Large Language Model Driven Context-Aware Robotic Manipulation via Human Demonstration - Hossain, Iftekher (2025)
This thesis introduces a novel zero-shot adaptive imitation learning framework that facilitates the power of foundational models to enable robots to perform context-aware manipulation tasks only from passive video demonstrations. This architecture is inspired by the human cognitive adaptability metaphorically to extract the high-level knowledge from raw video demonstration and generate abstract symbolic knowledge representations without any robot-specific data. Additionally, this architecture demonstrates the versatile capabilities of foundational models in bridging perception, reasoning, and action in modern autonomous systems.