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Course Detail

Course Name Artificial Intelligence for Robotics
Course Code 23AID436
Program B.Tech in Artificial Intelligence and Data Science
Credits 3
Campus Coimbatore , Amritapuri ,Faridabad , Bangaluru, Amaravati

Syllabus

Unit 1

Introduction to AI for Robotics

Overview of AI for robotics, Robotics components and their interactions, Sensing and perception in robotics, Planning and decision-making in robotics, Control systems and robotics.

Unit 2

Machine Learning for Robotics

Supervised learning and its applications in robotics, Unsupervised learning and its applications in robotics, Reinforcement learning and its applications in robotics, Transfer learning in robotics

Unit 3

Deep Learning for Robotics

Neural networks and deep learning, Convolutional Neural Networks for Perception in Robotics, Recurrent Neural Networks for Robotics Planning, Deep Reinforcement Learning for Robotics Control

Objectives and Outcomes

Course Objectives

  • This course aims to introduce students to the fundamentals of artificial intelligence and machine learning techniques and their applications to robotics, including perception, planning, and control.
  • This course will help students understand the challenges involved in applying AI and machine learning techniques to robotics and develop the ability to design and implement intelligent robotics systems.
  • This course will provide students with the knowledge and skills required to apply deep learning algorithms to robotics problems, including object recognition, motion planning, and robot control.

Course Outcomes

After completing this course, students will be able to

CO1

Apply machine learning and deep learning algorithms to solve robotics problems.

CO2

Design intelligent agents that can perceive and act in different environments.

CO3

Evaluate different robotics and AI applications and identify their strengths and weaknesses.

CO4

Implement deep learning models for robotics tasks.

CO-PO Mapping

PO/PSO

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

PO9

PO10

PO11

PO12

PSO1

PSO2

PSO3

CO

CO1

3

3

2

1

3

–

–

2

3

2

–

2

3

3

2

CO2

3

3

1

1

3

1

–

–

3

3

–

2

3

3

3

CO3

3

3

3

2

3

2

2

2

3

3

–

2

3

3

3

CO4

3

3

3

2

3

–

–

–

3

3

–

2

3

3

2

Evaluation Pattern

Evaluation Pattern

Assessment

Internal/External

Weightage (%)

Assignments (minimum 2)

Internal

30

Quizzes (minimum 2)

Internal

20

Mid-Term Examination

Internal

20

Term Project/ End Semester Examination

External

30

Text Books / References

Text Books / References

Govers, F. X. Artificial Intelligence for Robotics. Packt Publishing; 2018

Nehmzow U. Mobile robotics: a practical introduction. Springer Science & Business Media; 2012.

  1. Corke, Robotics, Vision, and Control, Springer, 2011.
  2. Antsaklis and K. Passino, An Introduction to Intelligent and Autonomous Control, Kluwer, 1993.
  3. Kortenkamp, R. Bonasso, and R. Murphy, ed., Artificial Intelligence and Mobile Robots, AAAI Press, 1998.

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