Reinforcement Learning

Two-Legged Spot: Teaching a Quadruped to Only Use Its Hind Legs for Locomotion

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.

Multi-Agent Planning in Adversarial Environments

At Multi AI, we have built a multi-agent reinforcement learning platform for complex planning and coordination problems of large numbers of assets in the military.

Autonomous Mission Planning for Robotics Systems

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.

Flying in Cluttered Environments

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 …