Abstract
Consider the two characteristics: (1) Simultaneous localization and mapping (SLAM) is a popular algorithm for autonomous underwater vehicle, but visual SLAM is significantly influenced by weak illumination. (2) Geomagnetism-aided navigation and gravity-aided navigation are equally important methods in the field of vehicle navigation, but both are affected heavily by time-varying noises and terrain fluctuations. However, magnetic gradient vector can avoid the influence of time-varying noises, and is less affected by terrain fluctuations. To this end, we propose an adaptive SLAM-based magnetic gradient aided navigation with the following advantages: (1) Adaptive SLAM is an efficient way to deal with uncertainty of the measurement model. (2) Magnetic gradient inversion equation is a good alternative to be used as measurement equation in visual SLAM-denied environment. Experimental results show that our proposed method is an effective solution, combining magnetic gradient information with SLAM.
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Wu, M., Yao, J. (2015). Adaptive UKF-SLAM Based on Magnetic Gradient Inversion Method for Underwater Navigation. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2015. Lecture Notes in Computer Science(), vol 9245. Springer, Cham. https://doi.org/10.1007/978-3-319-22876-1_21
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DOI: https://doi.org/10.1007/978-3-319-22876-1_21
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