Planning and control for quadrotor flight through cluttered environments

Abstract

Previous demonstrations of autonomous quadrotor flight have typically been limited to sparse environments due to the computational burden associated with planning for a large number of obstacles. We hypothesized that it would be possible to do efficient planning and robust execution in obstacle-dense environments using the novel Iterative Regional Inflation by Semidefinite programming algorithm (IRIS), mixed-integer semidefinite programs (MISDP), and model-based control approaches. Here, we present experimental validation of this hypothesis using a small quadrotor in a series of indoor environments including a cubic meter volume containing 20 interwoven strings. We chose one of the smallest hardware platforms available on the market (34g, 92mm rotor to rotor), allowing for these dense environments and explain how to overcome the many system identification, state estimation, and control problems that result from the small size of the platform and the complexity of the environments.