Development of environmental niche models for use in underwater vehicle navigation. Issue 2 (18th January 2021)

• Record Type: Journal Article
• Authors: Fitzpatrick, Michael; Reis, Gregory M.; Anderson, Jacob; Bobadilla, Leonardo; Al Sabban, Wesam; Smith, Ryan N.
• Is Part Of: IET cyber-systems and robotics. Volume 2:Issue 2(2020)
• Page Start: 67
• Page End: 77
• Publication Date: 2021-01-18
• Subjects: probability -- underwater vehicles -- mobile robots -- position control -- path planning; environmental niche models -- environmental niche modelling -- confidence intervals -- underwater vehicle navigation -- aquatic species -- Big Fisherman's Cove -- Santa Catalina Island -- probability density functions -- biological analysis method -- ecological analysis method -- position estimation problem -- navigation problem; Robotics -- Periodicals; Cybernetics -- Periodicals; Cybernetics; Robotics; Periodicals; 629
• DOI: 10.1049/iet-csr.2019.0042
• Languages: English
• ISSNs: 2631-6315

Abstract

Abstract : This paper presents a review of Environmental Niche Modeling and a methodology for isolating the environmental niche of an aquatic species, given that prior information is available for characterising the physical tolerances for that species. To test and demonstrate our methodology, the environmental niche of the kelp bass has been isolated within Big Fisherman's Cove, Santa Catalina Island, CA, at specific confidence intervals. The motivation for this examination is to demonstrate the utility of ecological analysis in Robotics. Specifically, the utilisation of physical water properties to provide relative navigation and localisation for an aquatic robot. The environmental niches act as navigational landmarks in the seemingly featureless underwater environment. As water patches tend to stick together, this provides persistent landmarks for use in aquatic navigation problems. We provide the background and development of Environmental Niche Models, and present results from field trials for solving the navigation and localisation problem for underwater vehicles. Specifically, we provide results from a technique developed by the authors that utilises physical water parameters, e.g., temperature, salinity, chlorophyll, etc., to localise an underwater vehicle in a given region. The presented method leverages the concept of Environmental Niche Models to provide accurate position estimation that rivals GPS accuracy.