Extended Data Fig. 1: Method overview: learning vision-based agile flight via differentiable physics.

The differentiable simulator carries gradients from the output state directly to the control inputs, and hence, to the policy parameters. A single timestep consists of depth map rendering, action prediction, and quadrotor dynamics simulation. The training environment only includes randomly placed obstacles.