CS1019 ROBOTICS CURRICULUM AND SYLLABUS B.E. COMPUTER SCIENCE AND ENGINEERING – ANNA UNIVERSITY CHENNAI

ANNA UNIVERSITY CHENNAI: CHENNAI – 600 025
B.E DEGREE PROGRAMME COMPUTER SCIENCE AND ENGINEERING
(Offered in Colleges affiliated to Anna University)
CURRICULUM AND SYLLABUS – REGULATIONS – 2004
B.E. COMPUTER SCIENCE AND ENGINEERING
LIST OF ELECTIVES FOR COMPUTER SCIENCE AND ENGINEERING

CS1019 ROBOTICS

AIM
Robots are slowly and steadily replacing human beings in many fields. The aim of this course is to introduce the students into this area so that they could use the same when they enter the industries.

OBJECTIVE
The course has been so designed to give the students an overall view of the mechanical components
• The mathematics associated with the same.
• Actuators and sensors necessary for the functioning of the robot.

UNIT I ROBOTIC MANIPULATION 8
Robotic manipulation – Automation and Robots – Robot Classification – Applications – Robot Specifications – Notation. Direct Kinematics: The ARM Equation – Dot and Cross products – Coordinate frames – Rotations – Homogeneous coordinates – Link coordinates – The arm equation – A five-axis articulated robot (Rhino XR-3) – A four-axis SCARA Robot (Adept One) – A six-axis articulated Robot (Intelledex 660). Inverse Kinematics: Solving the arm equation – The inverse kinematics problem – General properties of solutions – Tool configuration – Inverse kinematics of a five-axis articulated robot (Rhino XR-3) – Inverse kinematics of a four-axis SCARA robot (Adept one) - Inverse kinematics of a six-axis articulated robot (Intelledex 660) - Inverse kinematics of a three-axis articulated robot – A robotic work cell.

UNIT II DYNAMIC OF ROBOTS 12
Workspace analysis and trajectory planning: Workspace analysis – Work envelop of a five-axis articulated robot – Work envelope of a four-axis SCARA robot – Workspace fixtures – The pick-and-place operation – Continuous-path motion – Interpolated motion – Straight-line motion. Differential motion and statics: The tool-configuration Jacobian matrix – Joint-space singularities – Generalized Inverses – Resolved-Motion rate control:n<=6 – Rate control of redundant robots:n>6 – rate control using {1}-inverses – The manipulator Jacobian – Induced joint torques and forces. Manipulator Dynamics: Lagrange’s equation – Kinetic and Potential energy – Generalized force – Lagrange -Euler dynamic model – Dynamic model of a two-axis planar articulated robot - Dynamic model of a three-axis SCARA robot – Direct and Inverse dynamics – Recursive Newton-Euler formulation – Dyamic model of a one-axis robot.

UNIT III ROBOT CONTROL 6
Robot control: The control problem – State equation – Constant solutions – Linear feedback systems - Single-axis PID control – PD-Gravity control – Computed-Torque control – Variable-Structure control – Impedance control

UNIT IV SENSORS AND ACTUATORS 9
Actuators - Introduction – Characteristics of actuating systems – Comparison of actuating systems – Hydraulic devices – Pneumatic devices – Electric motors – Microprocessor control of electric motors – Magnetostricitve actuators – Shape-memory type metals – Speed reduction. Sensors – Introduction – Sensor characteristics – Position sensors – Velocity sensors – Acceleration sensors – Force and pressure sensors – Torque sensors – Microswitches – Light and Infrared sensors – Touch and Tactile sensors – Proximity sensors – Range-finders – Sniff sensors – Vision systems – Voice Recognition devices – Voice synthesizers – Remote center compliance device.

UNIT V VISION AND TASK PLANNING 9
Robot vision – Image representation – Template matching – Polyhedral objects – Shape analysis – Segmentation – Iterative processing – Perspective Transformations – Structured illumination –Camera calibration. Task planning: Task-level programming – Uncertainty – Configuration space – Gross-Motion planning – Grasp planning – Fine-Motion planning – Simulation of planar motion – A task-planning problem.

TOTAL : 45
TEXT BOOKS
1. Robert J.Schilling, “Fundamentals of Robotics – Analysis & Control”, Prentice Hall of India Pvt. Ltd., 2002. (Chapters 1 to 9 – Unit I, II, III, V)
2. Saeed B.Niku, “Introduction to Robotics – Analysis, Systems, Applications”, Prentice Hall of India Pvt. Ltd., 2003. (Chapters 6 & 7 – Unit IV)

CS1019 ROBOTICS CURRICULUM AND SYLLABUS B.E. COMPUTER SCIENCE AND ENGINEERING – ANNA UNIVERSITY CHENNAI

ANNA UNIVERSITY CHENNAI: CHENNAI – 600 025
B.E DEGREE PROGRAMME COMPUTER SCIENCE AND ENGINEERING
(Offered in Colleges affiliated to Anna University)
CURRICULUM AND SYLLABUS – REGULATIONS – 2004
B.E. COMPUTER SCIENCE AND ENGINEERING
LIST OF ELECTIVES FOR COMPUTER SCIENCE AND ENGINEERING

CS1019 ROBOTICS

AIM
Robots are slowly and steadily replacing human beings in many fields. The aim of this course is to introduce the students into this area so that they could use the same when they enter the industries.

OBJECTIVE
The course has been so designed to give the students an overall view of the mechanical components
• The mathematics associated with the same.
• Actuators and sensors necessary for the functioning of the robot.

UNIT I ROBOTIC MANIPULATION 8
Robotic manipulation – Automation and Robots – Robot Classification – Applications – Robot Specifications – Notation. Direct Kinematics: The ARM Equation – Dot and Cross products – Coordinate frames – Rotations – Homogeneous coordinates – Link coordinates – The arm equation – A five-axis articulated robot (Rhino XR-3) – A four-axis SCARA Robot (Adept One) – A six-axis articulated Robot (Intelledex 660). Inverse Kinematics: Solving the arm equation – The inverse kinematics problem – General properties of solutions – Tool configuration – Inverse kinematics of a five-axis articulated robot (Rhino XR-3) – Inverse kinematics of a four-axis SCARA robot (Adept one) - Inverse kinematics of a six-axis articulated robot (Intelledex 660) - Inverse kinematics of a three-axis articulated robot – A robotic work cell.

UNIT II DYNAMIC OF ROBOTS 12
Workspace analysis and trajectory planning: Workspace analysis – Work envelop of a five-axis articulated robot – Work envelope of a four-axis SCARA robot – Workspace fixtures – The pick-and-place operation – Continuous-path motion – Interpolated motion – Straight-line motion. Differential motion and statics: The tool-configuration Jacobian matrix – Joint-space singularities – Generalized Inverses – Resolved-Motion rate control:n<=6 – Rate control of redundant robots:n>6 – rate control using {1}-inverses – The manipulator Jacobian – Induced joint torques and forces. Manipulator Dynamics: Lagrange’s equation – Kinetic and Potential energy – Generalized force – Lagrange -Euler dynamic model – Dynamic model of a two-axis planar articulated robot - Dynamic model of a three-axis SCARA robot – Direct and Inverse dynamics – Recursive Newton-Euler formulation – Dyamic model of a one-axis robot.

UNIT III ROBOT CONTROL 6
Robot control: The control problem – State equation – Constant solutions – Linear feedback systems - Single-axis PID control – PD-Gravity control – Computed-Torque control – Variable-Structure control – Impedance control

UNIT IV SENSORS AND ACTUATORS 9
Actuators - Introduction – Characteristics of actuating systems – Comparison of actuating systems – Hydraulic devices – Pneumatic devices – Electric motors – Microprocessor control of electric motors – Magnetostricitve actuators – Shape-memory type metals – Speed reduction. Sensors – Introduction – Sensor characteristics – Position sensors – Velocity sensors – Acceleration sensors – Force and pressure sensors – Torque sensors – Microswitches – Light and Infrared sensors – Touch and Tactile sensors – Proximity sensors – Range-finders – Sniff sensors – Vision systems – Voice Recognition devices – Voice synthesizers – Remote center compliance device.

UNIT V VISION AND TASK PLANNING 9
Robot vision – Image representation – Template matching – Polyhedral objects – Shape analysis – Segmentation – Iterative processing – Perspective Transformations – Structured illumination –Camera calibration. Task planning: Task-level programming – Uncertainty – Configuration space – Gross-Motion planning – Grasp planning – Fine-Motion planning – Simulation of planar motion – A task-planning problem.

TOTAL : 45
TEXT BOOKS
1. Robert J.Schilling, “Fundamentals of Robotics – Analysis & Control”, Prentice Hall of India Pvt. Ltd., 2002. (Chapters 1 to 9 – Unit I, II, III, V)
2. Saeed B.Niku, “Introduction to Robotics – Analysis, Systems, Applications”, Prentice Hall of India Pvt. Ltd., 2003. (Chapters 6 & 7 – Unit IV)

CS1018 SOFT COMPUTING CURRICULUM AND SYLLABUS B.E. COMPUTER SCIENCE AND ENGINEERING – ANNA UNIVERSITY CHENNAI

ANNA UNIVERSITY CHENNAI: CHENNAI – 600 025
B.E DEGREE PROGRAMME COMPUTER SCIENCE AND ENGINEERING
(Offered in Colleges affiliated to Anna University)
CURRICULUM AND SYLLABUS – REGULATIONS – 2004
B.E. COMPUTER SCIENCE AND ENGINEERING
LIST OF ELECTIVES FOR COMPUTER SCIENCE AND ENGINEERING

CS1018 SOFT COMPUTING

AIM
To introduce the techniques of soft computing and adaptive neuro-fuzzy inferencing systems which differ from conventional AI and computing in terms of its tolerance to imprecision and uncertainty.

OBJECTIVES
• To introduce the ideas of fuzzy sets, fuzzy logic and use of heuristics based on human experience
• To become familiar with neural networks that can learn from available examples and generalize to form appropriate rules for inferencing systems
• To provide the mathematical background for carrying out the optimization associated with neural network learning
• To familiarize with genetic algorithms and other random search procedures useful while seeking global optimum in self-learning situations
• To introduce case studies utilizing the above and illustrate the intelligent behavior of programs based on soft computing

UNIT I FUZZY SET THEORY 10
Introduction to Neuro – Fuzzy and Soft Computing – Fuzzy Sets – Basic Definition and Terminology – Set-theoretic Operations – Member Function Formulation and Parameterization – Fuzzy Rules and Fuzzy Reasoning – Extension Principle and Fuzzy Relations – Fuzzy If-Then Rules – Fuzzy Reasoning – Fuzzy Inference Systems – Mamdani Fuzzy Models – Sugeno Fuzzy Models – Tsukamoto Fuzzy Models – Input Space Partitioning and Fuzzy Modeling.

UNIT II OPTIMIZATION 8
Derivative-based Optimization – Descent Methods – The Method of Steepest Descent – Classical Newton’s Method – Step Size Determination – Derivative-free Optimization – Genetic Algorithms – Simulated Annealing – Random Search – Downhill Simplex Search.
UNIT III NEURAL NETWORKS 10
Supervised Learning Neural Networks – Perceptrons - Adaline – Backpropagation Mutilayer Perceptrons – Radial Basis Function Networks – Unsupervised Learning Neural Networks – Competitive Learning Networks – Kohonen Self-Organizing Networks – Learning Vector Quantization – Hebbian Learning.
UNIT IV NEURO FUZZY MODELING 9
Adaptive Neuro-Fuzzy Inference Systems – Architecture – Hybrid Learning Algorithm – Learning Methods that Cross-fertilize ANFIS and RBFN – Coactive Neuro Fuzzy Modeling – Framework Neuron Functions for Adaptive Networks – Neuro Fuzzy Spectrum.
UNIT V APPLICATIONS OF COMPUTATIONAL INTELLIGENCE 8
Printed Character Recognition – Inverse Kinematics Problems – Automobile Fuel Efficiency Prediction – Soft Computing for Color Recipe Prediction.

TOTAL : 45
TEXT BOOK
1. J.S.R.Jang, C.T.Sun and E.Mizutani, “Neuro-Fuzzy and Soft Computing”, PHI, 2004, Pearson Education 2004.

REFERENCES
1. Timothy J.Ross, “Fuzzy Logic with Engineering Applications”, McGraw-Hill, 1997.
2. Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”, Addison Wesley, N.Y., 1989.
3. S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2003.
4. R.Eberhart, P.Simpson and R.Dobbins, “Computational Intelligence - PC Tools”, AP Professional, Boston, 1996.