Multi-Sensory UAV Navigation Research Testbed

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This proposal seeks funding to acquire infrastructure to support multi-model robotic navigation system design research at the Intelligent Systems Lab of Memorial University of Newfoundland. Unmanned Aerial Vehicles (UAVs) are servicing several industrial, survey, and research sectors in both remotely operated and autonomous settings. Currently, these applications employ GPS waypoint navigation control to service inspection tasks required by clients. However, for many industrial applications, precise autonomous operation under intermittent and limited GPS conditions is desired in varying environmental conditions, e.g., structural inspection tasks at sites with areas of patchy GPS reception, offshore structures inspection, dry dock inspection of ships, operational scale drone delivery, and environmental surveillance to support harsh environment navigation. These applications demand a multi-sensory and multi-model approach with robust redundancy measures to achieve safety-critical autonomy of the platforms. The research program has both fundamental knowledge development and operational scale validation where an archive of system and sensor models is used in a consistent way to reliably observe the navigation states of robots, i.e., aerial robots transitioning through GPS limited areas, through pre-mapped regions, and areas with changing environmental conditions such as wind gust, magnetic disturbances, and degraded visibility. The research methodology examines probabilistic estimator design that employs a bank of models at its disposal that include nominal Inertial Navigation System (INS) mechanization equations, dynamic constraints of the platform, learned un-modeled dynamics, and models with varying stochastic noise parameters. Furthermore, the existence of redundant sensor sources ranging from visual, inertial, Ultra-Wide Band, LiDAR, and GPS are investigated to achieve robust navigational system performance for extending platforms' operational envelope. This NSERC RTI proposal requests equipment support for a “Multi-sensory UAV navigation research testbed” which comprises of a hexacopter drone equipped with a custom visual-inertial-Lidar navigation sensor package and a RTK GPS system. The proposed equipment is necessary to complete field experimental validation of multi-model robotic navigation research findings using actual sensor data feedback during operation. The equipment will provide HQP hands-on training on operational scale validation of UAV navigation technology using state of the art software and hardware tools. These capabilities are highly transferable to technology and research sectors across Canada and significantly enhance the industry collaborative research partnerships of MUN ISL.