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

Paweł Kołosowski , Adam Wolniakowski , Mariusz Bogdan


AbstractIn 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.
Author Paweł Kołosowski (FME)
Paweł Kołosowski,,
- Faculty of Mechanical Engineering
, Adam Wolniakowski (FME / DACR)
Adam Wolniakowski,,
- Department of Automatic Control and Robotics
, Mariusz Bogdan (FME / DACR)
Mariusz Bogdan,,
- Department of Automatic Control and Robotics
Journal seriesActa Mechanica et Automatica, ISSN 1898-4088, e-ISSN 2300-5319, (N/A 40 pkt)
Issue year2019
Publication size in sheets0.5
Keywords in Englishgrasping, pick-and-place, object recognition, template matching, visual servoing
ASJC Classification2207 Control and Systems Engineering; 2210 Mechanical Engineering
URL http://www.acta.mechanica.pb.edu.pl/volume/vol13no3/28_2019_044_KOLOSOWSKI_WOLNIAKOWSKI_BOGDAN_AMA-D-19-00002.pdf
Internal identifierROC 19-20
Languageen angielski
LicenseJournal (articles only); published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)40
Score sourcejournalList
ScoreMinisterial score = 40.0, 17-02-2020, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.615
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