This is what motivated us to study computer vision, and structure from motion (SFM) in particular, from a control-theoretic perspective. We have done so within the Berkeley Aerial Robot Project, in which a number of ground and aerial robots form a team of pursuers that tries to capture a team of evaders in an unknown environment. The main vision tasks we want to acomplish are to detect position, orientation and velocities of the evaders; to detect position and orientation of obstacles; to estimate position and orientation of a moving helicopter; and to use all this information for navigation and control purposes such as pursuit evasion games, vision based landing of a helicopter, formation flight, etc.
In the talk, I will first describe our recent results in Single-Body
1) Multiple View Geometry
2) Implementation of Pursuit-Evasion Games.
I will then talk about our future research in Multi-Body SFM, the challenges we will have to face, and the way we plan to address the problem.