Reinforcement learning-based target grasping for low cost robotic arm
This dissertation focuses on grasping targets by robotic arms based on deep reinforcement learning. Theoretically, it goes into the application of the most advanced algorithms of reinforcement learning, particularly the Soft Actor-Critic algorithm. It will choose Stable Baselines3 for many advant...
محفوظ في:
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| التنسيق: | Thesis-Master by Coursework |
| اللغة: | English |
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Nanyang Technological University
2024
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| الوصول للمادة أونلاين: | https://hdl.handle.net/10356/180764 |
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sg-ntu-dr.10356-1807642024-10-25T15:45:38Z Reinforcement learning-based target grasping for low cost robotic arm Yuan, Weibin Wen Bihan School of Electrical and Electronic Engineering bihan.wen@ntu.edu.sg Computer and Information Science Engineering This dissertation focuses on grasping targets by robotic arms based on deep reinforcement learning. Theoretically, it goes into the application of the most advanced algorithms of reinforcement learning, particularly the Soft Actor-Critic algorithm. It will choose Stable Baselines3 for many advantages: verified set of algorithms, compatibility with PyTorch, and community support. The study has also been conducted with detailed analysis in terms of the structure of the robotic arm through juxtaposition of traditional control methods against reinforcement learning algorithms to gain a deeper understanding as to the various ways of controlling a robotic arm. Master's degree 2024-10-23T04:22:29Z 2024-10-23T04:22:29Z 2024 Thesis-Master by Coursework Yuan, W. (2024). Reinforcement learning-based target grasping for low cost robotic arm. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/180764 https://hdl.handle.net/10356/180764 en 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 |
Computer and Information Science Engineering |
| spellingShingle |
Computer and Information Science Engineering Yuan, Weibin Reinforcement learning-based target grasping for low cost robotic arm |
| description |
This dissertation focuses on grasping targets by robotic arms based on deep
reinforcement learning. Theoretically, it goes into the application of the most
advanced algorithms of reinforcement learning, particularly the Soft Actor-Critic
algorithm. It will choose Stable Baselines3 for many advantages: verified set
of algorithms, compatibility with PyTorch, and community support. The study
has also been conducted with detailed analysis in terms of the structure of the
robotic arm through juxtaposition of traditional control methods against reinforcement
learning algorithms to gain a deeper understanding as to the various
ways of controlling a robotic arm. |
| author2 |
Wen Bihan |
| author_facet |
Wen Bihan Yuan, Weibin |
| format |
Thesis-Master by Coursework |
| author |
Yuan, Weibin |
| author_sort |
Yuan, Weibin |
| title |
Reinforcement learning-based target grasping for low cost robotic arm |
| title_short |
Reinforcement learning-based target grasping for low cost robotic arm |
| title_full |
Reinforcement learning-based target grasping for low cost robotic arm |
| title_fullStr |
Reinforcement learning-based target grasping for low cost robotic arm |
| title_full_unstemmed |
Reinforcement learning-based target grasping for low cost robotic arm |
| title_sort |
reinforcement learning-based target grasping for low cost robotic arm |
| publisher |
Nanyang Technological University |
| publishDate |
2024 |
| url |
https://hdl.handle.net/10356/180764 |
| _version_ |
1814777794373091328 |