Abstract

Quad-rotor micro-UAVs have become an important tool in the field of indoor UAV research. Indoor flight poses problems not experienced in outdoor applications. The ability to be location- and movement-aware is paramount because of the close proximity of obstacles (walls, doorways, desks). The Helio-copter, an indoor quad-rotor platform that utilizes a compact FPGA board called Helios has been developed in the Robotic Vision Lab at Brigham Young University. Helios allows researchers to perform on-board vision processing and feature tracking without the aid of a ground station or wireless transmission. Using this on-board feature tracking system a drift stabilization control system has been developed that allows indoor flight of the Helio-copter without tethers. The Helio-copter uses an IMU to maintain level attitude while processing camera images on the FPGA. The FPGA then computes translation, scale, and rotation deviations from camera image feedback. An on-board system has been developed to control yaw, altitude and drift based solely on the vision sensors. Preliminary testing shows the Helio-copter capable of maintaining level, stable flight within a 6 foot by 6 foot area for over 40 seconds without human intervention using basic PID loop structures with minor tuning. The integration of the vision system into the control structures is explained.

Degree

MS

College and Department

Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2008-04-23

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd2375

Keywords

real-time image processing, micro-UAV control, stabilization, target tracking, BYU, FPGA, Kalman filter, quadrotor

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