Physical Task

Research on physical tasks focuses on enabling robots and AI systems to perform complex, physically interactive actions, mirroring human dexterity and adaptability. Current efforts concentrate on developing physics-informed planning frameworks, often incorporating neural networks (like PINNs) and tree search algorithms (like MCTS), to improve efficiency and generalization in learning and executing these tasks. This research is significant for advancing robotics, AI-assisted education, and assistive technologies, particularly for visually impaired individuals, by creating more robust and adaptable systems capable of handling real-world uncertainties and complexities. Furthermore, the development of effective methods for generating and evaluating reward functions for physical skills is a key area of focus.