Localization filters (Such as Bayesian filter, Kalman filter, particle filter)
Machine learning algorithms (Such as linear neural networks, Kohonen maps, reinforcement learning)
Expert systems (First order predicate logic & inference)
Robotics (Using real-life sensor data and actuators, practical application of localization filters)
Engineering applications of artificial intelligence
Objective
The students will gain an overview of artificial intelligence methods and their applications in the engineering field.
By finishing programming assignments using educational robots, the students learn to overcome practical obstacles when working with real life sensor data, actuators, and programming interfaces.
Study Material
The lectures will use power point slides and will be split into the different topics.
For each topic the connection to the fundamental origins (such as neural networks in human brains) will be presented as well as its connection to the engineering domain.
The students will learn to apply their knowledge on a practical localization problem using GoPiGo robot kits which will be provided to them.
The robot assignment will be performed in small teams of students.
Recommended Reading
Russell, S., Norvig, P., Canny, J., Malik, J., & Edwards, D. (1995). Artificial Intelligence: A Modern Approach. Prentice hall Englewood Cliffs.
Krishnamoorthy, C. S., & Rajeev, S. (1996). Artificial Intelligence and Expert Systems for Engineers. CRC Press LLC.
