Shimin Liu

Multimodal Autonomous Robotic Long-Horizon Task Planning via Embodied Language Model and Behavior Trees

Enabling robotic systems to perform long-horizon manipulation planning in real-world environments based on multimodal embodied perception and comprehension remains a longstanding challenge. Recent advancements in large language models (LLMs) have spurred the development of LLM-based planners; howeve