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Our team was awarded by DOT to establish a $30M Regional University Transportation Center (UTC).
ECEN885: Self-driving Cars: Perception and Control
ECEN885: Self-driving Cars: Perception and Control
Instructor: Dr. Ali Karimoddini, Dept. of Electrical and Computer Engineering, NC A&T University, Email: akarimod at ncat.edu
Prerequisite: ELEN668 or consent of instructor
Course Overview: This course will cover recent developments in control of autonomous cars and discusses fundamental problems that an autonomous car faces while moving in its environment. The course covers basic concepts of autonomous cars and feedback control of autonomous cars including sensors, estimation, sensor fusion, planning, navigation, and control.
Topics:
Topics will include most of the following:
- Introduction to Autonomous Vehicle Architecture
- Introduction to ROS
- Computer Vision
- Lane detection
- Introduction to tensorflow, Keras, Deep Neural Networks, Transfer Learning, Behavior Cloning, Decision Trees, SVM
- Sign Classifier
- Object Detection
- Autonomous Car Sensors (Camera, Lidar, Radar, GPS, IMU, Encoder
- Sensor Fusion and Kalman Filtering
- CANbus Interfacing
- Automatic Control (PID and MPC)
- Path Planning
Textbooks:
- Major Test books:
- Hong Cheng, Autonomous Intelligent Vehicles: Theory, Algorithms, and Implementation (Advances in Computer Vision and Pattern Recognition), Springer London, 2014. (1447158695, 9781447158691)
- Umit Ozguner, Tankut Acarman, Keith Redmill, Autonomous Ground Vehicles, ARTECH HOUSE, Boston|London, 2011, ISBN: 978-1608071920)
- Additional Textbooks:
- R. Siegwart, I. Nourbakhsh, D. Scaramuzza, Introduction to Autonomous Mobile Robots, 2nd Edition MIT Press, 2011. (ISBN: 0-262-01535-8)
- G. Dudek and M. Jenkin, Computational Principles of Mobile Robotics, 2nd Edition. Cambridge University Press, 2010. (ISBN: 0521692121)
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