Integral Backstepping Position Control for Quadrotors in Tunnel-Like Confined Environments

Abstract

There are many potential applications that require flying robots to navigate through tunnel-like environments, such as inspections of small railway culverts and mineral mappings of mining tunnels. Nevertheless, those environments present many challenges for quadrotors to navigate through. The aerodynamic disturbances created from the fluid interaction between the propellers’ downwash and the surrounding surfaces of the environment, as well as longitudinal wind gusts, add hardship in stabilising the vehicle while the restricted narrow space increases the risk of collision. Furthermore, poor visibility and dust blown by the downwash make vision-based localisation extremely difficult. This paper presents a cross-sectional localisation system using Hough Scan Matching and a simple kinematic Kalman filter. Using the estimated state information, an integral backstepping controller is implemented which enables quadrotors to robustly fly in tunnel-like confined environments. A semi-autonomous system is proposed with self-stabilisation in the vertical and lateral axes while a pilot provides commands in the longitudinal direction. The results of a series of experiments in a simulated tunnel show that the proposed system successfully hovered itself and tracked various trajectories in a cross-sectional area without the aid of any external sensing or computing system.