Active Localization using Bernstein Distribution Functions

Camilla Tabasso; Venanzio Cichella

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Active Localization using Bernstein Distribution Functions

Preprint

Open access

Active Localization using Bernstein Distribution Functions

Camilla Tabasso and Venanzio Cichella

ArXiv.org

10/06/2022

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url

https://doi.org/10.48550/arXiv.2210.03187View

Preprint (Author's original)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

In this work, we present a framework that enables a vehicle to autonomously localize a target based on noisy range measurements computed from RSSI data. To achieve the mission objectives, we develop a control scheme composed of two main parts: an estimator and a motion planner. At each time step, new estimates of the target's position are computed and used to generate and update distribution functions using Bernstein polynomials. A metric of the efficiency of the estimator is derived based on the Fisher Information Matrix. Finally, the motion planning problem is formulated to react in real time to new information about the target and improve the estimator's performance.

Details

Title: Subtitle: Active Localization using Bernstein Distribution Functions
Creators: Camilla Tabasso
Venanzio Cichella
Resource Type: Preprint
Publication Details: ArXiv.org
ISSN: 2331-8422
Language: English
Date posted: 10/06/2022
Academic Unit: Mechanical Engineering
Record Identifier: 9984305372702771

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