Vision-Based Solutions for Robotic Manipulation and Navigation Applied to Object Picking and Distribution
Zusammenfassung
This paper presents a robotic demonstrator for manipulation and distribution of objects. The demonstrator relies on robust 3D vision-based solutions for navigation, object detection and detection of graspable surfaces using the rc _ visard , a self-registering stereo vision sensor. Suitable software modules were developed for SLAM and for model-free suction gripping. The modules run onboard the sensor, which enables creating the presented demonstrator as a standalone application that does not require an additional host PC. The modules are interfaced with ROS, which allows a quick implementation of a fully functional robotic application.
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Roa-Garzón, M. A., Gambaro, E. F., Florek-Jasinska, M., Endres, F., Ruess, F., Schaller, R., Emmerich, C., Muenster, K. & Suppa, M.,
(2019).
Vision-Based Solutions for Robotic Manipulation and Navigation Applied to Object Picking and Distribution.
KI - Künstliche Intelligenz: Vol. 33, No. 2.
Springer.
(S. 171-180).
DOI: 10.1007/s13218-019-00588-z
@article{mci/Roa-Garzón2019,
author = {Roa-Garzón, Máximo A. AND Gambaro, Elena F. AND Florek-Jasinska, Monika AND Endres, Felix AND Ruess, Felix AND Schaller, Raphael AND Emmerich, Christian AND Muenster, Korbinian AND Suppa, Michael},
title = {Vision-Based Solutions for Robotic Manipulation and Navigation Applied to Object Picking and Distribution},
journal = {KI - Künstliche Intelligenz},
volume = {33},
number = {2},
year = {2019},
,
pages = { 171-180 } ,
doi = { 10.1007/s13218-019-00588-z }
}
author = {Roa-Garzón, Máximo A. AND Gambaro, Elena F. AND Florek-Jasinska, Monika AND Endres, Felix AND Ruess, Felix AND Schaller, Raphael AND Emmerich, Christian AND Muenster, Korbinian AND Suppa, Michael},
title = {Vision-Based Solutions for Robotic Manipulation and Navigation Applied to Object Picking and Distribution},
journal = {KI - Künstliche Intelligenz},
volume = {33},
number = {2},
year = {2019},
,
pages = { 171-180 } ,
doi = { 10.1007/s13218-019-00588-z }
}
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Mehr Information
ISSN: 1610-1987
Datum: 2019
Typ: Text/Journal Article

