Vision Based Autonomous UAV Plane Estimation And Following for Building Inspection

TL;DR

This paper presents a vision-based autonomous UAV system for building facade inspection, featuring a novel adaptive observer for plane pose estimation and a model predictive controller for stable multi-plane tracking, validated through simulations and real-world tests.

Contribution

It introduces a new adaptive observer for stable plane pose estimation and a model predictive control approach for smooth multi-plane tracking in UAV facade inspection.

Findings

Effective plane pose estimation under mild conditions

Stable multi-plane tracking demonstrated in simulations

Practical feasibility confirmed through real-world tests

Abstract

Unmanned Aerial Vehicle (UAV) has already demonstrated its potential in many civilian applications, and the fa\c{c}ade inspection is among the most promising ones. In this paper, we focus on enabling the autonomous perception and control of a small UAV for a fa\c{c}ade inspection task. Specifically, we consider the perception as a planar object pose estimation problem by simplifying the building structure as concatenation of planes, and the control as an optimal reference tracking control problem. First, a vision based adaptive observer is proposed which can realize stable plane pose estimation under very mild observation conditions. Second, a model predictive controller is designed to achieve stable tracking and smooth transition in a multi-plane scenario, while the persistent excitation (PE) condition of the observer and the maneuver constraints of the UAV are satisfied. The proposed autonomous plane pose estimation and plane tracking methods are tested in both simulation and practical building fas\c{c}ade inspection scenarios, which demonstrate their effectiveness and practicability.