There is need for fast, easy-to-operate, and low-risk methods for mapping geography, velocity, and bathymetry of rivers. River charts can be nonexistent or inadequate because of changes in water volume, tides, sediment transport, flooding, and other events. This is a hindrance and a hazard for navigation and other operations. Currently, procedures to map rivers involve navigating surface vessels into regions with significant uncertainty, which can be labor-intensive and dangerous. A better alternative is possible using low-cost sensors that float downstream, collecting data. Passive "drifters" have proven useful to research groups mapping ocean currents. However, faster flows and more constricted morphology in rivers present challenges. Passive floating sensors converge to similar streamlines and thus geographic coverage is limited, and can also get trapped or damaged by river features. In this program we will combine SSCI's technical and algorithmic expertise in autonomous vehicles, planning and decision making, and bathymetric mapping, and UC Berkeley's practical hands-on experience with self-propelled floating riverine sensors, for river modeling and mapping. We will design a system of collaborative, autonomous, self-propelled sensor vehicles and core strategies that will optimize the time, effort, cost, and risk necessary to successfully map rivers.
Keywords: Bathymetry, Bathymetry, Drifters, Autonomous Vehicles, River, Riverine, Morphology, Sensors, Navigation
