Programme Content
Introduction to robotics in industry and society, historical perspectives
Classification of robots and overview of current research in robotics, applications of AI/ML
Robotics market, current challenges, and opportunities
System-level architecture of robots – Levels of autonomy
Fundamental concepts of robots – Components, joints, coordinate systems, workspace
Kinematics and kinetics of robots
Dynamics of a robot – Trajectory and path
Learning Outcomes:
Learn about the state of the art of robotics and the opportunities
Understand the principles of design and functioning of robot
Role of interoceptive and exteroceptive sensing
Position, velocity, and acceleration sensors
Force and torque sensing
Robotic tactile sensors and soft haptics
Non-contact sensing using ultrasonic, LIDAR, and RADAR
Camera-based robotic sensing and machine vision
Computational models and methods for processing sensor information
Learning Outcomes:
Learn about the fundamentals of robotic sensing in-depth
Understand implementation strategies for robotic sensing
Role and characteristics of robotic actuators
Electrical motors – Servos, stepper motors and drive mechanisms
Pneumatic and hydraulic actuators
Soft robotic actuators
Electroactive polymers, shape memory actuators, and emerging paradigms
Biomimetic actuators, artificial muscle technology and wearable actuators
Role of 3D printing and mechanical testing in robotic fabrication
Learning Outcomes:
Learn how to make a robot move and perform key tasks
Understand mechanical and electrical aspects of robotics
Localisation, navigation, and environment representation
Designing of robotic components using CAD
Introduction to Robot Operating System (ROS)
3D robot modelling, motion planning, and simulation in ROS
Interfacing hardware and sensors to ROS
Introduction to the role of machine learning in robotics – Software architecture, behavior-based systems
Neural networks and genetic algorithms in robotics
Introduction to Deep Learning and applications in robotics
Learning Outcomes:
Learn how to design and strategize movement of a robot
Learn applications of AI and Machine Learning in robotics
Introduction to embedded computing and control
Introduction to embedded hardware platforms – Arduino and Raspberry Pi
Programming and interfacing of sensors and actuators
Wired and wireless communication systems – MODBUS, CAN, and other paradigms
Multi-tasking and closed-loop control of robots
Learning Outcomes:
Learn software development for robotic control
Learn about key sensing and interfacing techniques for robotic functionalisation
Introduction to biorobotics and bionics – Exoskeleton device, prosthetics and surgical robotics
Humanoid robots – Future directions in automation
Human-Robot Interaction (HRI) and Collaboration – Collaborative robotics
Manufacturing automation using industrial robots – The next industrial revolution
Safety standards in industrial robotics
Roboethics: Navigating the ethical use and pitfalls of robotics and AI
Learning Outcomes:
Learn about a range of robotic applications in research and industry
Understand about standards and ethics associated with robotics and AI

