Bimanual grasping

The current issue is that robots need to be pre-programmed for the specific task they are assigned to. The difficulty in describing a task formally, the high degree of variability and the time-consuming process required to program robots makes this approach less viable in today’s move towards smart...

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Main Author: Vadim, Koller
Other Authors: Domenico Campolo
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/150370
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1503702021-05-28T00:40:29Z Bimanual grasping Vadim, Koller Domenico Campolo School of Mechanical and Aerospace Engineering Robotics Research Centre d.campolo@ntu.edu.sg Engineering::Mechanical engineering The current issue is that robots need to be pre-programmed for the specific task they are assigned to. The difficulty in describing a task formally, the high degree of variability and the time-consuming process required to program robots makes this approach less viable in today’s move towards smart manufacturing. One solution is to allow robots to learn by demonstration. Learning by demonstration allows seamless transfer of information from the operator to the robot containing the proven and tested methods of carrying out a specific task. In the project, a direct control teleoperation system was set up to carry out the experiment. The experiment is composed of various sub-tasks such as reaching, moving, assembly, disassembly and rotating of a Tetris block. These sub-tasks are the building blocks of most assembly tasks found in the manufacturing sector. To ensure the accuracy of the experiment, a systematic robot calibration was conducted with the help of a motion-capture system. The object boundary was parametrised to evaluate the point of contact during the various sub-tasks to allow quantification of the grasp physical properties. MATLAB scripts were written to help bimanual grasping analysis and aid task visualisation. Contact between the end effector and object were determined using distance between proxies and force experienced at end effectors; grasp quality was inferred from the proxy velocity and slip analysis. Bachelor of Engineering (Mechanical Engineering) 2021-05-28T00:40:28Z 2021-05-28T00:40:28Z 2021 Final Year Project (FYP) Vadim, K. (2021). Bimanual grasping. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150370 https://hdl.handle.net/10356/150370 en A110 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
spellingShingle Engineering::Mechanical engineering
Vadim, Koller
Bimanual grasping
description The current issue is that robots need to be pre-programmed for the specific task they are assigned to. The difficulty in describing a task formally, the high degree of variability and the time-consuming process required to program robots makes this approach less viable in today’s move towards smart manufacturing. One solution is to allow robots to learn by demonstration. Learning by demonstration allows seamless transfer of information from the operator to the robot containing the proven and tested methods of carrying out a specific task. In the project, a direct control teleoperation system was set up to carry out the experiment. The experiment is composed of various sub-tasks such as reaching, moving, assembly, disassembly and rotating of a Tetris block. These sub-tasks are the building blocks of most assembly tasks found in the manufacturing sector. To ensure the accuracy of the experiment, a systematic robot calibration was conducted with the help of a motion-capture system. The object boundary was parametrised to evaluate the point of contact during the various sub-tasks to allow quantification of the grasp physical properties. MATLAB scripts were written to help bimanual grasping analysis and aid task visualisation. Contact between the end effector and object were determined using distance between proxies and force experienced at end effectors; grasp quality was inferred from the proxy velocity and slip analysis.
author2 Domenico Campolo
author_facet Domenico Campolo
Vadim, Koller
format Final Year Project
author Vadim, Koller
author_sort Vadim, Koller
title Bimanual grasping
title_short Bimanual grasping
title_full Bimanual grasping
title_fullStr Bimanual grasping
title_full_unstemmed Bimanual grasping
title_sort bimanual grasping
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/150370
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