Proseminar Robot Learning - WS 2014/15

Proseminar Robot Learning

• Organizer: Prof Dr. Wolfram Burgard
• Co-Organizers: Andreas Eitel, Nichola Abdo, Markus Kuderer, Ayush Dewan, Chau Do, Tim Welschehold.
• The Proseminar will be held as a "Blockseminar" in February 2015 (there will be a doodle with all participants).
• Please register via the online registration system.
• The first meeting was on Tuesday, October 28, 10.00 a.m. in room 02-017, building 52 .
• Students are requested to prepare a talk of 30 minutes and to write a summary. Both can be done in English or German.
• Topics will be assigned in the first meeting. Please contact your supervisor for details on literature.
• The summaries should be 7 pages long at maximum (latex, a4wide, 11pt) not counting the bibliography and figures. Significantly longer summaries will not be accepted. A LaTeX template can be downloaded here.

• Please fill out the assignment form and hand it to Andreas Eitel until Friday, October 31 in room 1006 (UG), building 79 .
• Slides from the first meeting.
  
• Please contact your supervisor for details on literature.

Updated Information

• Wolfram Burgard will give a lecture on "How to give a presentation".
  This lecture will take place on Wednesday, January 14, 10.00 s.t. in room 00-034, building 51.
• The Proseminar will take place on:
• February 2, 9.00 to 12.00.
• Location for the Proseminar: Room 00-014 , Building 078
• Students will be assigned to one meeting, a detailed schedule will be announced soon.
• The first version of the summary must be sent to the superviser on 13.Feb.2013. You can revise the summary once according to the comments of your supervisor. The final version has to be submitted by 20.Feb.2013.

Papers

1. E. Klingbeil, B. Carpenter, O. Russakovsky, and A.Y. Ng.
   Autonomous Operation of Novel Elevators for Robot Navigation
   ICRA 2010.
   material: Markov models and hidden Markov models, introduction to hidden Markov models , EM algorithm
   [supervisor: Wolfram Burgard]
   
   
2. E. Brunskill, T. Kollar and N. Roy.
   Topological Mapping Using Spectral Clustering and Classification
   IROS 2007.
   material: spectral clustering, boosting tutorial
   [supervisor: Nichola Abdo]
   
   
3. M. Bennewitz, W. Burgard and S. Thrun.
   Using EM to Learn Motion Behaviors of Persons with Mobile Robots
   ICRA 2002.
   material: learning motion patterns of persons, EM algorithm
   [supervisor: Wolfram Burgard]
   
   
4. B. Ziebart et al.
   Planning-based Prediction for Pedestrians
   IROS 2009.
   material: maximum entropy inverse reinforcement learning
   [supervisor: Markus Kuderer]
   
   
5. J.P. Mendoza, M. Veloso and R. Simmons.
   Motion Interference Detection in Mobile Robots
   IROS 2012.
   material: hidden Markov models
   [supervisor: Chau Do]
   
   
6. M. Gemici and A. Saxena.
   Learning Haptic Representation for Manipulating Deformable Food Objects
   IROS 2014.
   material: Dirichlet process, support vector regression
   [supervisor: Andreas Eitel]
   
   
7. A. Boularias, O. Kroemer and J. Peters.
   Learning Robot Grasping from 3-D Images with Markov Random Fields
   IROS 2011.
   material: learning associative Markov networks , discriminative learning of Markov random fields
   [supervisor: Andreas Eitel]
   
   
8. I. Lenz, H. Lee and A. Saxena.
   Deep Learning for Detecting Robotic Grasps
   RSS 2013.
   material: UFLDL tutorial, section: sparse autoencoder
   [supervisor: Andreas Eitel]
   
   
9. A. Ijspeert, J. Nakanishi and S. Schaal.
   Movement Imitation with Nonlinear Dynamical Systems in Humanoid Robots
   ICRA 2002.
   [material: locally weighted regression
   [supervisor: Nichola Abdo]
   
   
10. P. Pastor, H. Hoffmann, T. Asfour and S. Schaal.
    Learning and Generalization of Motor Skills by Learning from Demonstration
    ICRA 2009.
    material: least squares, dyanmic movement primitives
    [supervisor: Tim Welschehold]
    
    
11. S. Calinon, Z. Li, J.G. Rogers and H.I. Christensen.
    A Conditional Random Field Model for Place and Object Classification
    ICRA 2012.
    material: introduction to conditional random fields , relevance vector machine , bag of words
    [supervisor: Ayush Dewan]
    
    
12. L. Bo, X. Ren and D. Fox.
    Unsupervised Feature Learning for RGB-D Based Object Recognition
    ISER 2012.
    material: hierarchical matching pursuit , orthogonal matching pursuit
    [supervisor: Ayush Dewan]