NPTEL Course: Intelligent Control of Robotic Systems by IIT Roorkee | AI & Robotics
Course Details
| Exam Registration | 449 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 4 weeks |
| Categories | Electrical, Electronics and Communications Engineering, Control and Instrumentation |
| Credit Points | 1 |
| Level | Undergraduate/Postgraduate |
| Start Date | 16 Feb 2026 |
| End Date | 13 Mar 2026 |
| Enrollment Ends | 16 Feb 2026 |
| Exam Registration Ends | 27 Feb 2026 |
| Exam Date | 19 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Master the Future: Enroll in the NPTEL Course on Intelligent Control of Robotic Systems
The field of robotics is rapidly evolving beyond simple pre-programmed machines. Today's advanced robotic systems require intelligent control—the ability to perceive, learn, and adapt in dynamic environments. If you're an engineering student or professional looking to dive into this cutting-edge domain, the National Programme on Technology Enhanced Learning (NPTEL) offers a perfect gateway.
We are excited to highlight the course "Intelligent Control of Robotic Systems," a comprehensive 4-week program designed and taught by a distinguished expert from the Indian Institute of Technology Roorkee.
Meet Your Instructor: Prof. M. Felix Orlando
This course is led by Prof. M. Felix Orlando, an Associate Professor in the Department of Electrical Engineering at IIT Roorkee. With a rich academic and research background, Prof. Orlando is exceptionally qualified to guide you through this complex subject.
His credentials include:
- Ph.D. in Electrical Engineering from IIT Kanpur (2013).
- Postdoctoral research at Case Western Reserve University, Ohio, USA.
- A Master's in Robotics and Human-Computer Interaction from the Korea Institute of Science and Technology (KIST), Seoul.
- Extensive teaching experience at IIT Roorkee in Introduction to Robotics, Artificial Neural Networks, and Bio-Medical Robotics.
- Active research in AI, Robotics, Medical Surgery Interventions, and Human Biomechanics.
- Membership in prestigious societies like the IEEE Robotics and Automation Society (IEEE-RAS) and ASME.
Prof. Orlando's expertise ensures the course content is both foundational and aligned with the latest research trends.
Course Overview: What Will You Learn?
This intensive course is structured over four weeks to build your knowledge from the ground up, blending classical robotics with modern AI techniques.
Detailed Course Layout
| Week | Core Topics Covered |
|---|---|
| Week 1 | Robotics Primer & Classical Control: Robot anatomy, actuation, sensing, programming. Kinematic and Dynamic Control Strategies. |
| Week 2 | Fuzzy Logic-Based Control: Review of fuzzy sets and Fuzzy Logic Controllers (FLC). Applications in redundant robot arm control and mobile robot navigation using Mamdani and Takagi-Sugeno models. |
| Week 3 | Neural Network-Based Control: Fundamentals of Perceptrons, Multi-Layer Perceptrons, and Radial Basis Function Networks. Designing neural network controllers for robot trajectory tracking. |
| Week 4 | Search & Reinforcement Learning (RL): Path planning with A* and RRT algorithms. Introduction to RL concepts (Agent, Environment, Reward). Implementing RL for position/force control in robotic manipulators. |
The course emphasizes practical understanding through MATLAB-based simulation studies, allowing you to apply theoretical concepts to virtual robotic systems.
Who Should Enroll?
Intended Audience: This course is ideally suited for:
- Undergraduate (UG) and Postgraduate (PG) students.
- PhD scholars.
- Students and professionals from Electrical (EE), Mechanical (ME), Computer Science (CSE), and Electronics & Communication (ECE) backgrounds who have an interest in robotics and automation.
Prerequisites & Industry Support
To get the most out of this course, it is recommended to have prior knowledge of introductory robotics. Prof. Orlando's previous NPTEL course, "Robotics and Control: Theory and Practice," serves as excellent preparation.
Industry Support: The course's relevance is recognized by leading industries, including:
- KUKA Robotics (India) Private Limited.
- General Electric (GE).
This endorsement underscores the practical, industry-aligned skills you will develop.
Essential Reference Books
To supplement your learning, the course references authoritative texts in robotics and AI:
- Sciavicco & Siciliano: "Modelling and Control of Robot Manipulators" (Springer, 2000).
- John J. Craig: "Introduction to Robotics: Mechanics and Control" (Pearson, 2004).
- Francis X. Govers: "Artificial Intelligence for Robotics" (Packt, 2018).
- Spong & Vidyasagar: "Robot Dynamics and Control" (Wiley).
Why Take This Course?
In just four weeks, this course offers a powerful synthesis of traditional control theory and modern artificial intelligence. You will transition from understanding robot mechanics to designing intelligent controllers that use fuzzy logic, neural networks, and reinforcement learning. This knowledge is critical for research and development in:
- Industrial Automation
- Medical Robotics
- Autonomous Vehicles
- Smart Manufacturing and Industry 4.0
Whether you aim to kickstart academic research or build a career in the robotics industry, "Intelligent Control of Robotic Systems" provides the foundational toolkit. Enroll today on the NPTEL platform and take your first step towards mastering the intelligent machines of tomorrow.
Enroll Now →