Page 93 - R2017-REC-ECE-UG Syllabus

Department of ECE, REC

Robot kinematics: Introduction-Matrix representation- rigid motion &homogeneous transformation- forward
& inverse kinematics trajectory planning. Robot Dynamics: Introduction-Manipulator dynamics –Lagrange-
Euler formulation-Newton - Euler formulation

UNIT IV MACHINE VISION FUNDAMENTALS 9
Machine vision: image acquisition, digital images-sampling and quantization-levels of computation, Feature
extraction- windowing technique-segmentation-Thresholding- edge detection-binary morphology-gray
morphology

UNIT V ROBOT PROGRAMMING 8
Robot programming: Robot Languages-Classification of robot language-Computer control and robot
software-Val system and Languages- concepts of Artificial Intelligence- application of robots.

TOTAL= 45 PERIODS
OUTCOMES:
Upon the completion of this course, students will be able to
• Apply the basic engineering knowledge and laws for the design of robotics
• Explain the basic concepts like various configurations, classification and parts of end effectors
compare various end effectors &grippers and tools and sensors used in robots.
• Explain the concept of kinematics, degeneracy, dexterity and trajectory planning.
• Demonstrate the image processing and image analysis techniques by machine vision system
• Analyze the concept of Artificial intelligence in robots, various types of robot programming and
its applications.

TEXT BOOK:
1.Groover MP, M.Weiss ,R.N. Nagal, N.G.Odrey, "Industrial Robotics - Technology, programming and
Applications" Second Edition, Tata McGraw-Hill Education Pvt. Limited, 2012

REFERENCES:
1.John.J.Craig, " Introduction to Robotics: Mechanics & control" Pearson Publication, Fourth edition, 2018.
2.Ralph Gonzale, C.S.G. Lee K. S. Fu, "Robotics: Sensing, Vision &Intelligence", Tata McGraw- Hill
Publication, 2008.
3.Sathya Ranjan Deb, "Robotics Technology & flexible Automation" Second edition, Tata McGraw-Hill
Publication, 2009.
4.Jazar, "Theory of Applied Robotics :Kinematics, Dynamics and Control", Springer, Indian Reprint, 2010

EC17E73 VIDEO ANALYTICS L T P C
3 0 0 3
OBJECTIVES:
• To know the fundamental concepts of big data and analytics.
• To learn various techniques for mining data streams.
• To acquire the knowledge of extracting information from surveillance videos.
• To learn Event Modelling for different applications.
• To understand the models used for recognition of objects in videos.

Curriculum and Syllabus | B.E. Electronics and Communication Engineering | R2017 Page 93