Spring 2018: ENGR-E502

-- Introduction to Cyber-Physical Systems


  • Instructor: Prof. Lantao Liu (lantao@iu.edu)
  • Time: Tu/Th 9:30am-10:45pm
  • Location: Geology (GY) 436
  • Office hours: by appointment

The syllabus can be found here

Note: this page and the syllabus may be updated from time to time.

Course description:
Cyber-Physical Systems (CPS) integrate computation, networking, and physical processes. The CPS involve transdisciplinary technologies and are typically regarded as "smart" systems. This course covers a broad range of CPS with both uses and component technologies. Computational algorithms, dynamical systems, control, formal analysis, sensor networks, and mechanical construction issues will be included. Particularly, topics related to real-world applications such as autonomous robots and smart systems will be discussed. Lab sessions and hand-on experience will also be an essential part of course. Students need to work on projects based on popular simulation platforms or robotics platforms such as Turtlebot3 and nano-quadrotors.
Prerequisites
No particular course is a prerequisite. However, a good knowledge of Calculus, Linear Algebra, or Probability Analysis will make your learning process faster. Familiarity with C/C++ or python and GNU/Linux environment will be beneficial. Enrollment is open to all graduate students and certain senior undergraduate students (undergraduate students will need the instructor's approval).
Final exam
None. But there will be a term project.
Justification:
Intelligent Systems Engineering is a new department and a new major at IU. It is required that all graduate students take one of the E501-E507 Sequence. This course is for students who are interested in the Cyber-Physical Systems (CPS) Track of the Masters or Ph.D. in Intelligent Systems Engineering.
What you will learn in the course
When students complete this course, they should be able to:
  • Have a basic understanding of issues involved in engineering cyber-physical systems, especially robots and intelligent systems.
  • Apply knowledge of mathematics, science, and engineering.
  • Apply knowledge of mathematics, science, and engineering.
  • Understand research challenges and important application areas of Cyber-physical systems.
  • Gain hands-on laboratory experience with CPS systems
  • Have introductory skills in teamwork with peers.
  • Have a broad knowledge of CPS as seen in practical engineering and in the department's research. This should advance their ability to choose a research topic for Ph.D. students.
Class Projects
Each student is required to complete a big final term project as well as several mini-projects. The final project topic requires instructor's approval, so each student will need to consult with me before making a decision on the topic. You are encouraged to select a topic that fits well with your background and research interests, so talk to your research advisor to narrow down the potential topics. Finally, every student will submit a final report in the research paper style/tone and give a final project presentation by the end of the course.

Teaming work (2-3 people in a team, depending on the “size” of the project) is absolutely acceptable. In fact collaboration is encouraged. Specifically, during the course students are encouraged to work with each other, exchanging thoughts/understanding of the papers, explaining your own ideas and making suggestions to others. Many good ideas are inspired from discussions.
Course Grading
  • (10%) Class attendance and involvement
  • (40%) Assignments and mini-projects
  • (50%) Final project, presentation, and report
Useful books
Hardcopies of textbooks are not required. Most books listed below have electronic versions and can be found either online or in the university library.
  • Lee, Edward Ashford, and Sanjit A. Seshia. Introduction to Embedded Systems: A Cyber-Physical Systems Approach. MIT Press, 2016.
  • Alur, Rajeev. Principles of Cyber-Physical Systems. MIT Press, 2015.
  • Probabilistic Robotics. Sebastian Thrun, Wolfram Burgard, and Dieter Fox. 2005.
  • Bertsekas, Dimitri P., et al. Dynamic Programming and Optimal Control. Fourth edition, 2017.