GAM: Ground the Target Before You Learn the Action
GAM is a robot foundation model that conditions action chunk prediction on 3D grounded inputs — including language, 3D point clouds, and bounding boxes — alongside robot history, achieving strong results on LIBERO benchmarks and real-robot tasks. The 3D grounding mechanism advances how embodied agents spatially understand and act in their environment. In this episode of Embodied AI 101, we explore "GAM: Ground the Target Before You Learn the Action". We break down the research, methodology, and real-world implications for robotics, AI, and physical intelligence. Embodied AI 101 covers the…
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