© sebastian thrun, CMU, 20001 CS226 Statistical Techniques In Robotics Sebastian Thrun (Instructor) and Josh Bao (TA)

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Presentation transcript:

© sebastian thrun, CMU, CS226 Statistical Techniques In Robotics Sebastian Thrun (Instructor) and Josh Bao (TA) Office: Gates 154, Office hours: Monday 1:30-3pm

© sebastian thrun, CMU, Warm-Up Assignment: Localization, Due Sept 23

© sebastian thrun, CMU, Warm-Up Assignment: Localization

© sebastian thrun, CMU, Warm-Up Assignment: Localization

© sebastian thrun, CMU, 20005

6 Bayes Filters x = state d = data m = map t = time z = observation u = control [Kalman 60, Rabiner 85] Bayes Markov

© sebastian thrun, CMU, Nature of Odometry Data

© sebastian thrun, CMU, Probabilistic Kinematics map m

© sebastian thrun, CMU, Nature of Sensor Data

© sebastian thrun, CMU, laser datap(o|s,m) Probabilistic Range Sensing

© sebastian thrun, CMU, Posterior Probability (Single Scan) p(o|s,m) observation o

© sebastian thrun, CMU, Grid Approximations

© sebastian thrun, CMU, Markov Localization in Grid Map

© sebastian thrun, CMU, Monte Carlo Localization

© sebastian thrun, CMU, Sample Approximations

© sebastian thrun, CMU, Monte Carlo Localization, cont’d

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