Artificial Intelligence for Robotics

Course Book

• http://www.probabilistic-robotics.org/

• Localization
• 1 - Introduction
• 2 - Localization
• 3 - Total Probability
• 4 - Uniform Probability Quiz
• 5 - Uniform Probability Quiz Solution
• 6 - Uniform Distribution
• 7 - Uniform Distribution Solution
• 8 - Generalized Uniform Distribution
• 9 - Generalized Uniform Distribution Solution
• 10 - Probability After Sense
• 11 - Probability After Sense Solution
• 12 - Compute Sum
• 13 - Compute Sum Solution
• 14 - Normalize Distribution
• 15 - Normalize Distribution Solution
• 16 - pHit and pMiss
• 17 - pHit and pMiss Solution
• 18 - Sum of Probabilities
• 19 - Sum of Probabilities Solution
• 20 - Sense Function
• 21 - Sense Function Solution
• 22 - Normalized Sense Function
• 23 - Normalized Sense Function Solution
• 24 - Test Sense Function
• 25 - Test Sense Function Solution
• 26 - Multiple Measurements
• 27 - Multiple Measurements Solution
• 28 - Exact Motion
• 29 - Exact Motion Solution
• 30 - Move Function
• 31 - Move Function Solution
• 32 - Inexact Motion 1
• 33 - Inexact Motion 1 Solution
• 34 - Inexact Motion 2
• 35 - Inexact Motion 2 Solution
• 36 - Inexact Motion 3
• 37 - Inexact Motion 3 Solution
• 38 - Inexact Move Function
• 39 - Inexact Move Function Solution
• 40 - Limit Distribution Quiz
• 41 - Limit Distribution Quiz Solution
• 42 - Move Twice
• 43 - Move Twice Solution
• 44 - Move 1000
• 45 - Move 1000 Solution
• 46 - Sense and Move
• 47 - Sense and Move Solution
• 48 - Sense and Move 2
• 49 - Sense and Move 2 Solution
• 50 - Localization Summary
• 51 - Formal Definition of Probability 1
• 52 - Formal Definition of Probability 1 Solution
• 53 - Formal Definition of Probability 2
• 54 - Formal Definition of Probability 2 Solution
• 55 - Formal Definition of Probability 3
• 56 - Formal Definition of Probability 3 Solution
• 57 - Bayes’ Rule
• 58 - Cancer Test
• 59 - Cancer Test Solution
• 60 - Theorem of Total Probability
• 61 - Coin Flip Quiz
• 62 - Coin Flip Quiz Solution
• 63 - Two Coin Quiz
• 64 - Two Coin Quiz Solution
• Terms
• Resources
• 1 - Probability
• 2 - Probability Solution
• 3 - Localization
• 4 - Localization Solution
• 5 - Bayes’ Rule
• 6 - Bayes’ Rule Solution
• 7 - Localization Program
• 8 - Localization Program Solution
• 9 - Congratulations
• 1 - Office Hours Week 1
• Kalman Filters
  • Introduction
    • Stanley: The Robot that Won the DARPA Grand Challenge
  • Tracking intro
  • Gaussian Intro
  • Variance Comparison
  • Preferred Gaussian
  • Evaluate Gaussian
  • Maximize Gaussian
  • Measurement and Motion 1
    • Kalman Filter
  • Measurement and Motion 2
  • Shifting the mean
  • Predicting the Peak
  • Parameter Update
  • Parameter Update 2
  • Separated Gaussians
  • New Mean and Variance
  • Gaussian Motion
  • Predict Function
  • Kalman Filter Code
  • Kalman Prediction
  • Kalman Filter Land
  • Kalman Filter Prediction
  • Another Prediction
  • More Kalman Filters
  • Kalman Filter Design
• 1 - Introduction
• 2 - Tracking Intro
• 3 - Tracking Intro Solution
• 4 - Gaussian Intro
• 5 - Gaussian Intro Solution
• 6 - Variance Comparison
• 7 - Variance Comparison Solution
• 8 - Preferred Gaussian
• 9 - Preferred Gaussian Solution
• 10 - Evaluate Gaussian
• 11 - Evaluate Gaussian Solution
• 12 - Maximize Gaussian
• 13 - Maximize Gaussian Solution
• 14 - Measurement and Motion 1
• 15 - Measurement and Motion 1 Solution
• 16 - Measurement and Motion 2
• 17 - Measurement and Motion 2 Solution
• 18 - Shifting the Mean
• 19 - Shifting the Mean Solution
• 20 - Predicting the Peak
• 21 - Predicting the Peak Solution
• 22 - Parameter Update
• 23 - Parameter Update Solution
• 24 - Parameter Update 2
• 25 - Parameter Update 2 Solution
• 26 - Separated Gaussians
• 27 - Separated Gaussians Solution
• 28 - Separated Gaussians 2
• 29 - Separated Gaussians 2 Solution
• 30 - New Mean and Variance
• 31 - New Mean and Variance Solution
• 32 - Gaussian Motion
• 33 - Gaussian Motion Solution
• 34 - Predict Function
• 35 - Predict Function Solution
• 36 - Kalman Filter Code
• 37 - Kalman Filter Code Solution
• 38 - Kalman Prediction
• 39 - Kalman Prediction Solution
• 40 - Kalman Filter Land
• 41 - Kalman Filter Prediciton
• 42 - Kalman Filter Prediciton Solution
• 43 - Another Prediction
• 44 - Another Prediction Solution
• 45 - More Kalman Filters
• 46 - Kalman Filter Design
• 47 - Kalman Matrices
• 48 - Kalman Matrices Solution
• 49 - Conclusion
• Kalman Filter Notes
• 1 - Measurement Update
• 2 - Measurement Update Solution
• 3 - New Variance
• 4 - New Variance Solution
• 5 - Heavytail Gaussian
• 6 - Heavytail Gaussian Solution
• 7 - How Many Dimensions
• 8 - How Many Dimensions Solution
• 9 - State Transition Matrix
• 10 - State Transition Matrix Solution
• 11 - Programming Exercise
• 12 - Programming Exercise Solution
• 13 - Congratulations
• 1 - Office Hours Week 2
• Particle Filters
  • Field Trip
  • State Space, Belief, Efficiency
  • Using Robot Class
  • Filters
  • Robot Movement
• 1 - Field Trip
• 2 - State Space
• 3 - State Space Solution
• 4 - Belief Modality
• 5 - Belief Modality Solution
• 6 - Efficiency
• 7 - Efficiency Solution
• 8 - Exact or Approximate
• 9 - Exact or Approximate Solution
• 10 - Particle Filters
• 11 - Using Robot Class
• 12 - Robot Class Details
• 13 - Moving Robot
• 14 - Moving Robot Solution
• 15 - Add Noise
• 16 - Add Noise Solution
• 17 - Robot World
• 18 - Creating Particles
• 19 - Creating Particles Solution
• 20 - Robot Particles
• 21 - Robot Particles Solution
• 22 - Importance Weight
• 23 - Importance Weight Solution
• 24 - Resampling
• 25 - Resampling Solution
• 26 - Never Sampled 1
• 27 - Never Sampled 1 Solution
• 28 - Never Sampled 2
• 29 - Never Sampled 2 Solution
• 30 - Never Sampled 3
• 31 - Never Sampled 3 Solution
• 32 - New Particle
• 33 - New Particle Solution
• 34 - Resampling Wheel
• 35 - Resampling Wheel Solution
• 36 - Orientation 1
• 37 - Orientation 1 Solution
• 38 - Orientation 2
• 39 - Orientation 2 Solution
• 40 - Error
• 41 - Error Solution
• 42 - You and Sebastian
• 43 - Filters
• 44 - Filters Solution
• 45 - 2012
• 46 - Preview
• Particle Filter Notes
• 1 - Empty Cell
• 2 - Empty Cell Solution
• 3 - Motion Question
• 4 - Motion Question Solution
• 5 - Single Particle
• 6 - Single Particle Solution
• 7 - Circular Motion
• 8 - Circular Motion Solution
• 9 - Sensing
• 10 - Sensing Solution
• 11 - Final Quiz
• 12 - Final Quiz Solution
• 1 - Office Hours Week 3
• Conditional Particle Filters
• Motion Planning
  • Planning Problem
  • Compute Cost
  • Compute Cost 2
  • Optimal Path
  • Optimal Path 2
  • Maze
  • Maze 2
  • First Search Program
• 1 - Motion Planning
• 2 - Compute Cost
• 3 - Compute Cost Solution
• 4 - Compute Cost 2
• 5 - Compute Cost 2 Solution
• 6 - Optimal Path
• 7 - Optimal Path Solution
• 8 - Optimal Path 2
• 9 - Optimal Path 2 Solution
• 10 - Maze
• 11 - Maze Solution
• 12 - Maze 2
• 13 - Maze 2 Solution
• 14 - First Search Program
• 15 - First Search Program Solution
• 16 - Expansion Grid
• 17 - Expansion Grid Solution
• 18 - Print Path
• 19 - Print Path Solution
• 20 - A*
• 21 - Implement A*
• 22 - Implement A* Solution
• 23 - A* in Action
• 24 - Dynamic Programming
• 25 - Computing Value
• 26 - Computing Value Solution
• 27 - Computing Value 2
• 28 - Computing Value 2 Solution
• 29 - Value Program
• 30 - Value Program Solution
• 31 - Optimum Policy
• 32 - Optimum Policy Solution
• 33 - Left Turn Policy
• 34 - Left Turn Policy Solution
• 35 - Planning Conclusion
• Motion Planning Notes
• Problem Set 4
• 1 - Admissible Heuristic
• 2 - Admissible Heuristic Solution
• 3 - Admissible Heuristic 2
• 4 - Admissible Heuristic 2 Solution
• 5 - Bad Heuristic
• 6 - Bad Heuristic Solution
• 7 - Diagonal Motion
• 8 - Diagonal Motion Solution
• 9 - Stochastic Motion
• 10 - Stochastic Motion Solution
• 1 - Office Hours Week 4
• 1 - Robot Motion
• 2 - Robot Motion Solution
• 3 - Smoothing Algorithm
• 4 - Smoothing Algorithm Solution
• 5 - Smoothing Algorithm 2
• 6 - Smoothing Algorithm 2 Solution
• 7 - Smoothing Algorithm 3
• 8 - Smoothing Algorithm 3 Solution
• 9 - Path Smoothing
• 10 - Path Smoothing Solution
• 11 - Zero Data Weight
• 12 - Zero Data Weight Solution
• 13 - PID Control
• 14 - PID Control Solution
• 15 - Proportional Control
• 16 - Proportional Control Solution
• 17 - Implement P Controller - Artificial Intelligence for Robotics
• 18 - Implement P Controller Solution - Artificial Intelligence for Robotics
• 19 - Oscillations
• 20 - Oscillations Solution
• 21 - PD Controller - Artificial Intelligence for Robotics
• 22 - PD Controller Solution - Artificial Intelligence for Robotics
• 23 - Systematic Bias
• 24 - Systematic Bias Solution
• 25 - Is PD Enough
• 26 - Is PD Enough Solution
• 27 - PID Implementation - Artificial Intelligence for Robotics
• 28 - PID Implementation Solution - Artificial Intelligence for Robotics
• 29 - Twiddle
• 30 - Parameter Optimization - Artificial Intelligence for Robotics
• 31 - Parameter Optimization Solution - Artificial Intelligence for Robotics
• 32 - Summary
• PID Notes
• Problem Set 5
• 1 - Missing Parameters
• 2 - Missing Parameters Solution
• 3 - Cyclic Smoothing
• 4 - Cyclic Smoothing Solution
• 5 - Constrained Smoothing
• 6 - Constrained Smoothing Solution
• 7 - Racetrack Control
• 8 - Racetrack Control Solution
• 1 - Office Hours Week 5
• 1 - Putting It All Together
• 2 - Localization
• 3 - Localization Solution
• 4 - Planning
• 5 - Planning Solution
• 6 - PID
• 7 - PID Solution
• 8 - Your Robot Car
• 9 - Segmented CTE
• 10 - Segmented CTE Solution
• 11 - Fun with Parameters
• 12 - Wrap Up
• 13 - SLAM
• 14 - Is Localization Necessary
• 15 - Is Localization Necessary Solution
• 16 - Graph SLAM
• 17 - Graph SLAM Solution
• 18 - Implementing Constraints
• 19 - Implementing Constraints Solution
• 20 - Adding Landmarks
• 21 - Adding Landmarks Solution
• 22 - SLAM Quiz
• 23 - SLAM Quiz Solution
• 24 - Matrix Modification
• 25 - Matrix Modification Solution
• 26 - Untouched Fields
• 27 - Untouched Fields Solution
• 28 - Omega and Xi
• 29 - Omega and Xi Solution
• 30 - Landmark Position
• 31 - Landmark Position Solution
• 32 - Expand
• 33 - Expand Solution
• 34 - Introducing Noise
• 35 - Introducing Noise Solution
• 36 - Confident Measurements
• 37 - Confident Measurements Solution
• 38 - Implementing SLAM
• 39 - Implementing SLAM Solution
• 40 - Congratulations
• SLAM Notes
• 1 - Matrix Fill In
• 2 - Matrix Fill In Solution
• 3 - Online SLAM
• 4 - Online SLAM Solution
• 1 - Office Hours Week 6
• Office Hours
  • CS 8803 AIR Video Office Hours - Feb 6th 2018