Paper
22 December 2022 3D object recognition for coordination-less bin-picking automation
Shin Ishiyama, Huimin Lu
Author Affiliations +
Proceedings Volume 12508, International Symposium on Artificial Intelligence and Robotics 2022; 125080M (2022) https://doi.org/10.1117/12.2663323
Event: Seventh International Symposium on Artificial Intelligence and Robotics 2022, 2022, Shanghai, China
Abstract
At present, industrial robots are required to support high-mix low-volume production, which calls for automation and flexibility in production lines. To realize these requirements, it is necessary that automate of bin picking. In this work, we propose a three-dimensional object recognition using deep learning to automate coordination-less bin picking. The deep learning-based method requires the use of training data, but it has the higher cost of annotating the training data. Therefore, we construct a coordination-less recognition model by using the automatic acquisition method for training data in a simulation environment. For the evaluation, we conducted experiments in a simulation and real environment to verify the accuracy of the proposed method.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shin Ishiyama and Huimin Lu "3D object recognition for coordination-less bin-picking automation", Proc. SPIE 12508, International Symposium on Artificial Intelligence and Robotics 2022, 125080M (22 December 2022); https://doi.org/10.1117/12.2663323
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KEYWORDS
3D modeling

Data modeling

Clouds

3D image processing

Object recognition

Environmental sensing

Robots

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