Improving the Accuracy and Robustness of Ultra-Wideband Localization Through Sensor Fusion and Outlier Detection

Autor:	Jan Steckel, Erik Hostens, Kurt Geebelen, Anurodh Mishra, Merwan Birem, Risang Yudanto, Nathan Dwek
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Technology Control and Optimization Outlier Detection Computer science Biomedical Engineering Ultra-wideband 02 engineering and technology MITIGATION Extended Kalman filter Artificial Intelligence Robustness (computer science) SYSTEMS 0202 electrical engineering electronic engineering information engineering Computer vision Range Sensing Science & Technology business.industry Sensor Fusion Mechanical Engineering 020208 electrical & electronic engineering 020206 networking & telecommunications Robotics Sensor fusion Computer Science Applications Human-Computer Interaction Control and Systems Engineering Localization Anomaly detection Computer Vision and Pattern Recognition Artificial intelligence business Engineering sciences. Technology
Zdroj:	IEEE robotics and automation letters
ISSN:	2377-3766
Popis:	This article presents sensor fusion techniques for ultra-wideband-based localization to achieve sufficient accuracy and robustness for the control of vehicles in an industrial environment. We propose two outlier detection methods in combination with an extended Kalman Filter, and present experimental validation where 10 cm accuracy is achieved even in difficult NLOS conditions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d1a16beb69cb34cf87ba8d04d46c3a9 https://lirias.kuleuven.be/handle/123456789/664815 Zobrazit plný text záznamu