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Abstract
Gripper design process is one of the interesting challenges in the context of grasping within industry. Typically, simple parallel-finger grippers, which are easy to install and maintain, are used in platforms for robotic grasping. The context switches in these platforms require frequent exchange of gripper fingers to accommodate grasping of new products, while subjected to numerous constraints, such as workcell uncertainties due to the vision systems used. The design of these fingers consumes the man-hours of experienced engineers, and involves a lot of trial-and-error testing. In our previous work, we have presented a method to automatically compute the optimal finger shapes for defined task contexts in simulation. In this paper, we show the performance of our method in an industrial grasping scenario. We first analyze the uncertainties of the used vision system, which are the major source of grasping error. Then, we perform the experiments, both in simulation and in a real setting. The experiments confirmed the validity of our approach. The computed finger design was employed in a real industrial assembly scenario.
Original language | English |
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Title of host publication | IEEE International Conference on Simulation, Modelling, and Programming for Autonomous Robots (SIMPAR) |
Number of pages | 7 |
Publisher | IEEE |
Publication date | 23 Feb 2017 |
Pages | 177-184 |
ISBN (Print) | 978-1-5090-4617-1 |
ISBN (Electronic) | 978-1-5090-4616-4 |
DOIs | |
Publication status | Published - 23 Feb 2017 |
Event | IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots: Leveraging Simulation and Machine Learning for Robotics - The Parc 55, San Francisco, United States Duration: 13 Dec 2016 → 16 Dec 2016 Conference number: 5 http://simpar2016.org/ |
Conference
Conference | IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots |
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Number | 5 |
Location | The Parc 55 |
Country/Territory | United States |
City | San Francisco |
Period | 13/12/2016 → 16/12/2016 |
Internet address |
Keywords
- gripper optimization
- pose uncertainties
- Dynamic Simulation
- industrial assembly
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