Reinforcement learning-based target grasping for low cost robotic arm - Yuan, Weibin (Nanyang Technological University, 2024)
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.