Increasing GPS Localization Accuracy With Reinforcement Learning

2020 ◽  
pp. 1-12
Author(s):  
Ethan Zhang ◽  
Neda Masoud
Keyword(s):  
Reinforcement Learning ◽  
Localization Accuracy ◽  
Gps Localization

Improved GNSS Localization with the Use of DOP Parameter

2014 ◽  
Vol 611 ◽  
pp. 450-466 ◽  
Author(s):  
František Duchoň ◽  
Jaroslav Hanzel ◽  
Andrej Babinec ◽  
Jozef Rodina ◽  
Peter Paszto ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Mobile Robots ◽  
Reference Frame ◽  
Small Scale ◽  
Localization Error ◽  
Localization Accuracy ◽  
Gnss Receiver ◽  
Gps Localization

This paper presents the approach to improve localization based on GNSS. The principles of the GPS localization and impact of the DOP parameter on localization error are mathematically analyzed. The algorithm based on the use of DOP parameter and Kalman filter for the improvement of the localization accuracy suitable for small scale outdoor mobile robots and other outdoor applications is proposed. The applicability of the proposed methodology was verified by performed experiments with two common cheap miniature GPS modules and accurate high-end GNSS receiver used as a reference frame for the measurements. The obtained results affirmed the improvement of the localization accuracy.

Improving the Localization Accuracy of Virtual Sound Source through Reinforcement Learning

2013 ◽  
Author(s):  
Manabu Washizu ◽  
Shuhei Morioka ◽  
Isao Nambu ◽  
Shohei Yano ◽  
Haruhide Hokari ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Sound Source ◽  
Localization Accuracy

GPS Localization Accuracy Classification: A Context-Based Approach

2013 ◽  
Vol 14 (1) ◽  
pp. 262-273 ◽  
Author(s):  
Nabil M. Drawil ◽  
Haitham M. Amar ◽  
Otman A. Basir
Keyword(s):  
Localization Accuracy ◽  
Gps Localization

Role of pinnae and head movements in localizing pure tones 1The authors would like to thank Mr. Remi Humbert for implementing the experiment in Turbo Pascal and for his further assistance.

1999 ◽  
Vol 58 (3) ◽  
pp. 170-179 ◽  
Author(s):  
Barbara S. Muller ◽  
Pierre Bovet
Keyword(s):  
Sound Source ◽  
Head Movement ◽  
Movement Analysis ◽  
Head Movements ◽  
Sound Sources ◽  
Localization Accuracy ◽  
Sound Effects ◽  
Posterior Quadrant ◽  
Localization Performance ◽  
Pure Tones

Twelve blindfolded subjects localized two different pure tones, randomly played by eight sound sources in the horizontal plane. Either subjects could get information supplied by their pinnae (external ear) and their head movements or not. We found that pinnae, as well as head movements, had a marked influence on auditory localization performance with this type of sound. Effects of pinnae and head movements seemed to be additive; the absence of one or the other factor provoked the same loss of localization accuracy and even much the same error pattern. Head movement analysis showed that subjects turn their face towards the emitting sound source, except for sources exactly in the front or exactly in the rear, which are identified by turning the head to both sides. The head movement amplitude increased smoothly as the sound source moved from the anterior to the posterior quadrant.

Bayes factors for reinforcement-learning models of the Iowa gambling task.

Decision ◽  
2016 ◽  
Vol 3 (2) ◽  
pp. 115-131 ◽  
Author(s):  
Helen Steingroever ◽  
Ruud Wetzels ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Reinforcement Learning ◽  
Iowa Gambling Task ◽  
Bayes Factors ◽  
Gambling Task ◽  
Learning Models ◽  
Reinforcement Learning Models
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