Aggressive quadrotor flight through cluttered environments using mixed integer programming

Quadrotor flight has typically been limited to sparse environments due to numerical complications that arise when dealing with large numbers of obstacles. We hypothesized that it would be possible to plan and robustly execute trajectories in obstacle-dense environments using the novel Iterative Regional Inflation by Semidefinite programming algorithm (IRIS), mixed-integer semidefinite programs (MISDP), and model-based control. Unlike sampling-based approaches, the planning algorithm first introduced by Deits theoretically guarantees non-penetration of the trajectories even with small obstacles such as strings. We present experimental validation of this claim by aggressively flying a small quadrotor (34g, 92mm rotor to rotor) in a series of indoor environments including a cubic meter volume containing 20 interwoven strings, and present the control architecture we developed to do so.