RAST decouples what a system wants to achieve from how it moves. Using Inverse Optimal Control, we extract the optimization strategy, the cost structure, behind expert movement. This “motor signature” captures intent, not trajectory, enabling transfer across physics changes where imitation learning breaks.

RAST is grounded in optimal control: the same foundations behind spacecraft guidance and precision robotics. We apply that rigor to motor behavior and real-time execution.