Towards Flight Trials for an Autonomous UAV Emergency Landing using Machine Vision

This paper presents the evolution and status of a number of research programs focussed on developing an automated fixed wing UAV landing system. Results obtained in each of the three main areas of research as vision-based site identification, path and trajectory planning and multi-criteria decision making are presented. The results obtained provide a baseline for further refinements and constitute the starting point for the implementation of a prototype system ready for flight testing

Bioinspired engineering of exploration systems for NASA and DoD

A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers

Machine vision and scientific imaging for autonomous air vehicles (UAV).

This thesis outlines the necessary requirements to determine an Unmanned Aerial Vehicles (UAV’s) pose relative to a lead aircraft or target, thus enabling a UAV to successfully follow a lead aircraft or target. The use of Machine Vision for Autonomous navigation has been investigated and two flight scenarios were chosen for analysis. Firstly, following a manoeuvring lead aircraft, and secondly, maintaining a steady heading behind a target/lead aircraft (as would be required for in-flight refuelling). In addition, the author has performed a literature review of current research in this field which is significantly dominated by eventual military requirements in order to improve UAV endurance. In addition, experimental work towards developing a passive vision based navigation system has been undertaken. It is hoped that after further research and development this will lead to an eventual flight trial using the flight dynamics department’s UAV’s. The experimental work has been performed using both equipment and software already available within the department and furthermore, it has enabled an analysis of the department’s currently available capabilities for passive visual navigation to be undertaken. Key points for further work have been outlined for the future advancement of the visual navigation project.Engineering and Physical Sciences (EPSRC)MSc in Aerospace Dynamic