CISC367 S2023

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Course information

Title CISC367-012 Introduction to Mobile Robot Programming
Description A hands-on approach to implementing mobile robot algorithms on a small wheeled platform, both in simulation and reality. We will review the fundamentals of kinematics, planning, sensing, and control, as well as getting acquainted with higher-level concepts related to navigation, tracking, mapping, and learning.
When Wednesdays and Fridays, 8:40-9:55 am
Where Smith 102A
Instructor Christopher Rasmussen, 446 Smith Hall, cer@cis.udel.edu
Office hours Wednesdays and Fridays, 9:55-11 am in Smith 211
Grading
  • 16% 3 assignments worth 16% each. Each homework will be due 2 weeks after being assigned.
  • 20% Presentation. 20-minute tutorial or demo of advanced features in ROS and/or PCL (that were not presented in lecture). You can talk about platforms (walking, flying), sensors, planners, perception algorithms, etc. using slides, images, and movies or live code.
  • 32% Project

Programming assignments will be graded on the basis of correctness, efficiency, and originality. This is not an introductory programming class, so coding style is not critical. However, if you want partial credit for something that doesn't quite work, it needs to be well-commented and easy to follow.

For the overall course grade, a preliminary absolute mark will be assigned to each student based on the percentage of the total possible points they earn according to the standard formula: A = 90-100, B = 80-90, C = 70-80, etc., with +'s and -'s given for the upper and lower third of each range, respectively. Based on the distribution of preliminary grades for all students (i.e., "the curve"), the instructor may increase these grades monotonically to calculate final grades. This means that your final grade can't be lower than your preliminary grade, and your final grade won't be higher than that of anyone who had a higher preliminary grade.

I will try to keep you informed about your standing throughout the semester. If you have any questions about grading or expectations at any time, please feel free to ask me.

Academic policies Programming projects are due by midnight of the deadline day (with a grace period of a few hours afterward...after sunrise is definitely late). A late homework is a 0 without a valid prior excuse. To give you a little flexibility, you have 6 "late days" to use on homeworks to extend the deadline by one day each without penalty. No more than three late days may be used per assignment. Late days will automatically be subtracted, but as a courtesy please notify the instructor in an e-mail of your intention to use late days before the deadline.

Assignment submissions should consist of a directory containing all code (your .cpp files, makefile, etc.), any output data generated (e.g., images, movies, etc.), and an explanation of your approach, what worked and didn't work, etc. contained in a separate text or HTML file. Do not submit executables or .o files, please! The directory you submit for each assignment should be packaged by tar'ing and gzip'ing it or just zip'ing it. The resulting file should be e-mailed to the instructor (cer@cis.udel.edu).

Students can discuss problems with one another in general terms, but must work independently on programming assignments. This also applies to online and printed resources: you may consult them as references (as long as you cite them), but the words and source code you turn in must be yours alone. The University's policies on academic dishonesty are set forth in the student code of conduct here.

Instructions

Wifi

This is what all of the robots and SBCs are connected to in Smith 211. You should connect your laptop to it as well in order to communicate with them.

  • SSID: NETGEAR33
  • Username:
  • Password:
Robot

Yes, our robot platform is a Roomba. Except it can't clean.

  • Platform: iRobot Create 3 documentation running ROS2 Humble
  • SBC: Raspberry Pi 4 B running Ubuntu 22.04 and ROS2 Humble
  • Lidar: something else
  • Camera: RealSense D435
Operating system

Working backwards from the ROS requirements there are 3 options...

ROS2

We are using ROS2, to be exact, and the Humble Hawksbill version. My laptop and the Raspberry Pi's on the robots are running Ubuntu, so you will have your best support for this option. I have personally tried installing ROS2 Humble on Windows and it seems to be fine, so I at least have the ability to test things in this environment. I have no access to a Mac and therefore no experience and no ability to help troubleshoot issues there. A lot of public sample code and tutorials are available in both C++ and Python, but expect mostly C++ examples from me. I am agnostic about which of these two languages you use for homeworks and projects, but you will get your best support from me in C++.

Gazebo

This is a 3-D robot simulator


Schedule

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

# Date Topic Notes Readings Assignments/slides
1 Feb. 8 Introduction Background, course information slides
2 Feb. 10 ROS/Gazebo Installation, hello ROS, hello Gazebo slides
3 Feb. 15 ROS/Gazebo Writing simple ROS programs HW #1 (see slides)

slides

4 Feb. 17 ROS/Gazebo Odometry, ground truth positions slides
5 Feb. 22 Motion planning Background, kinematics, PID control slides
6 Feb. 24 Motion planning Homing controllers, occupancy grid and grid-based planning slides
7 Mar. 1 Motion planning Explanation of nav code (ROS costmap_2d and navfn, trajectory following, replanning), putting moving objects in Gazebo world HW #1 due

slides

8 Mar. 3 Motion planning Bug variants, search-based planning slides
9 Mar. 8 Perception Point clouds, estimation (least squares, RANSAC) HW #2 (see slides)
slides
10 Mar. 10 Perception Kinect tilt controller, plane segmentation in PCL slides
11 Mar. 15 Perception Point cloud matching, registration RSS 2011 tutorials on keypoints, range images slides
12 Mar. 17 Perception More details on registration and associated PCL functions
13 Mar. 22
14 Mar. 24 Localization Inference/tracking, Markov localization ETH localization 1 (through slide 31), ETH localization 2 (through slide 41), HW #2 due
14 Oct. 16 Localization Particle filtering, Monte Carlo localization (ROS amcl) Thrun particle filtering slides, U. Tennessee Monte Carlo Localization, Fox et al. AAAI 1999 paper, Nao localization at U. Freiburg
15 Oct. 18 Mapping SLAM (ROS gmapping) Thrun FastSLAM slides, gmapping demo, Darmstadt mapping HW #3
16 Oct. 23 Mapping gmapping details UC Berkeley notes on gmapping, scan-matching Instructions for running gmapping/amcl
17 Oct. 25 Mapping RGB-D SLAM (ROS rgbdslam) RGBD SLAM slides, ICRA 2012 RGBD SLAM paper, U. Texas slides on SIFT features 1, 2
18 Oct. 30 NO CLASS
HW #3 Lab
Sign up page
19 Nov. 1 NO CLASS
HW #3 Lab
Sign up page HW #3 due
Nov. 6 NO CLASS
Election day
20 Nov. 8 Student presentations Sign up page
21 Nov. 13 Student presentations Sign up page
22 Nov. 15 Student presentations Sign up page
23 Nov. 20 Miscellaneous Finish lecture on SIFT features, go over project ideas
Nov. 22 NO CLASS
Thanksgiving
24 Nov. 27 Project lab
25 Nov. 29 Project lab
26 Dec. 4 Project presentations (extra-long class)
NO FINAL EXAM