Autonomous Ground Vehicle Systems detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the IT students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Information Technology 6th Sem scheme and its subjects, do visit IT 6th Sem 2019 regulation scheme. For Professional Elective-II scheme and its subjects refer to IT Professional Elective-II syllabus scheme. The detailed syllabus of autonomous ground vehicle systems is as follows.
Course Objective:
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Unit I
Introduction To Autonomous Driving
Autonomous Driving Technologies Overview – Autonomous Driving Algorithms -Autonomous Driving Client System – Autonomous Driving Cloud Platform – Components of autonomy – Difference between Unmanned and Autonomous Vehicles – Introduction to Unmanned Aerial Vehicles (UAVs).
Suggested Activities:
- Flipped classroom on autonomous driving system architecture.
- External learning – Building blocks of typical Unmanned Aerial Vehicles.
- Flipped classroom on robot operating system.
- External learning – Applications of autonomous vehicles (aerial, under water, ground vehicles).
- Assignment on the design requirement specifications of autonomous vehicles (aerial, under water, ground vehicles).
Suggested Evaluation Methods:
- Viva voce on assignment topics.
- Quizzes on Advanced Driver Assistance Systems (ADAS).
- Group Discussion on Googles self-driving car.
Unit II
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Unit III
Environment Perception and Modeling
Road Recognition: Basic Mean Shift Algorithm, Mean Shift Clustering, Mean Shift Segmentation, Mean Shift Tracking, Road Recognition Algorithm -Vehicle Detection and Tracking: Generating ROIs, Multi Resolution Vehicle Hypothesis, Vehicle Validation using Gabor Features and SVM, Boosted Gabor Features – Multiple Sensor Based Multiple Object Tracking.
Suggested Activities:
- Flipped classroom on basic mean shift algorithm.
- External learning – Lane detection algorithm.
- Flipped classroom on vehicle tracking.
Suggested Evaluation Methods:
- Practical – Implementation of Mean Shift Clustering / Mean Shift Segmentation Algorithm.
- Practical – Experiments on stationary obstacle detection algorithm using Lidar sensor.
Unit IV
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Unit V
Vehicle Control and Connected Vehicle
Vehicle Control: Cruise Control, Antilock Brake Systems, Steering Control and Lane Following, Parking – Connected Vehicles: Vehicle to Vehicle Communication, Vehicle to Infrastructure Communication.
Suggested Activities:
- Flipped classroom on cruise control.
- External learning – Study on proportional integral derivative (PID) control.
- Assignment – Communication protocols for connected vehicles.
Suggested Evaluation Methods:
- Viva Voce on assignment topic.
- Practical – Experiment on simple velocity control.
- Practical – Experiment on simple longitudinal motion control.
Course Outcome:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Text Books:
- Shaoshan Liu, Liyun Li, Jie Tang, Shuang Wu, Jean-Luc Gaudiot, “Creating Autonomous Vehicle Systems”, Morgan and Claypool, 2018.
- Umit Ozguner, Tankut Acarman, Keith Redmill, “Autonomous Ground Vehicles”, Artech House, 2011.
References:
- Hong Cheng, “Autonomous Intelligent Vehicles Theory, Algorithms, and Implementation”, Springer, 2011.
- Mohinder S. Grewal, Angus P. Andrews, Chris G. Bartone, “Global Navigation Satellite Systems, Inertial Navigation, and Integration”, Third Edition, John Wiley and Sons, 2013.
For detailed syllabus of all the other subjects of Information Technology 6th Sem, visit IT 6th Sem subject syllabuses for 2019 regulation.
For all Information Technology results, visit Anna University IT all semester results direct link.