{"id":{"repo_id":"byu","oai_identifier":"oai:scholarsarchive.byu.edu:etd-2374"},"canonical_url":"https://search.dev.ndltd.org/etd/byu/oai:scholarsarchive.byu.edu:etd-2374","repository":{"repo_id":"byu","name":"Brigham Young University","base_url":"https://scholarsarchive.byu.edu/do/oai/"},"display":{"title":"Stabilization and Control of a Quad-Rotor Micro-UAV Using Vision Sensors","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Fowers, Spencer G."],"institution":"Brigham Young University - Provo","degree_name":"MS","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T01:29:12Z","subjects":["real-time image processing","micro-UAV control","stabilization","target tracking","BYU","FPGA","Kalman filter","quadrotor","Electrical and Computer Engineering"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsarchive.byu.edu/etd/1375","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Fowers, Spencer G."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2008-04-23T07:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["Brigham Young University - Provo"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["real-time image processing","micro-UAV control","stabilization","target tracking","BYU","FPGA","Kalman filter","quadrotor","Electrical and Computer Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsarchive.byu.edu/etd/1375","https://scholarsarchive.byu.edu/context/etd/article/2374/viewcontent/ETD_CISOPTR_1379.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering"]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:format","label":"Dc Format","values":["application:pdf"]},{"key":"dc:source","label":"Dc Source","values":["Brigham Young University - Provo"]},{"key":"dc:title","label":"Title","values":["Stabilization and Control of a Quad-Rotor Micro-UAV Using Vision Sensors"]}]}],"canonical_facts":{"dc:creator":["Fowers, Spencer G."],"dc:date":["2008-04-23T07:00:00Z"],"dc:description":["Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering"],"dc:description.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."],"dc:format":["application:pdf"],"dc:identifier":["https://scholarsarchive.byu.edu/etd/1375","https://scholarsarchive.byu.edu/context/etd/article/2374/viewcontent/ETD_CISOPTR_1379.pdf"],"dc:language":["English"],"dc:publisher":["Brigham Young University - Provo"],"dc:source":["Brigham Young University - Provo"],"dc:subject":["real-time image processing","micro-UAV control","stabilization","target tracking","BYU","FPGA","Kalman filter","quadrotor","Electrical and Computer Engineering"],"dc:title":["Stabilization and Control of a Quad-Rotor Micro-UAV Using Vision Sensors"],"dc:type":["Thesis"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T01:29:12Z"}