Gaussian Process-Based Scalar Field Estimation in GPS-Denied Environments

Fuente: arXiv
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Main Authors: Qureshi, Muzaffar, Ogri, Tochukwu Elijah, Ramos, Humberto, Bell, Zachary I., Kamalapurkar, Rushikesh
Format: Preprint
Published: 2025
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author Qureshi, Muzaffar
Ogri, Tochukwu Elijah
Ramos, Humberto
Bell, Zachary I.
Kamalapurkar, Rushikesh
author_facet Qureshi, Muzaffar
Ogri, Tochukwu Elijah
Ramos, Humberto
Bell, Zachary I.
Kamalapurkar, Rushikesh
contents This paper presents a methodology for an autonomous agent to map an unknown scalar field in GPS-denied regions. To reduce localization errors, the agent alternates between GPS-enabled and GPS-denied areas while collecting measurements. User-defined error bounds determine the dwell time in each region. A switching trajectory is then designed to ensure field measurements in GPS-denied regions remain within the specified error limits. A Lyapunov-based stability analysis guarantees bounded error trajectories while tracking the desired path. The effectiveness of the proposed methodology is demonstrated through simulations, with an error analysis comparing the GP-predicted scalar field model to the actual field.
format Preprint
id arxiv_https___arxiv_org_abs_2502_17584
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Gaussian Process-Based Scalar Field Estimation in GPS-Denied Environments
Qureshi, Muzaffar
Ogri, Tochukwu Elijah
Ramos, Humberto
Bell, Zachary I.
Kamalapurkar, Rushikesh
Systems and Control
This paper presents a methodology for an autonomous agent to map an unknown scalar field in GPS-denied regions. To reduce localization errors, the agent alternates between GPS-enabled and GPS-denied areas while collecting measurements. User-defined error bounds determine the dwell time in each region. A switching trajectory is then designed to ensure field measurements in GPS-denied regions remain within the specified error limits. A Lyapunov-based stability analysis guarantees bounded error trajectories while tracking the desired path. The effectiveness of the proposed methodology is demonstrated through simulations, with an error analysis comparing the GP-predicted scalar field model to the actual field.
title Gaussian Process-Based Scalar Field Estimation in GPS-Denied Environments
topic Systems and Control
url https://arxiv.org/abs/2502.17584