機械知覚&ロボティクスグループ
中部大学

Deep Learning Robotics Object Detection 学術論文(J)

挟持グリッパをベースとした混載商品を識別するピッキングロボットの開発

Author
堂前幸康, 川西亮輔, 白土浩司, 原口林太郎, 藤田正弘, 山内悠嗣, 山下隆義, 藤吉弘亘, 秋月秀一, 橋本学
Publication
日本ロボット学会誌, vol. 38, no. 1, pp. 95–103, 2020.

Download: PDF (Japanese)

We proposed a picking robot system which is apllicable to various mixed items in shelves. The robot has a two-finger gripper which can change the open width of the finger. To determine the position, the pose and the open width when the gripper pick items, we proposed efficient determination algorithm which is based on a RGBD sensor data. In our experiments, 25 items of Amazon Picking Challenge 2015 can be picked well by our proposed system. In this paper, we describe the system, the algorithms and the experimental results.

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