A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in Laboratories
This paper presents a fast approach to organizing arm grasping and placing manipulations for mobile robot transportation systems in life science laboratories. The approach builds a blind framework to realize the robot arm operations without integrating any other sensors or recognizing computation, b...
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2014-03-01
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Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.5772/58253 |
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doaj-9bc6e892f90f4860b19c1e9ede11ffd72020-11-25T04:01:11ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142014-03-011110.5772/5825310.5772_58253A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in LaboratoriesHui Liu0Norbert Stoll1Steffen Junginger2Kerstin Thurow3 Institute of Automation, University of Rostock, Germany Center for Life Science Automation, Germany Institute of Automation, University of Rostock, Germany Center for Life Science Automation, GermanyThis paper presents a fast approach to organizing arm grasping and placing manipulations for mobile robot transportation systems in life science laboratories. The approach builds a blind framework to realize the robot arm operations without integrating any other sensors or recognizing computation, but only adopting the robot's existing on-board ultrasonic sensors originally installed for collision avoidance. To achieve high-precision indoor positioning performance for the proposed blind arm strategy, a hybrid method is proposed, including a StarGazer system for all laboratory environments and an ultrasonic sensor-based component for the local areas where the arm operations are expected. At the same time, two error-correcting algorithms are presented for the improvement of the high-precision localization and the selection of the robot arm operations. In addition, the architecture of all the robotic controlling centres and their key APIs are also explained. Finally, an experiment proves that the proposed blind strategy is effective and economically viable for the laboratory automation.https://doi.org/10.5772/58253 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hui Liu Norbert Stoll Steffen Junginger Kerstin Thurow |
spellingShingle |
Hui Liu Norbert Stoll Steffen Junginger Kerstin Thurow A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in Laboratories International Journal of Advanced Robotic Systems |
author_facet |
Hui Liu Norbert Stoll Steffen Junginger Kerstin Thurow |
author_sort |
Hui Liu |
title |
A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in Laboratories |
title_short |
A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in Laboratories |
title_full |
A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in Laboratories |
title_fullStr |
A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in Laboratories |
title_full_unstemmed |
A Fast Approach to Arm Blind Grasping and Placing for Mobile Robot Transportation in Laboratories |
title_sort |
fast approach to arm blind grasping and placing for mobile robot transportation in laboratories |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2014-03-01 |
description |
This paper presents a fast approach to organizing arm grasping and placing manipulations for mobile robot transportation systems in life science laboratories. The approach builds a blind framework to realize the robot arm operations without integrating any other sensors or recognizing computation, but only adopting the robot's existing on-board ultrasonic sensors originally installed for collision avoidance. To achieve high-precision indoor positioning performance for the proposed blind arm strategy, a hybrid method is proposed, including a StarGazer system for all laboratory environments and an ultrasonic sensor-based component for the local areas where the arm operations are expected. At the same time, two error-correcting algorithms are presented for the improvement of the high-precision localization and the selection of the robot arm operations. In addition, the architecture of all the robotic controlling centres and their key APIs are also explained. Finally, an experiment proves that the proposed blind strategy is effective and economically viable for the laboratory automation. |
url |
https://doi.org/10.5772/58253 |
work_keys_str_mv |
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