2018 IEEE Intelligent Vehicles Symposium (IV) 2018
DOI: 10.1109/ivs.2018.8500610
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Online Adaptive Covariance Estimation Approach for Multiple Odometry Sensors Fusion

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Cited by 7 publications
(10 citation statements)
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“…This paper extends on the authors’ published work in [19]. In [19], the authors introduced the drift error model for wheel encoders and showed the feasibility of using an exteroceptive sensor to determine the covariance of a proprioceptive sensor such as wheel encoders.…”
Section: Introductionmentioning
confidence: 61%
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“…This paper extends on the authors’ published work in [19]. In [19], the authors introduced the drift error model for wheel encoders and showed the feasibility of using an exteroceptive sensor to determine the covariance of a proprioceptive sensor such as wheel encoders.…”
Section: Introductionmentioning
confidence: 61%
“…Visual demonstration of the three scenarios, where the green point is the start point and the blue curve is the path drawn using the LiDAR odometry. The Figure is reproduced from [19] (© 2018 IEEE).…”
Section: Figurementioning
confidence: 99%
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“…In any real-world deployment of robotic systems there is the potential for incurring increasing positional errors over time [99,100]. This is a challenge addressed in various ways in the literature.…”
Section: Motivationmentioning
confidence: 99%