CMSC828F  Spring 2006

 Advanced Topics in Information Processing: Perceptual Robotics

Instructors: Cornelia Fermller and Abhijit Ogale
Contact: fer at cfar.umd.edu  in AVW 4459

 ogale at cs.umd.edu in AVW 4403

Time/ Location: M: 4:00 - 6:45pm CSI 1122 

 

This class focuses on the study of spatial representations which a robot uses to map the environment and execute navigational tasks. In the Robotics literature this problem is referred to as SLAM (simultaneous localization and mapping) . It requires the integration of different cognitive modalities, such as perception, mapping and planning. The emphasis of this class lies in the exploration of meaningful visual representations to build with other tools from Robotics environmental maps. We will  study an develop tools for Control, Visual Localization, Mapping and Planning by means of a number of projects  and finally build SLAM programs.


 

Books :
Introduction to Autonomous Mobile Robots.  Roland Siegwart and Illah R. Nourbakhsh, MIT Press 2004  (recommended)

Principles of Robot Motion: Theory, Algorithms and Implementations. H. Choset, K. M. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. E Kavraki, and S. Thrun, MIT Press, 2005

Probabilistic Robotics. Sebastian Thrun, Wolfram Burgard, and Dieter  Fox, MIT Presss 2005

Introduction to AI Robotics. Robin R. Murphy, MIT Press 2000.

Planning and Control. Thomas L. Dean and Michael P. Wellman, Morgan Kaufmann Publishers, 1991.


Mobile Robotics: A Practical Introduction. Ulrich Nehmzow, Springer Verlag 1999.

Vehiles: Experiments in Synthetic Psychology. Valentino Braitenberg, MIT Press paperback edition 1986

 

  Software :

        Matlab software for controlling the ER1, reading the infrared data  and reading images : (matlabRobot)

        Drivers for ibot-camera : drivers

         Infrared sensor code : zip-file

 

 

 

Lectures:

    1/30:    Introduction

    2/6 : Locomotion and Robot Kinematics : Chapter 2 and 3  Siegwart and  Nourbakhsh; (powerpoint slides from UPenn 1,2,3)

    2/13 : Introduction to Control (Dean and Michael P. Wellman  Chapters 1 ,2 and 4, pdf- file ) and Description of Project 1

    2/20:  Talk by George Kantor on DEPTHX and Introduction to Kalman filtering (pdf-file)

    2/27: Bayesian filters and Particle filters ( Chapter 9 from  Principles of Robot Motion Theory, Algorithms and Implementations (hand-out)) ,   

               see also (Fox et. al. pdf),  Image calibration (ppt)

    3/6 : Vision : Image filtering (filter.ppt, filter2.ppt), Edge detection, Corner detection, Hough transform (ppt), Image motion (ppt)

    3/13: Description of Project 2, Summary of papers by B. Kuipers on the Spatial Semantic Hierarchy (ppt)

    3/27: Epipolar geometry (ppt), SIFT features (tutorial, paper by Lowe)

    4/3: Interpretation of 3D motion fields (ppt) , 3D motion from normal flow (ppt), Stereo

Projects:

    Project 1: A simulator for obstacle avoidance (Proj1)

    Project2: Localization with particle filters using IR sensor and Vision (Proj2)

 

 

Final Exam:

   Friday 5/19 :    1:30 - 3:30