Download this complimentary White Paper today! This White Paper gives robotics researchers and engineers an overview of a new large-scale motion capture dataset built to close the data gap limiting humanoid robot learning. It also shows how policies trained on the dataset transfer to a real humanoid robot.   What you will learn about:  Why humanoid robot learning, a central problem in embodied AI and Physical AI, needs data that internet video and existing motion capture datasets cannot provide.  How FrameNet, a linguistic framework for human action, can guide motion capture collection to systematically cover a broad range of whole-body motion.  Why synchronized object trajectories and meshes make human-object interaction data useful for teaching robots real-world tasks such as carrying, pushing, and pulling.  How reinforcement learning policies trained on this motion capture data improve with scale, and how sim-to-real transfer carries them onto a physical humanoid robot.    Click 'LOOK INSIDE' to Download Now.

Download this complimentary White Paper today! This White Paper gives engineers, researchers, and care professionals an overview of how socially assistive wellness robots can support senior wellness, and how a framework can measure their autonomy. What you will learn about:  Why the senior care crisis exceeds incremental healthcare automation. Staffing shortages, rising dementia prevalence, and limited daily wellness programming all play a part. How the seven ICAA dimensions of wellness define a distinct category of socially assistive robot, separate from companion devices, medical devices, and general-purpose humanoids. How the Care Robot Autonomy Scale (CRAS), a six-level framework modeled on a driving-automation standard, measures autonomy across four wellness dimensions. What technical capabilities, clinical evidence, and a three-phase roadmap suggest about the path from current practice toward full wellness autonomy in the early 2030s. Click 'LOOK INSIDE' to Download Now.