AKTU Fundamentals of Robotics & AI (HTRA401) Syllabus PDF – B.Tech Honors Degree in Robotics and Artificial Intelligence

Course Outcomes

At the end of the course, the students will be able to:

1. Differentiate types of robots and robot grippers.
2. Apply basic principles of AI in solutions that require problem solving, inference, perception, knowledge representation and learning.
3. Understand AI, its current scope and limitations, and societal implications.
4. Analyse forces in links and joints of a robot.
5. Demonstrate awareness and a fundamental understanding of AI techniques in intelligent agents, artificial neural networks.

Unit 1: Introduction

Introduction to Robotics-classification with respect to geometrical configuration (Anatomy), Industrial robots specifications. Selection based on the Application. Controlled system & chain type: Serial manipulator & Parallel Manipulator. Components of Industrial robotics-precession of movement-resolution, accuracy & Repeatability-Dynamic characteristics- speed of motion, load carrying capacity & speed of response.

Unit 2: Sensors, Drives and Grippers

Characteristics of sensing devices, Criterion for selections of sensors, Classification, & applications of sensors. Internal sensors: Position sensors, & Velocity sensors, External sensors: Proximity sensors, Tactile Sensors, & Force or Torque sensors.

Drives – Basic types of drives. Advantages and Disadvantages of each type. Selection / suitability of drives for Robotic application. Controllers, Types of Controller and introduction to close loop controller Grippers, Mechanical Gripper-Grasping force, mechanisms for actuation, Magnetic gripper vacuum cup gripper-considerations in gripper selection & design.

Unit 3: Kinematics of Manipulators

Kinematics-Manipulators Kinematics, Rotation Matrix, Homogeneous Transformation Matrix, D-H transformation matrix, D-H method of assignment of frames. Direct and Inverse Kinematics for industrial robots. Differential Kinematics for planar serial robots Robot Applications: Material transfer and machine loading/unloading, processing operations assembly and inspection. Programming and Languages: Methods of robot programming, Introduction to various languages such as RAIL and VAL II …etc., Features of each type and development of languages for recent robot systems.

Unit 4: Introduction to Artificial Intelligence

Overview: foundations, scope, problems, and approaches of AI. Intelligent agents: reactive, deliberative, goal-driven, utility-driven, and learning agents, Artificial Intelligence programming techniques.

Unit 5: Problem-solving through Search and Knowledge Representation and Reasoning

forward and backward, state-space, blind, heuristic, problem reduction, alpha-beta pruning, minimax, constraint propagation, neural, stochastic, and evolutionary search algorithms, sample applications.

Ontologies, foundations of knowledge representation and reasoning, representing and reasoning about objects, relations, events, actions, time, and space; predicate logic, situation calculus, description logics, reasoning with defaults, reasoning about knowledge, sample applications. Planning: planning as search, partial order planning, construction and use of planning graphs. Representing and Reasoning with Uncertain Applications of AI (vision/robotics etc.).

Text Books

• John J. Craig, Introduction to Robotics, Pearson Education Inc., Asia, 3rd Edition, 2005.
• AsitavaGhoshal, Robotics: Fundamental concepts and analysis, Oxford University Press, 2006. (iii) Dilip Kumar Pratihar, Fundamentals of Robotics, Narosa Publishing House, 2019. Suggested Reference Books
• S. K. Saha, Introduction to Robotics, TATA McGraw Hills Education, 2014.
• S. B. Nikku, Introduction to Robotics – Analysis, Control, Applications, 3rd edition, John Wiley & Sons Ltd., 2020. (iii) Mikell Groover, Mitchell Weiss, Roger N. Nagel, Nicholas Odrey, Ashish Dutta, Industrial Robotics 2nd edition, SIE, McGraw Hill Education (India) Pvt. Ltd., 2012.
• R. D. Klafter, Thomas A. Chmielewski, and Michael Negin, Robotic Engineering – An Integrated Approach, EEE, Prentice Hall India, Pearson Education Inc., 2009.
• Russell, Stuart and Norvig, Peter, Artificial Intelligence: A Modern Approach" Prentice Hall, 2003.
• Aleksander, Igor and Burnett, Piers, Thinking Machines Oxford, 1987. (vii) Bench-Capon, T. J. M., Knowledge Representation: An approach to artificial intelligence Academic Press, 1990. (viii) Genesereth, Michael R. and Nilsson, Nils J, Logical Foundations of Artificial Intelligence Morgan Kaufmann, 1987.
• Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition), 2011.
• Vinod Chandra S.S., AnandHareendran S, "Artificial Intelligence and Machine Learning", 2014.
• Luger " Artificial Intelligence", Edition 5, Pearson, 2008.