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

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

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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)
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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 mobile robots; pose estimation; sensor fusion; Kalman filtering; inertial sensors; robot sensing systems; dynamic model; embedded systems; global positioning systems; event based systems
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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.


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