Monte Carlo localization

Results: 49



#Item
1Simultaneous Learning of Motion and Sensor Model Parameters for Mobile Robots Teddy N. Yap, Jr. and Christian R. Shelton Department of Computer Science and Engineering University of California, Riverside, CA 92521, USA {

Simultaneous Learning of Motion and Sensor Model Parameters for Mobile Robots Teddy N. Yap, Jr. and Christian R. Shelton Department of Computer Science and Engineering University of California, Riverside, CA 92521, USA {

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Source URL: rlair.cs.ucr.edu

Language: English - Date: 2011-01-19 19:25:14
2Vision-Based Cognition of a Humanoid Robot in Standard Platform Robot Soccer Somchaya Liemhetcharat 1 , Brian Coltin 2 , and Manuela Veloso 3 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213, US

Vision-Based Cognition of a Humanoid Robot in Standard Platform Robot Soccer Somchaya Liemhetcharat 1 , Brian Coltin 2 , and Manuela Veloso 3 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213, US

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Source URL: somchaya.org

Language: English - Date: 2014-05-05 11:43:56
3Localization on OpenStreetMap Data using a 3D Laser Scanner Philipp Ruchti Bastian Steder Abstract— To determine the pose of a vehicle is a fundamental problem in mobile robotics. Most approaches relate the

Localization on OpenStreetMap Data using a 3D Laser Scanner Philipp Ruchti Bastian Steder Abstract— To determine the pose of a vehicle is a fundamental problem in mobile robotics. Most approaches relate the

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Source URL: europa2.informatik.uni-freiburg.de

Language: English - Date: 2015-09-26 09:44:03
4Robot Navigation in Hand-Drawn Sketched Maps Federico Boniardi Bahram Behzadian Wolfram Burgard

Robot Navigation in Hand-Drawn Sketched Maps Federico Boniardi Bahram Behzadian Wolfram Burgard

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Source URL: europa2.informatik.uni-freiburg.de

Language: English - Date: 2015-09-26 10:08:24
5Relative Topometric Localization in Globally Inconsistent Maps Mladen Mazuran, Federico Boniardi, Wolfram Burgard, and Gian Diego Tipaldi Abstract Mobile robot localization is a mature field that over the years has demon

Relative Topometric Localization in Globally Inconsistent Maps Mladen Mazuran, Federico Boniardi, Wolfram Burgard, and Gian Diego Tipaldi Abstract Mobile robot localization is a mature field that over the years has demon

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Source URL: europa2.informatik.uni-freiburg.de

Language: English - Date: 2015-11-26 06:02:31
6ETHZ D-INFK Prof. Dr. B. Meyer, Dr. J. Shin Robotics Programming Laboratory – Assignments Fall 2013

ETHZ D-INFK Prof. Dr. B. Meyer, Dr. J. Shin Robotics Programming Laboratory – Assignments Fall 2013

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Source URL: se.inf.ethz.ch

Language: English - Date: 2013-10-28 19:47:49
7Sequential Monte Carlo for Simultaneous Passive Device-Free Tracking and Sensor Localization Using Received Signal Strength Measurements Xi Chen Andrea Edelstein

Sequential Monte Carlo for Simultaneous Passive Device-Free Tracking and Sensor Localization Using Received Signal Strength Measurements Xi Chen Andrea Edelstein

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Source URL: www.ece.mcgill.ca

Language: English - Date: 2011-04-19 17:56:25
    8σ MCL: Monte-Carlo Localization for Mobile Robots with Stereo Vision Pantelis Elinas and James J. Little Computer Science Department University of British Columbia Vancouver, BC, Canada, V6T 1Z4

    σ MCL: Monte-Carlo Localization for Mobile Robots with Stereo Vision Pantelis Elinas and James J. Little Computer Science Department University of British Columbia Vancouver, BC, Canada, V6T 1Z4

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    Source URL: www.roboticsproceedings.org

    Language: English - Date: 2015-06-22 09:52:54
      9Pose Estimation for Contact Manipulation with Manifold Particle Filters Michael C. Koval Mehmet R. Dogar Nancy S. Pollard

      Pose Estimation for Contact Manipulation with Manifold Particle Filters Michael C. Koval Mehmet R. Dogar Nancy S. Pollard

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      Source URL: www.ri.cmu.edu

      Language: English - Date: 2013-05-18 23:41:21
      10Vehicle Self-localization with High-Precision Digital Maps Andreas Schindler Abstract— Cooperative driver assistance functions benefit from sharing information on the local environments of individual road users by mean

      Vehicle Self-localization with High-Precision Digital Maps Andreas Schindler Abstract— Cooperative driver assistance functions benefit from sharing information on the local environments of individual road users by mean

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      Source URL: www.forwiss.uni-passau.de

      Language: English - Date: 2013-08-07 02:22:36