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Autor principal: Saxena, Devanshu
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2505.22675
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author Saxena, Devanshu
author_facet Saxena, Devanshu
contents Approximately seventy-one percent of the Earth is covered in water. Of that area, ninety-five percent of the ocean has never been explored or mapped. There are several engineering challenges that have prevented the exploration of the deep ocean through human or autonomous means. These challenges include but are not limited to high pressure, cold temperatures, little natural light, corrosion of materials, and communication. Ongoing research has been focused on trying to find optimal and low-cost solutions to effective communication between autonomous underwater vehicles (AUVs), and the surface or air. In this paper, an architecture is introduced that utilizes an edge computing approach to establish computation nearer to the source of data, allowing further exploration of the deep ocean. Taking the most common interpolation techniques used today in the field of bathymetry, the data are tested and analyzed to find the feasibility of switching from CPU to GPU computation. Specifically, the focus is on writing efficient interpolation algorithms that can be run on low-level GPUs, which can be carried onboard AUVs as payload.
format Preprint
id arxiv_https___arxiv_org_abs_2505_22675
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Towards Real-Time Interpolation for Enhanced AUV Deep Sea Mapping
Saxena, Devanshu
Atmospheric and Oceanic Physics
Networking and Internet Architecture
Robotics
Approximately seventy-one percent of the Earth is covered in water. Of that area, ninety-five percent of the ocean has never been explored or mapped. There are several engineering challenges that have prevented the exploration of the deep ocean through human or autonomous means. These challenges include but are not limited to high pressure, cold temperatures, little natural light, corrosion of materials, and communication. Ongoing research has been focused on trying to find optimal and low-cost solutions to effective communication between autonomous underwater vehicles (AUVs), and the surface or air. In this paper, an architecture is introduced that utilizes an edge computing approach to establish computation nearer to the source of data, allowing further exploration of the deep ocean. Taking the most common interpolation techniques used today in the field of bathymetry, the data are tested and analyzed to find the feasibility of switching from CPU to GPU computation. Specifically, the focus is on writing efficient interpolation algorithms that can be run on low-level GPUs, which can be carried onboard AUVs as payload.
title Towards Real-Time Interpolation for Enhanced AUV Deep Sea Mapping
topic Atmospheric and Oceanic Physics
Networking and Internet Architecture
Robotics
url https://arxiv.org/abs/2505.22675