Course Information

Course Name	Turkish	Robotik Kontrol Sistemleri
	English	Robotic Control Systems
Course Code	UZB 438E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	-	-	-
Course Language		English
Course Coordinator		Murad Abu-khalaf
Course Objectives		1. To demonstrate how to model and describe the kinematic and dynamic motion of robots. 2. To demonstrate how to control the robot, by commanding its actuators to track a desired pre-planned motion in a stable and robust manner, under the assumption that the robot is fully aware of its pose. 3. To demonstrate how to plan robotic motion. 4. To demonstrate how to estimate the robot’s pose and motion from sensory input in known and unknown environments.
Course Description		Course Description Explains what the control problem in robotics is; how it fits within the autonomy and automation pipeline; how the motion control design problem depends on estimating the robot pose and on planning the motion in known and unknown environments. The course focuses on basic mathematical design and analysis tools for the control, planning and estimation of robot motion. The platforms considered are robotic manipulators and mobile robots.
Course Outcomes		1. To learn the different types of control problems. 2. To learn orientation representation and reference frames. 3. To learn forward and inverse kinematics. 4. To learn deriving robot dynamics from first principles. 5. To learn basic nonlinear control design and stability analysis tools for robots. 6. To learn why and when controllers need to be robust and/or adaptive, and how to design them accordingly. 7. To learn planning the robot motion towards desired destinations or configurations while avoiding collisions. 8. To learn pose estimation and robot localization in a known environment via optimal state estimation techniques such as Kalman filtering and optimal Bayesian estimation. 9. To learn robot localization and estimation of the traversed trajectory in an unknown environment via SLAM algorithms, and to map unknown environment.
Pre-requisite(s)
Required Facilities
Other		Website: https://abukhalaf.github.io/UZB438E/
Textbook		1. Mark W. Spong, Seth Hutchinson, M. Vidyasagar, Robot Modeling and Control, 2nd Edition, ISBN 9781119523994, John Wiley & Sons, 2020. 2. Lewis, F. L., Dawson, D. M., & Abdallah, C. T., Robot manipulator control: theory and practice. ISBN: 0-8247-4072-6, CRC Press, 2003. (URL: https://doi.org/10.1201/9780203026953)
Other References		1. Peter Corke, Robotics, Vision and Control: Fundamental Algorithms In MATLAB, 2nd edition, ISBN 9783319544120, Springer, 2017. (URL: https://doi.org/10.1007/978-3-319-54413-7) 2. Lewis, F.L., Xie, L., & Popa, D., Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition, ISBN: 9781420008296, CRC Press, 2008. (URL: https://doi.org/10.1201/9781315221656) 3. Slotine, Jean-Jacques E., and Weiping Li. Applied nonlinear control, ISBN: 0130408905, Englewood Cliffs, NJ: Prentice hall, 1991. 4. Kirk, D. E., Optimal control theory: an introduction. ISBN: 0486434842, Courier Corporation, 2004. 5. Edwin K. P. Chong, Stanislaw H. Zak, An Introduction to Optimization, 3rd edition, ISBN: 9780471758006, Wiley, 2008. (URL: http://doi.org/10.1002/9781118033340)

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