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Vision Systems for Autonomous Aircraft Guidance

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Vision Systems for Autonomous Aircraft Guidance Vision Systems for Autonomous Aircraft Guidance Richard J. D. Moore A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2012 Queensland Brain Institute Abstract Unmanned aerial vehicles (UAVs) are increasingly being used for a wide variety of civil and commercial applications such as infrastructure inspection and maintenance, search and rescue, mapping and cartography, as well as agricultural and environmental monitoring, to name just a few. Unmanned aircraft are suited to these roles because they can be smaller and lighter than manned aircraft and hence cheaper to operate, as well as being able to perform dull or repetitive tasks with greater precision than human operators, and dangerous tasks with greater safety. With the expanding set of roles for UAVs, there is an increasing need for them to be able to fly with a degree of low-level autonomy, thus freeing up their human controllers to concentrate on high-level decisions. Modern UAVs control their position and orientation in space using technologies such as the Global Positioning System (GPS) and attitude and heading reference systems (AHRSs). They are unable to detect or avoid other objects or vehicles using these systems only, however, rendering them incapable of operating autonomously in near-Earth environments or around other moving vehicles. In these situations the aircraft must be able to monitor its surroundings continuously. Active proximity sensors, such as laser range-finders or radar, can be bulky, stealth-compromising, high-power, and low-bandwidth { limiting their utility for small-scale UAVs. There is considerable benefit to be gained, therefore, by designing guidance systems that use passive sensing, such as vision. This thesis builds on recent research into biological vision-based flight control strategies to demonstrate that such bioinspired methods can offer dramatically improved sensing and control efficiencies over more complex computer vision-based approaches. Furthermore, this thesis establishes that wide-angle vision systems enable a broad array of sensing and guidance strategies, which can be implemented in parallel, in turn enabling complex flight behaviours that would traditionally require sensing and processing architectures incompatible with small-scale UAVs. Two wide-angle vision systems are developed during the course of this research as well as a number of novel vision-based sensing and guidance algorithms, enabling detection of oncoming obstacles, estimation of attitude and altitude, long-term tracking of features, and interception of independently moving objects. Using these systems, complex capabilities such as terrain following at low altitude, aerobatics, landing in an uncontrolled environment, as well as tracking and interception of i an independently moving object are all demonstrated for the first time using only computing resources available on board a small-scale UAV and using only vision for all sensing and guidance. The findings of this thesis contribute towards a greater understanding of the minimum requirements { in terms of sensing and guidance architectures { for complex UAV behaviours; and the design methodologies proposed herein represent an important step towards full autonomy for small-scale airborne platforms, thereby contributing towards exploitation of UAVs for civil and commercial applications and bringing autonomous UAVs a step closer to the remarkable capabilities of their biological counterparts. ii Declaration by the Author This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis. I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my research higher degree candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award. I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the General Award Rules of The University of Queensland, immediately made available for research and study in accordance with the Copyright Act 1968. I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis. iii Publications during candidature Refereed conference proceedings [Moore et al., 2012] R. J. D. Moore, S. Thurrowgood, M. V. Srinivasan, \Vision-only estimation of the wind field strength and direction from an aerial platform". In Proc. IEEE/RSJ International Conference on Intelligent Robots and System, Vilamoura, Portugal, Oct. 2012. [Moore et al., 2011c] R. J. D. Moore, S. Thurrowgood, D. Soccol, D. Bland, M. V. Srinivasan, \A method for the visual estimation and control of 3-DOF attitude for UAVs". In Proc. ARAA Australasian Conference on Robotics and Automation, Melbourne, Australia, Dec. 2011. [Moore et al., 2011a] R. J. D. Moore, S. Thurrowgood, D. Bland, D. Soccol, M. V. Srinivasan, \A fast and adaptive method for estimating UAV attitude from the visual horizon". In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 4935{4940, 2011. [Thurrowgood et al., 2010] S. Thurrowgood, R. J. D. Moore, D. Bland, D. Soccol, M. V. Srinivasan, \UAV attitude control using the visual horizon". In Proc. ARAA Australasian Conference on Robotics and Automation, Brisbane, Australia, Dec. 2010. [Moore et al., 2010] R. J. D. Moore, S. Thurrowgood, D. Bland, D. Soccol, M. V. Srinivasan, \UAV altitude and attitude stabilisation using a coaxial stereo vision system". In Proc. IEEE/RAS International Conference on Robotics and Automation, pages 29{34, 2010. [Moore et al., 2009] R. J. D. Moore, S. Thurrowgood, D. Bland, D. Soccol, M. V. Srinivasan, \A stereo vision system for UAV guidance". In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3386{3391, 2009. [Thurrowgood et al., 2009] S. Thurrowgood, D. Soccol, R. J. D. Moore, D. Bland, M. V. Srinivasan, \A vision based system for attitude estimation of UAVs". In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 5725{ 5730, 2009. Book chapters [Srinivasan et al., 2012] M. V. Srinivasan, R. J. D. Moore, S. Thurrowgood, D. Soccol, D. Bland, \Insect vision and applications to robotics". In F. G. Barth, J. A. C. Humphrey, M. V. Srinivasan (Eds.), Frontiers in Sensing: From Biology to Engineering, pages 19{39, Springer-Verlag, Wien, 2012. [Moore et al., 2011b] R. J. D. Moore, S. Thurrowgood, D. Soccol, D. Bland, M. V. Srinivasan, \A bio-inspired stereo vision system for guidance of autonomous aircraft". In A. Bhatti (Ed.), Advances in Theory and Applications of Stereo Vision, pages 305{ 326, InTech, Rijeka, 2011. iv Publications included in this thesis Moore et al.[2011b] incorporated as portions of Chapters1{4. Contributors: R. J. D. M., design (50%), implementation (70%), analysis (100%), article (90%); S. T., design (30%), implementation (20%), article (5%); D. B., implementation (5%) and other assistance; D. S., implementation (5%) and other assistance; M. V. S., design (20%), article (5%) and other assistance. Moore et al.[2009] incorporated as portions of Chapters3&4. Contributors as above. Moore et al.[2010] incorporated as portions of Chapters3&4. Contributors as above. Moore et al.[2011a] incorporated as portions of Chapter6. Contributors: R. J. D. M., design (80%), implementation (80%), analysis (100%), article (90%); S. T., design (20%), implementation (10%), article (5%); D. B., implementation (5%) and other assistance; D. S., implementation (5%) and other assistance; M. V. S., article (5%) and other assistance. Moore et al.[2011c] incorporated as portions of Chapter6. Contributors: R. J. D. M., design (100%), implementation (80%), analysis (100%), article (90%); S. T., implementation (10%), article (5%); D. B., implementation (5%) and other assistance; D. S., implementation (5%) and other assistance; M. V. S., article (5%) and other assistance. Moore et al.[2012] incorporated as Section 6.6.1. Contributors: R. J. D. M., design (100%), implementation (75%), analysis (100%), article (90%); S. T., implementation (25%), article (5%); M. V. S., article (5%) and other assistance. Contributions by others to this thesis Aside from the contributions by others to publications incorporated within this thesis (listed above), the research and ideas, as well as the design and development of algorithms, experimental design, analysis and interpretation of results, and writing contained within this thesis are all entirely the candidate's own work. Where this research relies on work conducted jointly with others, and no appropriate prior publication is available, the candidate's contribution is stated explicitly. Statement of parts of this thesis submitted to qualify for the award of another degree None. v
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