Vision-Based Plane Estimation and Following for Building Inspection With Autonomous UAV
Yang Lyu, Muqing Cao, Shenghai Yuan, Lihua Xie
Abstract
In this article, we focus on enabling the autonomous perception and control of a small unmanned aerial vehicle (UAV) for a façade inspection task. Specifically, we consider the perception as a planar object pose estimation problem by simplifying the building structure as a concatenation of planes, and the control as an optimal reference tracking control problem. First, a vision-based adaptive observer is proposed for plane pose estimation which converges fast and is insensitive to noise under very mild observation conditions. Second, a model predictive controller (MPC) is designed to achieve stable plane following and smooth transition in a multiple-plane scenario, while the persistent excitation (PE) condition of the observer and the maneuver constraints of the UAV are satisfied. The stability of the observer and the MPC controller is also investigated to ensure theoretical completeness. The proposed autonomous plane pose estimation and plane tracking methods are tested in both simulation and practical building façade inspection scenarios, which demonstrate their effectiveness and practicability.