Episode Details

Vision-language-action (VLA) models predict robot actions from visual observations and language instructions. These actions are defined in the robot's own 3D coordinate frame, yet most VLAs observe the scene in 2D. This paper proposes robot-centric pointmaps to bridge this gap for vision-language-action models. In this episode of Embodied AI 101, we explore "Stop Teaching the VLA Your Camera: Robot-Centric Pointmaps as an Action-Aligned Visual Interface". We break down the research, methodology, and real-world implications for robotics, AI, and physical intelligence. Embodied AI 101 covers the latest research at the intersection of AI and physical intelligence — robotics, manipulation, world models, and the path from digital intelligence to embodied agents.