Augmenting LSPIV Surface Current Measurement with Drifting ASVs

Abstract

Large Scale Particle Image Velocimetry (LSPIV) has been successfully used in the field to gather water surface flow data, which is critical to understanding complex geomorphic, hydrologic, and ecological river processes. Its success, however, depends on lighting conditions and adequate flow seeding with trackable debris or visual features, that can be hampered by environmental disturbances such as wind or wildlife. Instead, this research proposes augmenting traditional LSPIV methods by incorporating autonomous surface vehicles (ASVs) as pieces of actuated debris. This addresses the shortcomings of artificial seeding with tracers that may not be recoverable and impractical. Our method uses initial image velocimetry flow estimates to guide an ASV to sparsely seeded or poorly illuminated regions within the survey area. There it can be set adrift and tracked from above to capture additional measurements to improve the surface flow field reconstruction. We compare conventional techniques with our augmented LSPIV system in simulation and in field tests. The results showcase performance and capability enhancements ASVs can provide.