CISC849 S2011

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Course information

  • Title CISC849 Environmental Robotics & Vision for Animal Behavior Analysis
  • Description We will examine the increasing use of robots and computer vision for environmental monitoring and animal behavior analysis, both in the field and in the laboratory. In recent years, autonomous ground, air, and underwater vehicles equipped with a wide array of sensors have been deployed under ice sheets, on the flanks of volcanoes, and high in forest canopies in order to collect climate and geological data. At the same time, automatic mining of video from cameras pointed at bird nests, insects in flight, and lab mice has created an exciting new tool for biology research. The course will survey sensors, algorithms, and applications through readings, presentations, and projects.
  • When Tuesdays and Thursdays, 2-3:15 pm
  • Where Smith 102A
  • Instructor Christopher Rasmussen, 446 Smith Hall,
  • Office hours Tuesdays 3:15-4:15 pm, Thursdays 12-1 pm
  • Grading:
    • 10% Find, describe ER/VABA system not in introductory lecture or on course page as of 2/15 (2 pages). Subject to instructor approval, you may later use this for presentation.
    • 20% Oral paper presentation (individual, 30 minutes)
    • 30% Two programming assignments
    • 40% Final project (teams 1-3)
      • 5% = 2 page proposal, including planned methods, citations of relevant papers, data sources, and division of labor
      • 5% = Milestone reports
      • 10% = Joint 15-minute presentation on final results, with accompanying slides
      • 20% = Actual results and estimated effort, factoring in difficulty of problem tackled



Note: The blue squares in the "#" column below indicate Tuesdays.

# Date Topic Notes Links/Readings Assignments
1 Feb. 8 Course introduction I * Dennis Hong's TED 2010 talk Va. Tech. robot mechanisms: leg/wheel hybrid, climber for geology, crab, amoeba, hand, snake, humanoid (0'-12')
2 Feb. 10 Course introduction II Lecture slides
3 Feb. 15 Measuring simple environmental variables with sensor networks; basic field methods including transects Lecture slides
4 Feb. 17 Sensor networks for automatic detection/localization Tracking/triangulating zebras, badgers, marmots


5 Feb. 22

Register/add deadline Feb. 21

Filtering detections with advanced recognition techniques Bird call recognition, bird nest image analysis


Description of unlisted ER/VABA system due
6 Feb. 24 Vision tutorial, introduction to OpenCV Background subtraction, tracking


* "High-throughput ethomics in large groups of Drosophila" HW #1 (vision)
7 Mar. 1 Guest lecture on AUVs: Prof. Art Trembanis
8 Mar. 3 More on computer vision algorithms/OpenCV
9 Mar. 8 Simultaneous Localization and Mapping (SLAM) HW #1 due
10 Mar. 10 3-D mapping and modeling


HW #2 (SLAM)
11 Mar. 15 Visual odometry, mapping for UAVs


12 Mar. 17 Case study: Mars rovers
13 Mar. 22 Multi-robot forest monitoring proposal


HW #2 due
14 Mar. 24 More on forest monitoring, trail following


Paper presentation choice due
Mar. 29 NO CLASS
Spring break
Mar. 31 NO CLASS
Spring break
Instructor away
15 Apr. 7

National Robotics Week demo in Washington D.C., April 9-11

Student presentations: P. Saponaro
16 Apr. 12 Student presentations: A. Landwehr, J. Landwehr
17 Apr. 14

Withdraw deadline Apr. 18

Student presentations: J. Ye, V. Ly Final project proposals due
18 Apr. 19 Student presentations: Y. Lu, M. Kocamaz
19 Apr. 21 Student presentations: P. Kannappan, C. Thorpe
20 Apr. 26 Student presentations: G. Su
21 Apr. 28 Kinect body pose recognition


"Real-Time Human Pose Recognition in Parts from Single Depth Images", J. Shotton et al., CVPR 2011

22 May 3 Project milestone 1 presentations
23 May 5 Footstep planning on rough terrain


"Learning locomotion over rough terrain using terrain templates", M. Kalakrishnan et al., IROS 2009

24 May 10 Project milestone 2 presentations
25 May 12 Applications of learning by demonstration Slides Final project due
26 May 17 Project presentations