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Sensors 2016, 16(5), 749; doi:10.3390/s16050749

Integrated Navigation System Design for Micro Planetary Rovers: Comparison of Absolute Heading Estimation Algorithms and Nonlinear Filtering

1
Department of Robotics and Virtual Engineering, Korea University of Science and Technology (UST), Daejon 305-333, Korea
2
Robotics R & BD Group, Korea Institute of Industrial Technology (KITECH), Ansan 426-791, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Stefano Mariani
Received: 23 March 2016 / Revised: 10 May 2016 / Accepted: 17 May 2016 / Published: 23 May 2016
(This article belongs to the Collection Modeling, Testing and Reliability Issues in MEMS Engineering)

Abstract

This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level. View Full-Text
Keywords: planetary rovers navigation; absolute heading angle estimation; multi-sensor fusion; Sun sensor; Extended Kalman filter; Unscented Kalman filter planetary rovers navigation; absolute heading angle estimation; multi-sensor fusion; Sun sensor; Extended Kalman filter; Unscented Kalman filter
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. (CC BY 4.0).

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MDPI and ACS Style

Ilyas, M.; Hong, B.; Cho, K.; Baeg, S.-H.; Park, S. Integrated Navigation System Design for Micro Planetary Rovers: Comparison of Absolute Heading Estimation Algorithms and Nonlinear Filtering. Sensors 2016, 16, 749.

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