There are many potential applications to utilise aerial robots in hazardous tunnel-like environments. For example, aiding human operators with inspections of small railway culverts or mineral mappings of mining tunnels. Nevertheless, such confined environments pose many challenges for quadcopters to navigate through. Suspended dust particles, poor lighting conditions and featureless/excessive features in the surroundings make localisation difficult. Furthermore, the fluid interactions between the rotors' downwash and the surfaces of the surroundings create aerodynamic disturbances, which threaten the quadcopter's stability and increase its risk of collision in the restricted confined space, not to mention the longitudinal wind gusts. This paper presents our findings on the characteristics of these aerodynamic disturbances, the Tunnel Effects for quadcopters, in a 1.5m(W) x 1.5m(H) square cross section tunnel through a series of experiments. A semi-autonomous system is proposed with self-stabilisation in the vertical and lateral axes while a pilot provides commands in heading and the longitudinal direction of the tunnel for performing required tasks such as tunnel wall inspections. We propose a cross-sectional localisation scheme using Hough Scan Matching with a simple kinematic Kalman filter for providing reliable vertical and lateral position information. An integral backstepping (IBS) controller is designed and implemented to enable quadcopters to robustly fly in tunnel-like confined environments. The proposed system is tested in simulated tunnel environments and a real railway tunnel with various reference trajectories, and the IBS controller has shown superior tracking performance in comparison with a PID controller despite of the existence of the Tunnel Effects.

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.

This project aims to develop a small-scale multi-rotor unmanned aerial system (UAS) as a railway culvert inspection tool. In the current study, the UAS is deployed at the entrance to a culvert and it then traverses through the culvert in a semi-autonomous fashion. The UAS is able to measure the cross sectional shape of the culvert in real time using the on-board light detection and ranging (LiDAR) scanner, that is also used to autonomously align the UAS with the centroid of this cross section. With extra sensors to measure the distance of the UAS from entrance of the culvert, the cross sectional data collected from the LiDAR can then be further processed to obtain three-dimensional point clouds of the culvert's structure. This system enables the railway entities to safely and efficiently conduct regular inspections and collect necessary measurements without needing to enter confined spaces or rail corridor. Navigating the UAS through confined spaces does present a number of challenges. Novel research is required to deal with the stability of a UAS in a confined space, where the interaction between the vehicle rotor downwash and the walls of the culvert leads to unstable flight.