IIIT Hyderabad Publications
Autonomous Navigation of Generic Monocular Quadcopter
Author: Kumar Bipin
Report no: IIIT/TH/2016/43
Autonomous navigation of generic monocular quadcopter in the natural and urban environment requires sophisticated mechanism for perception, planning and control. This thesis is primarily focused on describing a framework which performs perception using monocular camera and generates minimum time collision free trajectory and control for any commercial quadcopter flying through cluttered unknown environment. The proposed framework first utilizes supervised learning approach to estimate the dense depth map for video stream obtained from frontal monocular camera. This depth map is initially transformed into Ego Dynamic Space and subsequently, is used for computing locally traversable way-points utilizing binary integer programming methodology. Finally, trajectory planning and control module employs a convex programming technique to generate collision-free trajectory which follows these way-points and produces appropriate control inputs for the quadcopter. These control inputs are computed from the generated trajectory in each update. Hence, they are applicable to achieve closed loop control similar to model predictive controller. A majority of the work in this thesis is attributed to developing a Autonomous Navigation Framework for generic quad copter which incorporates various theoretical concepts into practical implementation with ROS (Robot Operating System) as middle-ware which is running on a conventional desktop computer with Ubuntu 12.04 LTS. The functionality of the proposed approach could be described as a threefold navigation framework: perception, planning and control. The thesis is concluded by demonstrating the applicability of developed navigation framework in controlled indoors and in unstructured natural outdoors environment on a low cost commercial quadcopter ParrotTM Ardrone 2.0.
Full thesis: pdf
Centre for Robotics
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