Occlusion alleviation through motion using a mobile robot

Duc Fehr; William J. Beksi; Dimitris Zermas; Nikolaos P Papanikolopoulos

doi:10.1109/ICRA.2014.6907316

Occlusion alleviation through motion using a mobile robot

Duc Fehr, William J. Beksi, Dimitris Zermas, Nikolaos P Papanikolopoulos

Computer Science and Engineering

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Object segmentation and classification is an important and difficult task in robotic vision. The task is complicated even further when the different objects are partially or completely occluded. Allowing a robot to take measurements from varying points of view can help in alleviating or completely removing occlusions. A robot equipped with an RGB-D sensor has the capability of searching for new and better points of view to facilitate object recognition. In this work, a motion control algorithm is designed and implemented on a mobile robot to facilitate object classification in RGB-D data of clustered objects.

Original language	English (US)
Article number	6907316
Pages (from-to)	3179-3184
Number of pages	6
Journal	Proceedings - IEEE International Conference on Robotics and Automation
DOIs	https://doi.org/10.1109/ICRA.2014.6907316
State	Published - Sep 22 2014
Event	2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China Duration: May 31 2014 → Jun 7 2014

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title = "Occlusion alleviation through motion using a mobile robot",

abstract = "Object segmentation and classification is an important and difficult task in robotic vision. The task is complicated even further when the different objects are partially or completely occluded. Allowing a robot to take measurements from varying points of view can help in alleviating or completely removing occlusions. A robot equipped with an RGB-D sensor has the capability of searching for new and better points of view to facilitate object recognition. In this work, a motion control algorithm is designed and implemented on a mobile robot to facilitate object classification in RGB-D data of clustered objects.",

author = "Duc Fehr and Beksi, {William J.} and Dimitris Zermas and Papanikolopoulos, {Nikolaos P}",

year = "2014",

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journal = "Proceedings - IEEE International Conference on Robotics and Automation",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2014 IEEE International Conference on Robotics and Automation, ICRA 2014 ; Conference date: 31-05-2014 Through 07-06-2014",

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AU - Fehr, Duc

AU - Beksi, William J.

AU - Zermas, Dimitris

AU - Papanikolopoulos, Nikolaos P

PY - 2014/9/22

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N2 - Object segmentation and classification is an important and difficult task in robotic vision. The task is complicated even further when the different objects are partially or completely occluded. Allowing a robot to take measurements from varying points of view can help in alleviating or completely removing occlusions. A robot equipped with an RGB-D sensor has the capability of searching for new and better points of view to facilitate object recognition. In this work, a motion control algorithm is designed and implemented on a mobile robot to facilitate object classification in RGB-D data of clustered objects.

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