Paper Info
Title
Object Singulation By Nonlinear Pushing For Robotic Grasping
Abstract
In this study, we aim at grasping a single target object in a cluttered environment using a robotic arm. While dexterous grasp for various shapes of objects is not considered in this work, we focus on developing the method to mitigate clutter near the target object as soon as quickly. For this purpose, we propose a method to generate nonlinear pushing motions for object singulation based on an off-the-shelf machine learning algorithm and a typical semantic segmentation algorithm. Through experiments, we show that the success rate of robotic grasping is considerably improved by the proposed pushing behavior. And notably, the nonlinear pushing trajectories allows the robot to perform singulation of the target object in a cluttered environment with fewer trials than linear pushing usually pursued in related works.
Year
DOI
Venue
2019
10.1109/IROS40897.2019.8968077
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Field
DocType
ISSN
Computer vision,Robotic arm,Nonlinear system,GRASP,Clutter,Computer science,Segmentation,Artificial intelligence,Robot
Conference
2153-0858
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Jongsoon Won100.34
Youngbin Park245.85
Byung-Ju Yi344474.48
Il Hong Suh4780110.60