MCTR 1002: Autonomous Systems

Autonomy (Ancient Greek: auto- "self" + nomos- "law") is a desirable feature in modern systems. Autonomous systems are intelligent systems that can perform desired tasks in unstructured environments without continuous explicit human guidance. Mobile robots are commonly used as a platform to study different aspects of autonomous systems. These aspects include, but are not limited to, environment mapping, localization, motion planning, navigation, decision making under uncertainty, learning, and interaction with human or non-human actors in the environment. Examples of autonomous mobile robots range from autonomous helicopters to autonomous robot vacuum cleaners.
MCTR1002 Autonomous Systems course aims at providing students with the basics required to develop autonomous systems. It provides a broad overview of the technologies and methods of mobile robotics. Major topics will include locomotion systems, kinematics, sensing and perception (or thinking about sensing), state estimation, localization, mapping, planning (or thinking about actions), navigation and control. In addition, a special topic about multirobot systems will be introduced. This is a lecture- exercise-project course in which topics are presented by the instructor and a course project and assignments are completed by students. Without assuming any prior knowledge of artificial intelligence, the course provides an introduction to the key artificial intelligence issues involved in the development of intelligent robots.

Course Instructor: Dr. Alaa Khamis
Email: alaa[dot]khamis[at]guc[dot]edu[dot]eg
Office hours: Saturdays 3rd slot

Course TAs:
Eng. Omar Mahmoud
Email: omar[dot]mohamad[at]guc[dot]edu[dot]eg
Office: C6.104
Office hours: Sunday 5th slot or via Email
Eng. Mohamed Yehia Baderldin
Email: mohamed[dot]badereldin[at]guc[dot]edu[dot]eg
Office: C6.104
Office hours: Sunday 5th slot or via Email

- R. Siegwart and I. Nourbakhsh . Introduction to Autonomous Mobile Robots. MIT Press, 2004.
- Thomas Braunl. Embedded Robotics. Springer, 2006.
- Robin Murphy . Introduction to AI Robotics. MIT Press, 2000.
- Phillip McKerrow. Introduction to Robotics. Addison-Wesley, 1991.
- Mark Lee. Intelligent Robotics. Halsted Press and Open University Press, 1989.
Lectures will be based mainly, but not exclusively, on material in these textbooks. Lectures will not follow the same sequence as the material presented in the texts.