Behavior imitation for manipulator control and grasping with deep reinforcement learning

Behavior imitation for manipulator control and grasping with deep reinforcement learning

The existing Motion Imitation models typically require expert data obtained through MoCap devices, but the vast amount of training data needed is difficult to acquire, necessitating substantial investments of financial resources, manpower, and time. This project combines 3D human pose estimation...

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Bibliographic Details
Main Author: Liu, Qiyuan
Other Authors: Lyu Chen
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Engineering
Motion Imitation, Imitation Learning, Deep Reinforcement Learning, 3D Human Pose Estimation, Motion Retargeting, Inverse Kenimatics, PyBullet Simulation
Online Access:https://hdl.handle.net/10356/177492

Internet

https://hdl.handle.net/10356/177492

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