Towards a Cerebrum-Cerebellum Collaboration Framework for Large Embodied Models

Location: Junior Stage

Recent advances in large-scale multimodal models have significantly enhanced embodied AI systems, enabling more natural and adaptive interactions with the physical world. However, current models and frameworks often struggle with spatial-temporal perception, real-time and precise collabration. Inspired by the biological synergy between the cerebrum and cerebellum, we propose a novel collaboration framework that integrates high-level cognitive reasoning with fast, low-latency sensorimotor adaptations. This talk explores how this framework can improve planning, error correction, and robustness in embodied AI. We will discuss model architectures, training strategies, and applications in robotic manipulation and human-robot interaction, paving the way for more agile and intelligent embodied systems.