Development of an autonomous surface tracking quadrotor system utilizing low-cost proximity sensors
| dc.contributor.author | Spyker, Jamie | |
| dc.date.accessioned | 2017-10-24T23:34:27Z | |
| dc.date.available | 2017-10-24T23:34:27Z | |
| dc.date.issued | 2017 | en |
| dc.description.abstract | This thesis provides extensive research and development for autonomous control of a quadrotor system using low-cost proximity sensors. Investigations towards this are completed in the areas of quadrotor simulation, control algorithm development and prototype system construction. Autonomous UAV systems can be highly useful for a variety of applications and are becoming more widespread in modern society. Reviewing current techniques for autonomous control showed that most commonly computer vision and GPS methods are utilized, with their key downsides being high complexity and cost. It was proposed that creating a simplified autonomous control system using proximity sensors could be option for reducing these problems. The use for such a system was identified to have a potential application within the areas of commercial inspections, where a nearby surface would constantly be present for ranging data. A literature review was completed into current similar applications and methods providing a basis to build off. Further background research was completed into UAV dynamics and relevant hardware for proximity sensor tracking. To enable the development of algorithms with use of proximity sensors, simulation software was created. The base simulation implementation included dynamic modelling of a quadrotor and localized control methods. Following this virtual sensors and surfaces were designed and implemented into the simulation software. The developed software was functionally tested and worked as expected comparing well to results of similar research. With use of the built simulator, research was undertaken into potential control algorithms utilizing proximity sensors. The intention of this exploration is to confirm the viability of proximity sensor control and to provides potential algorithm options that can be extended upon in the future. Control algorithms were developed which focused on automating a singular control channels - for roll, pitch and yaw of a quadrotor system. Options were presented for both flat and varied vertical surfaces proving the potential viability for such methods. Development for a prototype system was completed that can control a UAV with autonomous isolated channels, for the purpose of real-world testing of algorithms. The system was validated by testing a prior control algorithm created within the simulator. The results of the functional tests showed the the system successfully tracking a vertical surface with autonomous pitch control. Further investigation into the performance results showed that improvements should be focused on reducing system noise as significant fluctuations were present reducing control accuracy. In summary, this study provides a comprehensive overview of the potential options for autonomous control of a quadrotor using proximity sensors and proves their viability. Key contributions include the addition of virtual sensors in a simulation environment, algorithm options for autonomous control and the development of autonomous control hardware. This investigation provides a solid basis for future researchers with wide possibilities of potential future work that could be completed. | en |
| dc.identifier.uri | http://hdl.handle.net/10092/14546 | |
| dc.identifier.uri | http://dx.doi.org/10.26021/2952 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.publisher | University of Canterbury | en |
| dc.rights | All Right Reserved | en |
| dc.rights.uri | https://canterbury.libguides.com/rights/theses | en |
| dc.title | Development of an autonomous surface tracking quadrotor system utilizing low-cost proximity sensors | en |
| dc.type | Theses / Dissertations | en |
| thesis.degree.discipline | Mechanical Engineering | |
| thesis.degree.grantor | University of Canterbury | en |
| thesis.degree.level | Masters | en |
| thesis.degree.name | Master of Engineering | en |
| uc.bibnumber | 2539161 | |
| uc.college | Faculty of Engineering | en |