DreamZero is a World Action Model by NVIDIA that replaces the Vision-Language backbone common in VLAs with a video diffusion model to inherit richer physical priors. I compare DreamZero with π0.5 across 12 tasks in Isaac Sim on a DROID setup.
We use reinforcement learning in NVIDIA Isaac Lab to train Boston Dynamics' Spot to move using only its hind legs. Despite several challenges, we deploy the policy in the real world and show how well the sim-to-real policy transfer works.
Grievous is a low-cost mobile manipulation platform built on XLeRobot, extended with onboard SO-101 leader arms for fast in-place teleoperation. We finetune SmolVLA on pick-and-place and dusting tasks collected in lab environment and showcase current …
From voice command to synchronized flip: we show our early autonomous mission planning work that grew into Multi AI, including Tello drone choreography and a loyal wingman simulation for unmanned-manned teaming.
Standard path planners proved insufficient for dense multi-drone environments. We develop custom algorithms on top of EGO-Planner to enable robust obstacle avoidance in the Texas Robotics motion capture space, supporting advanced multi-agent …