Agile Autopilot Control for Infrastructure InspectionMandeep Singh, Prajwal Shanthakumar, Jonah Orevillo, Arash Nouri

Dr. Pratap Tokekar, Dr. Matthew Hebdon

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Motivation and Objectives:▪ Bridge inspection: increase safety, ease, speed; lower cost▪ Reliable UAV flight and data collection▪ Autonomous navigation In difficult to access, GPS denied/sporadic

environments ▪ 3D reconstruction of the structure being inspected

System Design:▪ Quadrotor with Pixhawk autopilot▪ Monocular camera▪ 360° sweeping LIDAR▪ Intel NUC running ROS

Progress:➢ Preliminary Field Campaigns:• Experimental flights conducted at Coleman Memorial Bridge, Virginia Tech Smart Road Bridge, Kentland farm research facility

➢ Wind Velocity Profiling:▪ Data taken at each station with 3 anemometers at variable heights▪ Relative wind variation/turbulence ▪ Several longitudinal stations recorded▪ Describe the variation at different bridge cross-sections

➢ Visual Odometry:▪ For localization in GPS denied environments

1. Feature Based Methods:▪ Extract features from images for tracking (Eg., ORB)▪ Tracking good when environment is feature rich▪ Green squares: tracked features▪ Blue triangles: camera trajectory

2. Direct Methods:▪ Directly use pixel intensities (Eg., DSO)▪ Work better in environments with limited features▪ In case of rotation without translation, large tracking error (image on far right)

Summary:▪ UAV system with Camera and LIDAR constructed▪ Experiments conducted at various sites to obtain data▪ Various visual odometry techniques tested using logged data▪ 3D reconstruction carried out using Pix4D software

Next Steps:▪ Combine direct and feature based methods for visual odometry▪ Integrate IMU data – Visual Inertial Odometry▪ Integrate LIDAR – autonomous behaviours such as wall following

and obstacle avoidance

3D reconstruction of Coleman Memorial Bridge using Pix4D