Transcription of Introduction to SLAM Simultaneous Localization And Mapping
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Introduction to SLAM Simultaneous Localization And Mapping
Introduction to SLAMS imultaneous LocalizationAnd Mapping Paul RobertsonCognitive RoboticsWed Feb 9th, 2005 Outline Introduction Localization SLAM KalmanFilter Example Large SLAM Scaling to large maps2 Introduction3 ( Localization ) Robot needs to estimate its location with respects to objects in its environment (Map provided). ( Mapping ) Robot need to map the positions of objects that it encounters in its environment (Robot position known) (SLAM) Robot simultaneously maps objects that it encounters and determines its position (as well as the position of the objects) using noisy Movie4 Localization Tracking Bounded uncertainty Can flip into kidnapping problem Global Localization Initially huge uncertainties Degenerates to tracking Kidnapping Problem Unexpected global localizationTrackingGlobalLocalizationKi dnapped5 Representing RobotsPosition of robot is represented as a triple consisting of its xt, ytcomponents and its heading t.
Simultaneous Localization And Mapping Paul Robertson Cognitive Robotics Wed Feb 9th, 2005. Outline • Introduction • Localization •SLAM • Kalman Filter –Example • Large SLAM – Scaling to large maps 2. Introduction 3 • (Localization) Robot needs to estimate its
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