Most autonomous vehicles, especially high-performance aircraft, must perceive their environment very rapidly using limited computing and sensing resources. In many high-performance applications, slight deviations in the trajectory of the vehicle may enable substantial increase in perception capabilities. Therefore, the trajectory of the vehicle must be chosen carefully to optimize, not only trajectory objectives, but also perception objectives.

FlightGoggles is envisioned to be development environment that allows the design, implementation, testing and validation of autonomous super-vehicles. FlightGoggles currently provides exteroceptive sensor simulation based on the Unity3D engine as well as vehicle dynamics and inertial sensor simulation capabilities. We aim to train algorithms in this photogrammetric environment and transfer them directly to real world applications.

Pose estimation is critical in many robotics applications, particularly to enable autonomous vehicles to perceive other vehicles around them. We design algorithms that allow 6D pose estimation in challenging scenarios, including heavy occlusion, while under computational constraints.