M.Tech. in Robotics and Artificial Intelligence is an interdisciplinary engineering program designed to equip students with the knowledge and skills to develop intelligent, autonomous systems. These programs blend core concepts from robotics, artificial intelligence, automation, and control systems to build smart machines capable of performing complex tasks in dynamic environments.
The curriculum covers critical areas such as machine learning, computer vision, embedded systems, control theory, and the Internet of Things (IoT). Students also gain proficiency in programming languages like Python and C++, as well as experience with AI frameworks and robotics hardware. Through hands-on laboratory work, projects, and internships, students apply theoretical knowledge to real-world problems, enhancing both technical and practical understanding.
Advanced topics such as deep learning, reinforcement learning, and swarm intelligence are introduced to enable autonomous decision-making and adaptive behavior in robotic systems. These skills are increasingly valuable in industries such as healthcare, manufacturing, space exploration, logistics, and autonomous transportation, where intelligent automation is reshaping the future.
With the global surge in demand for AI-driven technologies, graduates of Robotics and AI programs are well-positioned for lucrative careers in research, development, and innovation, contributing to solutions for real-world challenges and shaping the next generation of intelligent systems.
| S. No. | Course Type | Course Code | Course Title | Lecture | Tutorial | Practical | Total Hours | Credits |
|---|---|---|---|---|---|---|---|---|
| 1 | PCC | 25M31EC111 | Introduction to Robots | 3 | - | - | 3 | 3 |
| 2 | PCC | 25M31EC112 | Robotic Control System | 3 | - | - | 3 | 3 |
| 3 | PCC | 1SM11GE111 | Research Methodology and Intellectual Property Rights | 2 | - | - | 2 | 2 |
| 4 | PEC | - | DE-I | 3 | - | - | 3 | 3 |
| 5 | PEC | - | DE-II | 3 | - | - | 3 | 3 |
| 6 | LAB | 25M35EC111 | Robotics Lab | - | - | 2 | 2 | 1 |
| 7 | LAB | 25M35EC112 | Robot Design and Modelling Lab | - | - | 2 | 2 | 1 |
| 8 | LAB | 25M35EC113 | AI and Machine Learning for Robotics Lab | - | - | 2 | 2 | 1 |
| Total | 14 | - | 6 | 20 | 17 | |||
| S. No. | Course Type | Course Code | Course Title | Lecture | Tutorial | Practical | Total Hours | Credit |
|---|---|---|---|---|---|---|---|---|
| 1 | PCC | 25M31EC113 | Sensors and Actuators for Robotics | 3 | - | - | 3 | 3 |
| 2 | PCC | 25M31EC114 | Robotic Operating System | 3 | - | - | 3 | 3 |
| 3 | PEC | DE-III | 3 | - | - | 3 | 3 | |
| 4 | PEC | DE-IV | 3 | - | - | 3 | 3 | |
| 5 | PEC | DE-V | 3 | - | - | 3 | 3 | |
| 6 | AC | Audit-I (Qualifying) | 2 | - | - | 2 | Qualifying | |
| 7 | LAB | 25M35EC111 | Advanced Mechatronics and Automation Lab | - | - | 4 | 4 | 2 |
| 8 | LAB | 25M35EC112 | Humanoid and Quadruped Robotics Lab | - | - | 2 | 2 | 1 |
| 9 | PBL | 17M11EC122 | PBL-I | - | - | 4 | 4 | 2 |
| Total | 17 | - | 10 | 27 | 20 | |||
| S. No. | Course Type | Course Code | Course Title | Lecture | Tutorial | Practical | Total Hours | Credit |
|---|---|---|---|---|---|---|---|---|
| 1 | Seminar | 17M17EC218 | Seminar & Term Paper OR Earn credits by transfer e.g. MOOCs, Course Work at another Institute, Supervised Study | - | - | 4 | 4 | 4 |
| 2 | OPE | Open Elective | 3 | - | - | 3 | 3 | |
| 3 | AC | Audit-II (Qualifying) | 2 | - | - | 2 | Qualifying | |
| 4 | PBL | 25M15EC211 / 17M17EC219 | PBL-II | - | - | 8 | 8 | 4 |
| 5 | Project | 17M17EC220 / 17M17EC221 | Dissertation - Industrial Project / Entrepreneurial Project | - | - | 8 | 8 | 4 |
| Total | 5 | 0 | 24 | 25 | 15 | |||
| S. No. | Course Type | Course Code | Course Title | Lecture | Tutorial | Practical | Total Hours | Credit |
|---|---|---|---|---|---|---|---|---|
| 1 | Project | 17M17EC222 17M17EC223 17M17EC224 | Dissertation (Industrial Project / Entrepreneurial Project) | - | - | - | 32 | 16 |
| Total | 0 | 0 | 0 | 32 | 16 | |||
TOTAL CREDITS: 68

