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Lectures

The dates below are old, and the lecture details will change as class progresses.

Note: The notes posted below may not be include all the material covered in the class. Please refer to what was discussed in the actual class.

# DATE TOPIC NOTES
1 Jan 22 Introduction Overview, Topics Overview. Robot Kinematics. pdf
2 Jan 24 Supervised Learning. Gradient descent slides, pdf (part of notes)
3 Jan 29 Supervised Learning Linear Regression, Cross-val testing. knn, linear regression 1, 2. (Slides from Piyush Rai.) (No slides for train/test cross validation.)
4 Jan 31 Robot survival kit Probability view. ROS+Gazebo+PR2 simulator (Sung). slides. Also see Piazza.
5 Feb 5 Supervised Learning Logistic Regression. Newton's method. slides, optional notes
6 Feb 7 Markov Chains Robot state transitions. -
7 Feb 12 Reinforcement Learning Decision making, MDP, Bellman eqns, Value Iteration pdf
8 Feb 14 Reinforcement Learning Policy Iteration, estimating robot transitions. (see previous)
9 Feb 19 Reinforcement Learning Fitted Value Iteration, Value Function approximation (see previous)
10 Feb 21 Path Planning. Potential Field, RRT. pdf
11 Feb 26 Kalman Filters Discrete Time Linear Systems.- pdf
12 Feb 28 Kalman Filters observations, applications to tracking (see previous)
13 Mar 5 Kalman Filters Extended Kalman Filters. pdf
14 Mar 7 Supervised Learning Robotic Perception, Basic Operations, 3D Features. PCL slides
15 Mar 12 Supervised Learning Bag of features (shape-words), 3D algorithms, Point-cloud library PCL (Anand) slides, Also see Piazza.
16 Mar 14 Control Linear systems controllability, PID control. pdf
17 Mar 26 Learning discrete HMM pdf
18 Mar 28 Learning HMM: Inference and Learning (see previous), paper
19 April 2 Applications Kalman and HMM application examples pdf, more
- April 4 Sprint 2 presentations - -
20 April 9 Learning Particle filters. pdf
21 April 11 Particle Filters derivation from Bayes filters (see previous)
22 April 16 Learning Particle Filters (previous)
23 April 18 Review -
Apr 18 Prelim 7:30-10pm. Open notes midterm / no electronic devices. April 18, 2013 (evening)
24 April 23 POMDPs / 5min project group presentations ppt
25 April 25 POMDPs / 5min project group presentations (see previous)
26 April 30 Robot Learning Applications / 5min project group presentations .
27 May 2 Robot Learning Applications / 5min project group presentations .
-- Final poster presentation / demo Thu, May 09, 2013 02:00 PM - 04:30 PM
-- Final written reports due May 15 midnight 2013 (absolutely NO extensions)

Some of these lecture notes have been taken from the following classes: CS223A by Oussama Khatib, CS229 by Andrew Ng.