Subject Overview

An advanced study of robotic systems and industrial automation, integrating mechanics, electronics, control, programming, artificial intelligence, manufacturing systems, digital technologies, safety, economics and strategic management. The subject develops capabilities to analyse, design, integrate and govern contemporary automation solutions.

Learning Goal

Students will be able to model and control robots, design automated systems, apply sensing and intelligent decision-making, evaluate technical and economic performance, manage implementation risks, and develop safe, ethical and future-ready robotics and automation strategies.

Syllabus

1. Foundations of Robotics and Automation

Learning Objective: Explain robotics terminology, historical development, robot classifications, degrees of freedom, automation levels, system architectures, performance specifications and applications across manufacturing and service sectors.

Category: foundation

2. Mathematical Modelling and Spatial Representation

Learning Objective: Apply coordinate frames, vectors, rotation matrices, Euler angles, quaternions, homogeneous transformations and Denavit–Hartenberg conventions to represent robotic motion.

Category: foundation

3. Robot Kinematics and Workspace Analysis

Learning Objective: Solve forward and inverse kinematics; analyse Jacobians, velocity relationships, singularities, manipulability, redundancy, workspace and calibration errors.

Category: core

4. Robot Dynamics and Mechanical Design

Learning Objective: Model forces, torques and energy using Newton–Euler and Lagrangian methods; evaluate links, joints, payload, stiffness, vibration, accuracy and dynamic performance.

Category: core

5. Actuators, Drives, Transmissions and End Effectors

Learning Objective: Select electric, hydraulic and pneumatic actuation; analyse servo drives, transmissions and power systems; design grippers, tools and compliant end effectors for task requirements.

Category: core

6. Sensors, Machine Vision and Robotic Perception

Learning Objective: Integrate proprioceptive and exteroceptive sensors; apply signal conditioning, sensor fusion, image processing, 2D/3D vision, localization, object recognition and uncertainty analysis.

Category: core

7. Robot Control Systems

Learning Objective: Design joint-space and task-space controllers using PID, feedforward, computed-torque, force, impedance, adaptive, robust and model-predictive control; assess stability and real-time performance.

Category: core

8. Trajectory Generation and Motion Planning

Learning Objective: Generate smooth joint and Cartesian trajectories; apply configuration-space, graph-search, sampling-based and optimization methods for collision avoidance, scheduling and multi-robot coordination.

Category: application

9. Robot Programming and Workcell Engineering

Learning Objective: Develop online and offline robot programs; perform simulation, calibration and debugging; design workcells including fixtures, guarding, material handling, cycle-time analysis and human–machine interfaces.

Category: application

10. Industrial Automation and Manufacturing Systems

Learning Objective: Design automation using PLCs, ladder logic, CNC, SCADA, DCS and industrial networks; analyse assembly lines, flexible manufacturing, computer-integrated manufacturing, line balancing and process automation.

Category: application

11. Mobile, Autonomous and Collaborative Robotics

Learning Objective: Analyse mobile robot locomotion, mapping, localization, SLAM, navigation, fleet coordination, autonomous manipulation and human–robot collaboration, including cobots, AMRs and field robots.

Category: advanced

12. Artificial Intelligence and Intelligent Automation

Learning Objective: Apply machine learning, deep learning, reinforcement learning, knowledge-based methods and generative AI to perception, control, inspection, predictive maintenance and adaptive automation while recognizing data and model limitations.

Category: contemporary

13. Connected Automation, Digital Twins and Systems Integration

Learning Objective: Integrate robots with MES, ERP, cloud-edge platforms, IIoT and cyber-physical systems; use simulation, virtual commissioning, digital twins, interoperability standards and cybersecurity-by-design.

Category: contemporary

14. Automation Strategy, Economics and Performance Analytics

Learning Objective: Formulate automation roadmaps; evaluate feasibility, capacity, OEE, quality, productivity, lifecycle cost, ROI and sustainability; manage procurement, implementation, workforce transition, maintenance and operational risk.

Category: strategic

15. Safety, Ethics, Governance and Future Directions

Learning Objective: Apply functional safety, risk assessment and relevant robot standards; address accountability, privacy, bias, cybersecurity, workforce and environmental impacts; critically assess soft robotics, swarm systems, humanoids, autonomous factories and research frontiers.

Category: strategic