COURSE: FALL 2022 CS 498 GC
Mobile Robotics for Computer Scientists
Announcements:All the announcements are made at Canvas
- Girish Chowdhary, Office: CSL 150, Email: email@example.com
- Programming assignment TA: Dr. Andres Baquero, Email: firstname.lastname@example.org
- The class meets on Wednesday and Friday from 02:00 to 03:15 PM in-person at 216 Siebel Center for Computer Science
- The class counts for 3 credits, and includes coding exercises. There is a 4 credit version for graduate students with additional work.
- Half hour before and after class or by appointment
This course will introduce students to foundational principles of mobile robotics with a view towards development of robot software. Topics covered will be dynamic modeling, coordinate transformations, principles of operations of different sensors, sensor fusion algorithms including Kalman filters, introduction to Simultaneous Localization and Mapping, and introduction to feedback control for robotics. Prerequisite of CS 225 suggested.
This course will draw from a number of texts but the primary text for the course is:
- Siegwart et al., Autonomous Mobile Robots (available electronically in UIUC library)
- Murphy, Introduction to AI for Robotics
- Kuipers, Quaternions and Rotation Sequences (available electronically in UIUC library)
- Farrell, Aided Navigation, GPS with high-rate Sensors
- Kelly, Mobile Robotics: Mathematics, Models, and Methods
- Dudek and Jenkin, Computational Principles of Mobile Robotics
- Thrun et al., Probabilistic Robotics
- A number of papers will also be included in the required reading.
Robots are computerized systems that perceive and understand the world around them and are capable of navigating the world or manipulating objects to perform tasks. Robots embody intelligence through programmed software-hardware interactions. Unlike a typical computer, robots are able to reposition themselves and manipulate their environments.
The last century has seen an unprecedented growth in manufacturing productivity and quality, largely due to the advent of factory-based robots. These robots accomplish complex manufacturing and assembly tasks in structured and highly controlled indoor environments. In contrast, mobile robots can maneuver themselves to locations where tasks need to be done. This opens the possibility of tackling a much broader variety of tasks in the real-world, outdoor, or loosely structured environments, which are not controlled, and in some cases can be harsh, full of uncertainty, and dynamically changing.
The next age in robotics will be enabled by rapid and profound advances in mobile robotics. The objective of this course is to prepare students in the foundations of mathematical principles, computational algorithms, and systems architecture aspects to enable them to design the next generation of mobile and outdoor robots that accomplish complex tasks in the face of high level of uncertainty.
We are already seeing exciting developments in the mobile robotics. Autonomous driving cars; home-cleaning robots; warehouse robots; GPS-enabled precision agricultural autonomous seeders, harvesters and sprayers; extraterrestrial rovers; and Unmanned Aerial Vehicles are but some examples of field robots. As the century progresses, we will see mobile robots enabling a vast array of exciting applications in domains where fixed robots have not yet had an impact.
In all of these and other emerging applications, the key enabling technology will leverage seamless integration of Cyber and Physical components in compact and self-sufficient robots that are able to communicate and work with each other and humans. Cyber components include software, embedded computers, sensors, and other electronic and computational artifacts; while physical components include hardware (cars, airplanes, power lines) that is subject to the rules of physics (dynamics, kinematics, electromechanics, fluid flows).
Robotic Cyber-Physical Systems (CPS) are expected to achieve the following:
This course is created to provide an introduction to the underlying scientific and engineering principles for the design and automation of mobile field robots.
Lecture Schedule - available on Canvas
Module Slides & NOTES
- Introduction to Mobile Robotics
- Robot Dynamics
- Mobile Robot Sensors, Dead Reckoning, and Multi-Sensor fusion
- Symbolic Perception Sensors
- Localization and Mapping
- Principles of Robot Motion Control
Statement on CS CARES and CS Values and Code of Conduct
All members of the Illinois Computer Science department - faculty, staff, and students - are expected to adhere to the CS Values and Code of Conduct. The CS CARES Committee is available to serve as a resource to help people who are concerned about or experience a potential violation of the Code. If you experience such issues, please contact the CS CARES Committee. The instructors of this course are also available for issues related to this class.
Following University policy, all students are required to engage in appropriate behavior to protect the health and safety of the community, including wearing a facial covering properly, maintaining social distance (at least 6 feet from others at all times), disinfecting the immediate seating area, and using hand sanitizer. Students are also required to follow the campus COVID-19 testing protocol.
Students who feel ill must not come to class.In addition, students who test positive for COVID-19 or have had an exposure that requires testing and/or quarantine must not attend class. The University will provide information to the instructor, in a manner that complies with privacy laws, about students in these latter categories. These students are judged to have excused absences for the class period and should contact the instructor via email about making up the work.
Students who fail to abide by these rules will first be asked to comply; if they refuse, they will be required to leave the classroom immediately. If a student is asked to leave the classroom, the non-compliant student will be judged to have an unexcused absence and reported to the Office for Student Conflict Resolution for disciplinary action. Accumulation of non-compliance complaints against a student may result in dismissal from the University.