MD3019 ROBOTICS SYLLABUS | ANNA UNIVERSITY BE MEDICAL ELECTRONICS ENGINEERING 8TH SEMESTER SYLLABUS REGULATION 2008 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY 8TH SEMESTER B.E MEDICAL ELECTRONICS ENGINEERING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI, TIRUNELVELI,COIMBATORE), 2008 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
MD3019 ROBOTICS L T P C
3 0 0 3
UNIT I INTRODUCTION TO ROBOTICS 9
Motion - Potential Function, Road maps, Cell decomposition and Sensor and sensor
planning. Kinematics. Forward and Inverse Kinematics - Transformation matrix and DH
transformation. Inverse Kinematics - Geometric methods and Algebraic methods. Non-
Holonomic constraints.
UNIT II COMPUTER VISION 9
Projection - Optics, Projection on the Image Plane and Radiometry. Image Processing -
Connectivity, Images-Gray Scale and Binary Images, Blob Filling,Thresholding,
Histogram. Convolution - Digital Convolution and Filtering and Masking Techniques.
Edge Detection - Mono and Stereo Vision.
UNIT III SENSORS AND SENSING DEVICES 9
Introduction to various types of sensor. Resistive sensors. Range sensors - Ladar (laser
distance and ranging), Sonar, Radar and Infra-red. Introduction to sensing - Light
sensing, Heat sensing, Touch sensing and Position sensing.
UNIT IV ARTIFICIAL INTELLIGENCE 9
Uniform Search strategies - Breadth first, Depth first, Depth limited, Iterative and
deepening depth first search and Bidirectional search. The A* algorithm . Planning -
State-Space Planning , Plan-Space Planning, Graphplan/SatPlan and their Comparison,
Multi-agent planning , and Multi-agent planning , Probabilistic Reasoning - Bayesian
Networks, Decision Trees and Bayes net inference .
UNIT V INTEGRATION TO ROBOTICS 9
Building of 4 axis or 6 axis robot - Vision System for pattern detection - Sensors for
obstacle detection - AI algorithms for path finding and decision making
TOTAL: 45 PERIODS
REFERENCES :
1. Duda, Hart and Stork, “Pattern Recognition”, Wiley-Interscience, 2000.
2. Mallot, “Computational Vision: Information Processing in Perception and Visual
Behavior”, Cambridge, MA: MIT Press, 2000.
3. Stuart Russell and Peter Norvig, “Artificial Intelligence-A Modern Approach” Pearson
Education Series in Artificial Intelligence, 2004
4. Robert Schilling and Craig ,”Fundamentals of Robotics, Analysis and control”,
5. Prentice Hall of India Private Limied, New Delhi, 2003.
6. Forsyth and Ponce, “Computer Vision-- A modern Approach”, Person Education,
2003.
MD3019 ROBOTICS L T P C
3 0 0 3
UNIT I INTRODUCTION TO ROBOTICS 9
Motion - Potential Function, Road maps, Cell decomposition and Sensor and sensor
planning. Kinematics. Forward and Inverse Kinematics - Transformation matrix and DH
transformation. Inverse Kinematics - Geometric methods and Algebraic methods. Non-
Holonomic constraints.
UNIT II COMPUTER VISION 9
Projection - Optics, Projection on the Image Plane and Radiometry. Image Processing -
Connectivity, Images-Gray Scale and Binary Images, Blob Filling,Thresholding,
Histogram. Convolution - Digital Convolution and Filtering and Masking Techniques.
Edge Detection - Mono and Stereo Vision.
UNIT III SENSORS AND SENSING DEVICES 9
Introduction to various types of sensor. Resistive sensors. Range sensors - Ladar (laser
distance and ranging), Sonar, Radar and Infra-red. Introduction to sensing - Light
sensing, Heat sensing, Touch sensing and Position sensing.
UNIT IV ARTIFICIAL INTELLIGENCE 9
Uniform Search strategies - Breadth first, Depth first, Depth limited, Iterative and
deepening depth first search and Bidirectional search. The A* algorithm . Planning -
State-Space Planning , Plan-Space Planning, Graphplan/SatPlan and their Comparison,
Multi-agent planning , and Multi-agent planning , Probabilistic Reasoning - Bayesian
Networks, Decision Trees and Bayes net inference .
UNIT V INTEGRATION TO ROBOTICS 9
Building of 4 axis or 6 axis robot - Vision System for pattern detection - Sensors for
obstacle detection - AI algorithms for path finding and decision making
TOTAL: 45 PERIODS
REFERENCES :
1. Duda, Hart and Stork, “Pattern Recognition”, Wiley-Interscience, 2000.
2. Mallot, “Computational Vision: Information Processing in Perception and Visual
Behavior”, Cambridge, MA: MIT Press, 2000.
3. Stuart Russell and Peter Norvig, “Artificial Intelligence-A Modern Approach” Pearson
Education Series in Artificial Intelligence, 2004
4. Robert Schilling and Craig ,”Fundamentals of Robotics, Analysis and control”,
5. Prentice Hall of India Private Limied, New Delhi, 2003.
6. Forsyth and Ponce, “Computer Vision-- A modern Approach”, Person Education,
2003.
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