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.
I use reinforcement learning in NVIDIA Isaac Lab to train Boston Dynamics' Spot to stand and move using only its hind legs. Despite several challenges, I achieve zero-shot sim-to-real transfer and deploy the policy directly on real hardware.
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 …