Sensors 2013, 13(10), 14133-14160; doi:10.3390/s131014133
Article

Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots

Department of Systems Engineering and Control, Instituto Universitario de Automática e Informática Industrial, Universidad Politécnica de Valencia, Camino de Vera, E-46022 Valencia, Spain
* Author to whom correspondence should be addressed.
Received: 26 August 2013; in revised form: 9 October 2013 / Accepted: 10 October 2013 / Published: 21 October 2013
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2013)
PDF Full-text Download PDF Full-Text [11829 KB, uploaded 21 October 2013 10:33 CEST]
Abstract: This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments.
Keywords: mobile robots; pose estimation; sensor fusion; Kalman filtering; inertial sensors; robot sensing systems; dynamic model; embedded systems; global positioning systems; event based systems

Article Statistics

Load and display the download statistics.

Citations to this Article

Cite This Article

MDPI and ACS Style

Marín, L.; Vallés, M.; Soriano, Á.; Valera, Á.; Albertos, P. Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots. Sensors 2013, 13, 14133-14160.

AMA Style

Marín L, Vallés M, Soriano Á, Valera Á, Albertos P. Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots. Sensors. 2013; 13(10):14133-14160.

Chicago/Turabian Style

Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro. 2013. "Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots." Sensors 13, no. 10: 14133-14160.

Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert