Robust Navigation Based on an Interacting Multiple-Model Filtering Framework Using Multiple Tracking Cameras

Sasanka Kuruppu Arachchige, Kyuman Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A commercial tracking camera readily available in aerospace applications usually provides reliable navigation solutions. While the navigation resulting from a tracking camera sometimes fails or drifts in a certain environment, another tracking camera facing a different direction in the same environment is usable. To produce consistent navigation with multiple tracking cameras facing distinct directions, we propose a real-time fusion approach employing an interacting multiple-model filtering framework. In other words, estimation outputs from each tracking camera are weighted according to their accuracy and uncertainty to generate a robust navigation system. The real-world experiments show that the proposed navigation system overcomes sensor failure and loss of texture for one camera.

Original languageEnglish
Title of host publicationAIAA SciTech Forum and Exposition, 2024
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624107115
DOIs
StatePublished - 2024
EventAIAA SciTech Forum and Exposition, 2024 - Orlando, United States
Duration: 8 Jan 202412 Jan 2024

Publication series

NameAIAA SciTech Forum and Exposition, 2024

Conference

ConferenceAIAA SciTech Forum and Exposition, 2024
Country/TerritoryUnited States
CityOrlando
Period8/01/2412/01/24

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