Robot Software & Simulation

Caltech, Stanford unveil HomeBody system to give GPT Astra spatial memory for humanoid robots - RobotHOT

Caltech, Stanford unveil HomeBody system to give GPT Astra spatial memory for humanoid robots

Researchers at Caltech and Stanford have unveiled HomeBody, a system that gives GPT Astra persistent spatial memory and the ability to execute compound humanoid actions for long-horizon tasks. In a kitchen demo, a Unitree G1 robot guided by Astra cleaned the room and retrieved remembered items from ambiguous requests. The team said the system requires no environment-specific training or additional policy learning. HomeBody replaces the trained intermediate VLA layer in conventional three-part architectures—System2 VLM for vision and instructions, System1 VLA for control commands, and System0 for coordinated motion. As frontier models such as Astra improve, the researchers argue trained VLAs are no longer necessary and System2 can directly manage reusable motion skills. A plug-and-play VLM calls a composable skill library....

ACE ROBOTICS open-sources ACE-Ego-Hand for 3D hand reconstruction from egocentric video, claims 45 benchmark wins - RobotHOT

ACE ROBOTICS open-sources ACE-Ego-Hand for 3D hand reconstruction from egocentric video, claims 45 benchmark wins

ACE ROBOTICS, in collaboration with the Chinese University of Hong Kong’s Multimedia Laboratory and Nanyang Technological University, has open-sourced ACE-Ego-Hand, a 3D dual-hand shape reconstruction model designed for first-person video, generating approximately 5,000 hours of training data that could serve as a foundational dataset for embodied AI model training. The model extracts structured 3D bimanual manipulation trajectories from massive egocentric video footage, translating human grasping, assembly and hand-coordination actions into machine-learnable data. It marks the first time a video generation model has been repurposed as a DreamHand encoder for end-to-end training, outputting hand pose, shape and 3D position in a single forward pass without frame-by-frame detection or temporal regression. Efficiency gains over traditional approaches Unlike previous hand models reliant on...

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