Using Quadcopter for Vision-based Tracking of High-Rise Vertical Structure

This research paper focuses on developing visionbased autonomous navigation and motion control algorithms for quadcopters to track high-rise industrial vertical structures. A camera, fixed on the drone will capture the Red-Green-Blue (RGB) channel image and will feed to the image processing node, which is a convolution neural network (CNN) based encoder-decoder model for image segmentation. The segmented image will go to the classical computer vision algorithm to get the desired features for navigation and the motion control algorithm. In this paper, we have implemented a nonlinear sliding mode control algorithm for motion control and discuss the results of positioning and motion control of the drone for the motion in circular and spiral paths. The entire experimentation is performed on the DJI M100 drone with the Nvidia Jetson Xavier NX as an onboard computer.