glasses: analysis method with free camera capture direction

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Abstract

Pig weights are important indicator for the healthcare and the economic operation of pig farms, and the development of a system to easily estimate these weights is desired. Although load cells are usually used for actual measurement in pig farms, it is not easy to guide pigs weighing more than 100 kg to the scales because many pigs do not like to get on the scales. Therefore, a convenient pig weight estimation system using RGB-D sensors has been developed. An RGB-D sensor (Intel Realsense D455) is used as the sensing device for weight estimation. Weight estimation is performed on 3D point cloud data of photographed pig images. When capturing pigs, it is desirable to have a constant camera orientation toward the pigs However, it is not easy to always capture from the same direction because pigs move around quickly in the piggery. A method with a high degree of freedom in the capture direction by exploiting pig symmetry of the pig’s body is introduced in this paper. The system is applied for a wearing device using AR (Augmented Reality) glasses. Experimental results show the feasibility of this system.

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Data availability

The datasets generated during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

All animal experiments were conducted in compliance with the protocol which was reviewed by the Institutional Animal Care and Use Committee and approved by the President of University of Miyazaki (Permit Number: 2017-021). This work was partially supported by JSPS KAKENHI Grant Number 20H03108. The staff of FEED ONE co. (Japan) and Big Dutchman (Germany) performed a great deal of work in collecting the training data and evaluating the device, and we thank them for their practical advice. We would like to express our gratitude to them.

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Authors and Affiliations

  1. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Kikuhito Kawasue, Pwint Phoo Wai, Khin Dagon Win & Geunho Lee

  2. Miyazaki Prefecture Livestock Research Institute, Kawaminami, Japan

    Yusuke Iki

Authors
  1. Kikuhito Kawasue
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  2. Pwint Phoo Wai
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  3. Khin Dagon Win
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  4. Geunho Lee
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  5. Yusuke Iki
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Correspondence to Kikuhito Kawasue.

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This work was submitted and accepted for the Journal Track of the joint symposium of the 28th International Symposium on Artificial Life and Robotics, the 8th International Symposium on BioComplexity, and the 6th International Symposium on Swarm Behavior and Bio-Inspired Robotics (Beppu, Oita, January 25–27, 2023).

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Kawasue, K., Wai, P.P., Win, K.D. et al. Pig weight prediction system using RGB-D sensor and AR glasses: analysis method with free camera capture direction. Artif Life Robotics 28, 89–95 (2023). https://doi.org/10.1007/s10015-022-00827-x

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  • DOI: https://doi.org/10.1007/s10015-022-00827-x

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