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Particle Filter/Monte Carlo Localization

Particle Filter/Monte Carlo Localization

Advanced Mobile Robotics. Probabilistic Robotics: . Particle Filter/Monte Carlo Localization. Dr. J izhong Xiao Department of Electrical Engineering CUNY City College jxiao@ccny.cuny.edu. Probabilistic Robotics. Bayes Filter Implementations Particle filters Monte Carlo Localization.

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1.36k views • 80 slides
Lunabotics Navigation Package

Lunabotics Navigation Package

Lunabotics Navigation Package. Team May14-20 Advisor: Dr. Koray Celik Clients: ISU Lunabotics Club, Vermeer Company. Project Scope. NASA Lunabotics Mining Competition For university-level students to design and build a mining robot that can traverse the simulated Martian chaotic terrain

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320 views • 25 slides
Automated Detection of Speech Landmarks Using Gaussian Mixture Modeling A. R. Jayan P. C. Pandey

Automated Detection of Speech Landmarks Using Gaussian Mixture Modeling A. R. Jayan P. C. Pandey

Automated Detection of Speech Landmarks Using Gaussian Mixture Modeling A. R. Jayan P. C. Pandey {arjayan, pcpandey}@ee.iitb.ac.in EE Dept., IIT Bombay February, 2008.

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386 views • 21 slides
Detection of Burst Onset Landmarks in Speech Using Rate of Change of Spectral Moments

Detection of Burst Onset Landmarks in Speech Using Rate of Change of Spectral Moments

Detection of Burst Onset Landmarks in Speech Using Rate of Change of Spectral Moments A. R. Jayan P. S. Rajath Bhat P. C. Pandey { arjayan , rajathbhat , pcpandey }@ ee.iitb.ac.in EE Dept, IIT Bombay 30 th January, 2011. PRESENTATION OUTLINE. 1. Introduction ? Speech landmarks

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375 views • 21 slides
Discriminative Rescoring using Landmarks

Discriminative Rescoring using Landmarks

Discriminative Rescoring using Landmarks. Katrin Kirchhoff. Rationale. WS04 approach: lattice/N-best list rescoring instead of first-pass recognition baseline system already provides high-quality hypotheses 1-best error rate from N-best lists: 24.4% (RT-03 dev set)

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303 views • 19 slides

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