Development of a Hand-Eye System for Random Picking Tasks

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  • Nishi Takao
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Okano Hitoshi
    Hiroshima Prefectural Technology Research Institute
  • Harada Yuji
    Hirotec Corporation
  • Yoshimi Takashi
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Harada Kensuke
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Kita Yasuyo
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Nagata Kazuyuki
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Yamanobe Natsuki
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Ueshiba Toshio
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Satoh Yutaka
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Masuda Takeshi
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Takase Ryuichi
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Nagami Takeshi
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Kawai Yoshihiro
    National Institute of Advanced Industrial Science and Technology (AIST)
  • Nakamura Osamu
    National Institute of Advanced Industrial Science and Technology (AIST)

Bibliographic Information

Other Title
  • ビンピッキング用ハンドアイシステムの開発
  • ビンピッキング用ハンドアイシステムの開発 : バラ積み物体位置姿勢推定アルゴリズムの評価手法
  • ビンピッキングヨウ ハンドアイ システム ノ カイハツ : バラズミ ブッタイ イチ シセイ スイテイ アルゴリズム ノ ヒョウカ シュホウ
  • — バラ積み物体位置姿勢推定アルゴリズムの評価手法 —
  • — Evaluation of Position and Pose Estimating Algorithm for Randomly Stacked Objects —

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Abstract

In this paper, we introduce the bin-picking robot system we developed for the manufacturing industry. The system, that is composed of RGB-D cameras and a dual-arm robot, should locate the target object inside a bin, pick it, and place it onto the assembly jig. As target objects, three types of pipes and two types of flat plates (all of them made of metal) were used. To estimate the position and pose of an object inside the bin, the depth image captured by the RGB-D camera is used. And we describe three evaluation methods; accuracy, reproducibility and availability, those applied for an object's position and pose estimation algorithm, too. The accuracy and the reproducibility of the estimation are evaluated using an XYθ stage. The object is transferred in X and Y directions and rotated about Z axis using the stage, and the estimated transfer matrix of each location is compared to the real one. The availability for the estimation algorithm is measured by simulating the manipulation task with human operation. The results of the estimation agree with the manipulation experiments performed on the robot.

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