Parts picking in disordered environment

Yanagihara, Yoshimasa; Kita, Toshiyuki

doi:10.1109/iros.1991.174524

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…For this reason, companies spend much money on regular quality checks for their products and manufacturing pipelines. Force/torque sensors have been used several times to detect if pick-and-place operations were successful [14][15][16]. Moreira et al focused on picking a set of entangled flexible tubes from a vehicle's air conditioning system [15].…”

Section: Related Workmentioning

confidence: 99%

Detecting and Solving Tube Entanglement in Bin Picking Operations

et al. 2020

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Manufacturing and production industries are increasingly turning to robots to carry out repetitive picking operations in an efficient manner. This paper focuses on tackling the novel challenge of automating the bin picking process for entangled objects, for which there is very little research. The chosen case study are sets of freely curved tubes, which are prone to occlusions and entanglement. The proposed algorithm builds a representation of the tubes as an ordered list of cylinders and joints using a point cloud acquired by a 3D scanner. This representation enables the detection of occlusions in the tubes. The solution also performs grasp planning and motion planning, by evaluating post-grasp trajectories via simulation using Gazebo and the ODE physics engine. A force/torque sensor is used to determine how many items were picked by a robot gripper and in which direction it should rotate to solve cases of entanglement. Real-life experiments with sets of PVC tubes and rubber radiator hoses showed that the robot was able to pick a single tube on the first try with success rates of 99% and 93%, respectively. This study indicates that using simulation for motion planning is a promising solution to deal with entangled objects.

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Section: Related Workmentioning

confidence: 99%

Detecting and Solving Tube Entanglement in Bin Picking Operations

et al. 2020

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“…There has been many efforts in developing bin picking technology [1] [2]. Much of the existing work is not applicable to most real world bin picking problems because they are too simplistic or not robust enough for industrial use.…”

Section: Introductionmentioning

confidence: 99%

Automated 3D vision guided bin picking process for randomly located industrial parts

Martínez¹,

Chen

Boca³

2015

2015 IEEE International Conference on Industrial Technology (ICIT)

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Bin picking has been a research topic for years because of the challenges in image processing, robot motion planning and tool system. However, much of the existing work is not applicable to most real world bin picking problems because they are too simplistic or not robust enough for industrial use. In this paper, we developed a robust random 3D bin picking system by integrating the vision system with the robotics system. The vision system identifies the location of candidate parts, then the robot system validates if one of the candidate parts is pickable; if a part is identified as pickable, then the robot will pick up this part and place it accurately in the right location. An ABB IRB2400 robot with an IRC5 controller was chosen for picking up the parts. A 3D vision system was used to locate the parts. Experimental results demonstrated that the system can successfully pick up randomly placed parts in an industrial setting. This system provides a practical and robust solution for the industrial applications that require 3D random bin picking.

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“…In recent years, much work have been reported on recognition of objects for the bin picking problem. Some concepts are limited to recognition of the objects while others concentrate on picking an object and analyzing the object for pose determination and recognition using database of the object images [1], [2], [3]. Stereo based approaches have been reported by some researchers; Rahardja and Kosaka [4] have developed an effective stereo based algorithm to find simple visual clues of complex objects, however the system requires human intervention for grasping tasks.…”

Section: Introductionmentioning

confidence: 99%

Stereo Vision System for A Bin Picking Adept Robot

Radhakrishnamurthy

Murugesapandian

Ramachandran

et al. 2007

MJCS

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In bin picking applications, robots are required to pick up an object from a pile of stacked or scattered objects placed in a bin. To perform such tasks, identification of the objects to be picked using a vision system is indispensable. In this paper, a stereo vision based automated bin picking system is proposed which identifies the topmost object from a pile of occluded objects and computes its location. The proposed bin picking process consists of two modules namely object segmentation module and object localization module. In the segmentation module, an 'Acclimatized Top Object Threshold' [ATOT] algorithm is proposed for segmentation of topmost object and in the localization module, the location of the object is estimated by computing the 'x', 'y', 'z' coordinates of the object midpoint using a unified stereo imaging algorithm. The validity of the algorithms is experimentally verified for object pick and place operations using the object location coordinates. The developed stereo vision system was implemented and validated for bin pick and place operations on an Adept Cobra 600 Robot.

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Parts picking in disordered environment

Cited by 7 publications

References 10 publications

Detecting and Solving Tube Entanglement in Bin Picking Operations

Detecting and Solving Tube Entanglement in Bin Picking Operations

Automated 3D vision guided bin picking process for randomly located industrial parts

Stereo Vision System for A Bin Picking Adept Robot

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