UNIQUE SERIES AKTU Syllabus
BEC053

Intelligent Systems and Robotics

L-T-P3-0-0 Credits3 Session2024-25 TypeTheory
Appears in 4 semesters · 4 branches

B.Tech Electronics & Communication Engineering · Sem 5 (Department Elective-I) · B.Tech Electronics & Instrumentation / Instrumentation & Control · Sem 5 (Department Elective-I) · B.Tech ECE (Advanced Communication Technology) · Sem 5 (Department Elective-I) · B.Tech Electronics Engineering (VLSI Design & Technology) · Sem 5 (Department Elective-I)

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Syllabus

5 units · 40 lecture hours
Unit1

Unit 1: System Modeling

8 hrs

Biological and Cognitive Paradigms for Robot Design, Declarative Procedural-Reflexive Hierarchy for Decision-Making and Control, Articulated Robots, Joint- Link (Denavit - Hartenberg) Transformations, Mobile Ground Robots, Uninhabited Air Vehicles, Intelligent Agents.

Unit2

Unit 2: Control System Principles

8 hrs

Open- and Closed-Loop Control, Time-domain and Frequency domain Analysis, Optimality and Constraints, Stability and Performance, Adaptation, Control Actuation, Closed-form and Probabilistic Path Planning.

Unit3

Unit 3: Computing, Measurement, State, and Parameter Estimation

8 hrs

Sensors and Sensing, Formal and Fuzzy Logic, Turing Machines and Concepts of Machine Learning, Analog and Digital Systems, Probability and Error Models, Sensor-Based Estimation, Extended Kalman and Particle Filters, Simultaneous Location and Mapping (SAM).

Unit4

Unit 4: Decision-Making and Machine Learning

8 hrs

Decision Trees, Bayesian Belief Networks, Classification of Data Sets, Task Planning for Individual and Multiple Agents.

Unit5

Unit 5: Numerical Methods for Evaluation and Search

8 hrs

Monte Carlo Simulation, Genetic Algorithms, Simulated Annealing, Particle Swarm Optimization, Production Systems, Forward Chaining, Backward Chaining, Training and Implementation of Network Architectures, Feed- Forward Networks, Associative Networks, Cerebellar Model Articulation Controller, Deep- Learning Algorithms.

Course Outcomes (COs)5 outcomes

After completion of the course student will be able to:

  1. CO1Apply the concept of Open- and Closed-Loop Control.
  2. CO2Apply Fourier to understand Time-domain and Frequency-domain Analysis
  3. CO3Apply the fundamental concepts of Closed-form and Probabilistic Path Planning
  4. CO4Analyze Formal and Fuzzy Logic.
  5. CO5Analyze Simultaneous Location and Mapping (SAM).

Text Books

  1. H. Asada and J.-J. Slotine, Robot Analysis and Control, J. Wiley & Sons, 1986.C. Asfahl, Robots and Manufacturing Automation, J. Wiley & Sons, 1992.
  2. D. Auslander, J. Ridgely, and J. Ringgenberg, Control Software for Mechanical Systems, Prentice- Hall, 2002.
  3. G. Bekey, Autonomous Robots, MIT Press, 2005.
  4. Albus, J. I., and Meystel, A. M., Engineering of Mind, J. Wiley & Sons, 2001.
  5. P. Antsaklis and K. Passino, An Introduction to Intelligent and Autonomous Control, Kluwer, 1993.

Reference Books

  1. J. Craig, Introduction to Robotics Mechanics and Control, Pearson, 2018
  2. R. Dorf, Robotics and Automated Manufacturing, Reston (Prentice-Hall), 1983
  3. D. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.

Official AKTU syllabus

This subject is on page 10 of the original AKTU PDF.

Official AKTU syllabus PDF ↗