Speaker: Dr. N. Andrew Browning
Title: High speed reactive obstacle avoidance and aperture traversal using a monocular camera
Flight in cluttered indoor and outdoor environments requires effective detection of obstacles and rapid trajectory updates to ensure successful avoidance. We present a low-computation, monocular-camera based solution that rapidly assesses collision risk in the environment through the computation of Expansion Rate, and fuses this with the range and bearing to a goal location (or object), in a Steering Field to steer around obstacles while flying towards the goal. The Steering Field provides instantaneous steering decisions based on the current collision risk in the environment, Expansion Rate provides an automatically-speed-scaled estimate of collision risk. Results from recent flight tests will be shown with flights at up to 20m/s around man-made and natural obstacles and through 5x5m apertures.
Dr. N. Andrew Browning obtained his PhD in Computational Neuroscience from Boston University with a thesis on how primates and humans process visual information for reactive navigation, the resulting neural model was built into a multi-layer convolutional neural network (called ViSTARS) and demonstrated, in simulation, to generate human-like trajectories in cluttered reactive navigation tasks. Following his PhD, applied post-doctoral research, and a brief stint as a Research Assistant Professor at BU, Dr. Browning started a research group at Scientific Systems Company Inc. (SSCI) to develop Active Perception and Cognitive Learning (APCL) systems as applied to autonomous robotic systems. The APCL lab at SSCI has developed into a global leader in the development of applied perception and autonomy solutions for small UAVs. Dr. Browning is now Deputy Director of Research and Development at SSCI with a broad remit across the areas of advanced controls, single vehicle and collaborative autonomy, visual perception, acoustic perception, and vision-aided GNC.