NOC:Introduction to Robotics (USB)

₹950.00
In stock
SKU
107106090



Media Storage Type : 32 GB USB Stick

NPTEL Subject Matter Expert : Dr. Krishna Vasudevan, Dr. Balaraman Ravindran, Dr. T Asokan

NPTEL Co-ordinating Institute : IIT Madras

NPTEL Lecture Count : 43

NPTEL Course Size : 5.9 GB

NPTEL PDF Text Transcription : Available and Included

NPTEL Subtitle Transcription : Available and Included (SRT)


Lecture Titles:

Lecture 1 - Introduction
Lecture 2 - Evolution of Robotics
Lecture 3 - Kinematics- Coordinate transformations
Lecture 4 - Homogeneus Transformation Matrix
Lecture 5 - Industrial Robot- Kinematic Structures
Lecture 6 - Robot Architectures
Lecture 7 - Kinematic Parameters
Lecture 8 - DH Algorithm
Lecture 9 - DH Algorithm- Examples
Lecture 10 - Forward Kinematics
Lecture 11 - Forward Kinematics- Examples
Lecture 12 - Inverse Kinematics
Lecture 13 - Inverse Kinematics- Examples
Lecture 14 - Differential Relations
Lecture 15 - Manipulator Jacobian and Statics
Lecture 16 - Overview of Electric Actuators and Operational Needs
Lecture 17 - Principles of DC Motor Operation
Lecture 18 - DC Motor Equations and Principles of Control
Lecture 19 - DC Motor Control Regions and Principles of Power Electronics
Lecture 20 - Power Electronic Switching and Current Ripple
Lecture 21 - The H-Bridge and DC Motor Control Structure
Lecture 22 - The Brushless DC Machine
Lecture 23 - Control of the Brushless DC Motor
Lecture 24 - The PM Synchronous Motor (PMSM) and SPWM
Lecture 25 - Principles of PMSM Control
Lecture 26 - Encoders for Speed and Position Estimation
Lecture 27 - Stepper Motors
Lecture 28 - Introduction to Probabilistic Robotics.
Lecture 29 - Recursive State Estimation: Bayes Filter
Lecture 30 - Recursive State Estimation: Bayes Filter Illustration
Lecture 31 - Probability basics
Lecture 32 - Probability basics
Lecture 33 - Kalman Filter
Lecture 34 - Extended Kalman Filter
Lecture 35 - Particle Filter
Lecture 36 - Binary Bayes
Lecture 37 - Velocity Motion Model
Lecture 38 - Odometry Motion Model
Lecture 39 - Occupa Grid Mapping
Lecture 40 - Range Finder Measurement Model
Lecture 41 - Localization Taxonomy
Lecture 42 - Markov Localization
Lecture 43 - Path Planning

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