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 {

Source URL: rlair.cs.ucr.edu

• Robot control
• Statistics
• Robot navigation
• Estimation theory
• Engineering
• Artificial intelligence
• Linear filters
• Simultaneous localization and mapping
• Monte Carlo methods
• Kalman filter
• Robot calibration
• Sensor

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

Source URL: somchaya.org

• Robotics
• Humanoid robot
• Mobile robot
• Monte Carlo localization
• Robot
• RoboCup
• Nao
• Artificial intelligence

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

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

• Robot navigation
• Robotic sensing
• Artificial intelligence
• Monte Carlo localization
• Visual odometry
• Geography
• Wolfram Burgard
• Robot
• Occupancy grid mapping
• Mobile robot
• Localization
• Knowledge

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

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

• Robot navigation
• Mobile robot navigation
• Robotics
• Mobile robot
• Robotic mapping
• Robot
• Simultaneous localization and mapping
• Motion planning
• Monte Carlo localization
• Occupancy grid mapping
• Distribution
• Localization

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

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

• Robot navigation
• Artificial intelligence
• Robot control
• Mathematics
• Localization
• Ring theory
• Simultaneous localization and mapping
• Computer vision
• Occupancy grid mapping
• Wolfram Burgard
• Robotic mapping
• Monte Carlo localization

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

Source URL: se.inf.ethz.ch

• Robotics
• Monte Carlo methods
• Robot control
• Robot navigation
• Monte Carlo localization
• Robot Operating System
• Mobile robot
• PrimeSense
• Particle filter
• Robotic mapping
• Kidnapped robot problem
• Robot

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

Source URL: www.ece.mcgill.ca

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

Source URL: www.roboticsproceedings.org

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

Source URL: www.ri.cmu.edu

• Estimation theory
• Robot control
• Linear filters
• Signal processing
• Monte Carlo methods
• Particle filter
• Recursive Bayesian estimation
• Kalman filter
• Simultaneous localization and mapping
• Statistics
• Control theory
• Electronic engineering

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

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

• Navigation
• Satellite navigation systems
• Simultaneous localization and mapping
• Robot control
• Global Positioning System
• Robotic mapping
• Angular mil
• Pi
• Monte Carlo localization
• Technology
• Robot navigation
• Mathematical analysis