Build programming, mathematics, mechanics, electronics, perception, control, integration and responsible engineering judgement.
Skills Required for AI and Robotics
Programming: Students should develop strong Python and C/C++ ability and understand software structure, testing and debugging.
Data Structures and Algorithms: Efficient problem-solving is important for planning, mapping and perception.
Mathematics: Linear algebra, calculus, probability, statistics and optimisation are fundamental.
Machine Learning: Students should understand data preparation, model training, evaluation and error analysis.
Computer Vision: Useful for detection, tracking, localisation and robot interaction.
Mechanical aptitude: Students need basic understanding of joints, links, gears, loads and mechanisms.
Electronics: Robotics requires circuits, sensors, power systems, microcontrollers and communication.
Embedded programming: Students must connect software with real hardware under limited resources.
Control systems: Feedback and stability are essential for reliable robot motion.
Kinematics and dynamics: These areas explain robot position, velocity, force and torque.
Simulation: Simulation supports testing before deploying code to hardware.
Sensor integration: Engineers must understand calibration, noise, limitations and sensor fusion.
Debugging: A robotic failure can originate from hardware, wiring, mechanics, software, timing or data. Systematic debugging is essential.
System integration: Engineers must connect mechanical, electronic and software components.
Problem-solving: Students should define requirements, test assumptions and measure performance.
Creativity: Robotics involves developing new mechanisms, interfaces and behaviours.
Communication: Engineers work with people from different technical backgrounds.
Teamwork: Complete robots usually require multidisciplinary teams.
Safety awareness: Robots can create mechanical, electrical, privacy and cybersecurity risks.
Ethical judgement: AI systems can affect people through surveillance, automated decisions and physical action.
Project management: Students should learn planning, version control, documentation, cost and risk management.
Continuous learning: AI frameworks, sensors, hardware and research methods change quickly.
Continue your AI and Robotics research
Course at a Glance
- Course AreaComputing and Emerging Technology
- Study PathwaysB.E./B.Tech, M.E./M.Tech, B.Sc./M.Sc., diploma and research pathways
- Primary FocusArtificial intelligence, machine learning, perception, robot mechanics, sensors, embedded systems, control and autonomous machines.