Autonomous wireless sensor deployment with unmanned aerial vehicles for structural health monitoring applications

Abstract

Summary Unmanned aerial vehicles (UAVs) equipped with onboard sensors empower end‐users to collect data within a wide range of civil engineering applications such as structural condition assessment. While UAVs have been used primarily as mobile sensing platforms to obtain imagery or other data, their mobility can also be used to deploy sensor networks. In this study, the feasibility of using an autonomous UAV to deploy wireless sensors in structural monitoring applications is proposed. While GPS‐based waypoint navigation is available for automating UAV flight operations, this approach does not provide the accuracy necessary for the precision placement of sensor payloads on structures. Computer vision‐based pose estimation is proposed to improve the accuracy of UAV localization for sensor placement. Variably sized fiducial markers integrated into a single pattern are applied to the surface of the structure and adopted as navigation and precision landing targets that identify sensor placement locations. Visual and inertial measurements are fused by means of a discrete Kalman filter to further increase the robustness of the relative position estimation algorithm that is included in the proportional‐integral‐derivative (PID) control law used for UAV landing. Outdoor experiments under realistic operational conditions are conducted to validate the proposed vision‐aided control of the UAV for sensor placement; the UAV is able to land on a predefined landing point within 10 cm. A UAV moving a wireless accelerometer to locations on a beam is used to experimentally show the validity of automating UAV sensor placement for modal analysis using reconfigurable sensor network topologies.

Non-linear vibration signal compensation technique for UAV-deployable sensor packages with edge computing

“…In addition, these systems are advantageous in that a small number of sensing nodes can be rapidly mobilized and re-positioned along a structure, 4 for instance, in experimental modal analysis applications of suspended bridges. 5 As a result of their Further author information: (Send correspondence to Austin R.J. Downey) Austin R.J. Downey: E-mail: austindowney@sc.edu A shortcoming of minimally invasive sensors is the mounting medium that maintains contact between the actual vibration sensor and the structure of interest. Magnets and adhesives have been used to varying degrees of success, [10][11][12] with transmissibility loss being the main limitation.…”

Feasibility of Accurate Point Cloud Model Reconstruction for Earthquake-Damaged Structures Using UAV-Based Photogrammetry

“…In recent years, UAVs have been widely applied in civil engineering [7]. With the rapid development of UAV technology [8], low-altitude UAV surveying and mapping technology provides a new efcient multidimensional information acquisition method for structural digitization [9], daily maintenance [10,11], and postdisaster emergency assessment [12] of engineering structures. For example, the autonomous UAV system integrated with a modifed faster region-based convolutional neural network was proposed to identify various types of structural damage and map the detected damage in a GPS-denied environment [13].…”