Integrating force-based manipulation primitives with deep visual servoing for robotic assembly
This paper explores the idea of combining Deep Learning-based Visual Servoing and dynamic sequences of force-based Manipulation Primitives for robotic assembly tasks. Most current peg-in-hole algorithms assume the initial peg pose is already aligned within a minute deviation range before a tight-cle...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/157880 |
| _version_ | 1826119863499751424 |
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| author | Lee, Yee Sien |
| author2 | Pham Quang Cuong |
| author_facet | Pham Quang Cuong Lee, Yee Sien |
| author_sort | Lee, Yee Sien |
| collection | NTU |
| description | This paper explores the idea of combining Deep Learning-based Visual Servoing and dynamic sequences of force-based Manipulation Primitives for robotic assembly tasks. Most current peg-in-hole algorithms assume the initial peg pose is already aligned within a minute deviation range before a tight-clearance insertion is attempted. With the integration of tactile and visual information, highly-accurate peg alignment before insertion can be achieved autonomously. In the alignment phase, the peg mounted on the end-effector can be aligned automatically from an initial pose with large displacement errors to an estimated insertion pose with errors lower than 1.5 mm in translation and 1.5° in rotation, all in one-shot Deep Learning-Based Visual Servoing estimation. If using solely Deep Learning-based Visual Servoing is not able to complete the peg-in-hole insertion, a dynamic sequence of Manipulation Primitives will then be automatically generated via Reinforcement Learning to fnish the last stage of insertion. |
| first_indexed | 2024-10-01T05:07:04Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/157880 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:07:04Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1578802023-03-04T20:08:32Z Integrating force-based manipulation primitives with deep visual servoing for robotic assembly Lee, Yee Sien Pham Quang Cuong School of Mechanical and Aerospace Engineering cuong@ntu.edu.sg Engineering::Mechanical engineering::Robots This paper explores the idea of combining Deep Learning-based Visual Servoing and dynamic sequences of force-based Manipulation Primitives for robotic assembly tasks. Most current peg-in-hole algorithms assume the initial peg pose is already aligned within a minute deviation range before a tight-clearance insertion is attempted. With the integration of tactile and visual information, highly-accurate peg alignment before insertion can be achieved autonomously. In the alignment phase, the peg mounted on the end-effector can be aligned automatically from an initial pose with large displacement errors to an estimated insertion pose with errors lower than 1.5 mm in translation and 1.5° in rotation, all in one-shot Deep Learning-Based Visual Servoing estimation. If using solely Deep Learning-based Visual Servoing is not able to complete the peg-in-hole insertion, a dynamic sequence of Manipulation Primitives will then be automatically generated via Reinforcement Learning to fnish the last stage of insertion. Bachelor of Engineering (Mechanical Engineering) 2022-05-26T04:01:26Z 2022-05-26T04:01:26Z 2022 Final Year Project (FYP) Lee, Y. S. (2022). Integrating force-based manipulation primitives with deep visual servoing for robotic assembly. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157880 https://hdl.handle.net/10356/157880 en B171 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Mechanical engineering::Robots Lee, Yee Sien Integrating force-based manipulation primitives with deep visual servoing for robotic assembly |
| title | Integrating force-based manipulation primitives with deep visual servoing for robotic assembly |
| title_full | Integrating force-based manipulation primitives with deep visual servoing for robotic assembly |
| title_fullStr | Integrating force-based manipulation primitives with deep visual servoing for robotic assembly |
| title_full_unstemmed | Integrating force-based manipulation primitives with deep visual servoing for robotic assembly |
| title_short | Integrating force-based manipulation primitives with deep visual servoing for robotic assembly |
| title_sort | integrating force based manipulation primitives with deep visual servoing for robotic assembly |
| topic | Engineering::Mechanical engineering::Robots |
| url | https://hdl.handle.net/10356/157880 |
| work_keys_str_mv | AT leeyeesien integratingforcebasedmanipulationprimitiveswithdeepvisualservoingforroboticassembly |