<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In the ever increasing number of robotic system applications in the industry, the robust and fast visual recognition and pose estimation of workpieces are of utmost importance. One of the ubiquitous tasks in industrial settings is the pick-and-place task where the object recognition is often important. In this paper, we present a new implementation of a work-piece sorting system using a template matching method for recognizing and estimating the position of planar workpieces with sparse visual features. The proposed framework is able to distinguish between the types of objects presented by the user and control a serial manipulator equipped with parallel finger gripper to grasp and sort them automatically. The system is furthermore enhanced with a feature that optimizes the visual processing time by automatically adjusting the template scales. We test the proposed system in a real-world setup equipped with a UR5 manipulator and provide experimental results documenting the performance of our approach.</p></abstract>

In the ever increasing number of robotic system applications in the industry, the robust and fast visual recognition and pose estimation of workpieces are of utmost importance. One of the ubiquitous tasks in industrial settings is the pick-and-place task where the object recognition is often important. In this paper, we present a new implementation of a work-piece sorting system using a template matching method for recognizing and estimating the position of planar workpieces with sparse visual features. The proposed framework is able to distinguish between the types of objects presented by the user and control a serial manipulator equipped with parallel finger gripper to grasp and sort them automatically. The system is furthermore enhanced with a feature that optimizes the visual processing time by automatically adjusting the template scales. We test the proposed system in a real-world setup equipped with a UR5 manipulator and provide experimental results documenting the performance of our approach.

Pick-and-Place Task Implementation Using Visual Open-Loop Control

Acta Mechanica et Automatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Pick-and-Place Task Implementation Using Visual Open-Loop Control"}

In the ever increasing number of robotic system applications in the industry, the robust and fast visual recognition and pose estimation of workpieces are of...

Pick-and-Place Task Implementation Using Visual Open-Loop Control

Online veröffentlicht: 05. Nov. 2019

Seitenbereich: 211 - 216

Eingereicht: 10. Juli 2019

Akzeptiert: 31. Okt. 2019

DOI: https://doi.org/10.2478/ama-2019-0028

Schlüsselwörter
Grasping, pick-and-place, object recognition, template matching, visual servoing

© 2019 Paweł Kołosowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Pick-and-Place Task Implementation Using Visual Open-Loop Control

Online veröffentlicht: 05. Nov. 2019

Seitenbereich: 211 - 216

Eingereicht: 10. Juli 2019

Akzeptiert: 31. Okt. 2019

DOI: https://doi.org/10.2478/ama-2019-0028

SchlüsselwörterGrasping, pick-and-place, object recognition, template matching, visual servoing

© 2019 Paweł Kołosowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Grasping, pick-and-place, object recognition, template matching, visual servoing