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Course Detail

Course Name Embedded Systems for Robotics
Course Code 25ES638
Program M. Tech. in Embedded Systems
Credits 3
Campus Bengaluru, Coimbatore

Syllabus

Syllabus

Robots and Embedded Systems-Sensors, Microcontrollers and Actuators in Robots – Control – On-Off Control, PID Control, Velocity Control and Position Control, Recent Trends in Robotics-Milli/Micro/Nano Robot- Human-robot interaction. Industrial Robots – Evolution of robotics, Robot anatomy, Manipulation and Control. Direct Kinematic Model – Denavit-Hartenberg Notation, Kinematic Relationship between adjacent links, Manipulator Transformation Matrix; Inverse Kinematic Model Manipulator Workspace, Solvability, Solution techniques, Closed form solution. Introduction to Robot dynamics & Control. Mobile Robots, Concepts of Localization, and path planning. Autonomous robots- Swarm and Collaborative robots. Robot Operating System: architecture, sensors, actuators and platforms supported.

Text Books / References
  1. Thomas Bräunl, “Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems”, Third Edition, Springer-Verlag Berlin Heidelberg, 2008. 
  2. K.Mittal and I.J.Nagrath, “Robotics and Control”, Tata McGraw-Hill Publishing Company Ltd., New Delhi, 2003. 
  3. John J. Craig, “Introduction to Robotics: Mechanics and Control”, Fourth Edition, Pearson, 2018. 
  4. Anis Koubaa, “Robot Operating System (ROS) The Complete Reference”, First Volume, Springer, 2016. 
  5. S. Fu, R.C. Gonzalez and C.S.G. Lee, “Robotics: Control, Sensing, Vision, and Intelligence”, McGraw-Hill, New York, 1987.

Objectives and Outcomes

Pre-requisite: Nil

Course Objectives:

  • To introduce the fundamentals of robotics, including the role of embedded systems, sensors, actuators, and control techniques.
  • To develop an understanding of industrial robot, kinematics, dynamics, and control, focusing on direct and inverse kinematic models, workspace analysis, and manipulator transformation techniques.
  • To provide knowledge on mobile and autonomous robots, including localization, path planning, swarm robotics, collaborative robots.

Course Outcomes:

CO1: Understand the architecture and components of robotic systems. 
CO2: Develop the kinematic models of manipulators 
CO3: Develop the inverse kinematic models for manipulators. 
CO4: Implement algorithms in autonomous mobile robot path planning, localization and control. 

CO-PO Mapping:

PO/PSO PO1 PO2 PO3 PSO1 PSO2
CO
CO1
CO2
CO3 1
CO4

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