Augmented Terrain-Based Navigation to Enable Persistent Autonomy for Underwater Vehicles in GPS-Denied Environments

Abstract

2.2 Descriptive statistics for the dataset collected during a mission at the Big Fisherman's Cove, Santa Catalina Island, CA, USA, on July 14th 2016.. 2.3 Descriptive statistics for the dataset collected during a mission at the Lake Nighthorse, CO, USA, on April 25th 2018, in the afternoon.. .. .. .. 2.4 Descriptive statistics for the dataset collected during a mission at the Lake Nighthorse, CO, USA, on May 2nd 2018, in the morning.. .. .. .. . 2.5 Descriptive statistics for the dataset collected during a mission at the Lake Nighthorse, CO, USA, on May 2nd 2018, in the afternoon.. .. .. .. . 4.1 Global correlation values for different combination of parameters.. .. .. . 5.1 Minimum, maximum, mean and standard deviation of the water parameters considered for the Santa Catalina Island deployment on the first day.. .. 5.2 Minimum, maximum, mean and standard deviation of the water parameters considered for the Santa Catalina Island deployment on the second day. .

Development of environmental niche models for use in underwater vehicle navigation

“…We found that the ATBN framework was reliable for localisation tasks, and could provide pose estimation at accuracies similar to GPS. Further research has been conducted, and for a more detailed analysis of the field trials and corresponding results, we encourage the interested reader to consider [28,29,42].…”

“…In this section, we present a summary of a few results we have obtained by applying the proposed theory of environmental niche models to the development of ATBN and implementing this onto underwater vehicles during field trials. Complete details of the results presented here can be found in [42].…”

“…The proposed methodology was tested with data from multiple deployments at the Big Fisherman's Cove on Santa Catalina Island, CA, USA. Further results from data gathered in Lake Nighthorse, CO, USA can be found in [42]. The missions were executed using a YSI EcoMapper AUVs [43].…”

“…This allows us to track the position of the vehicle within small intervals of time (less than an hour) until the GPS signal returns. Details of this decorrelation can be found in [35,42].…”

“…[25]. Further research on ATBN includes an examination on how to intelligently update our maps [34], and ways to predict spatiotemporal dynamics of the region [42], possibly through the incorporation of predictive ocean models [46]. Given enough deployments in the same region, covering a sufficient spatiotemporal epoch, one could investigate applications of machine or deep learning to incorporate dynamics onto the ATBN maps.…”