Course Structure Overview
The B.Tech Robotics program at LNCT BHOPAL INDORE CAMPUS is structured over 8 semesters, with a balanced blend of theoretical foundations and practical applications. The curriculum integrates core engineering principles with specialized robotics knowledge to produce graduates who are well-rounded and industry-ready.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | MATH-101 | Mathematics I | 3-1-0-4 | - |
| 1 | PHY-101 | Physics for Engineers | 3-1-0-4 | - |
| 1 | CSE-101 | Introduction to Programming | 2-0-2-3 | - |
| 1 | MEE-101 | Engineering Mechanics | 3-1-0-4 | - |
| 1 | ECE-101 | Basic Electronics | 3-1-0-4 | - |
| 1 | LIT-101 | English Communication | 2-0-0-2 | - |
| 2 | MATH-102 | Mathematics II | 3-1-0-4 | MATH-101 |
| 2 | PHY-102 | Applied Physics | 3-1-0-4 | PHY-101 |
| 2 | CSE-102 | Data Structures and Algorithms | 3-1-0-4 | CSE-101 |
| 2 | MEE-102 | Mechanics of Materials | 3-1-0-4 | MEE-101 |
| 2 | ECE-102 | Digital Electronics | 3-1-0-4 | ECE-101 |
| 2 | LIT-102 | Technical Writing | 2-0-0-2 | - |
| 3 | MATH-201 | Mathematics III | 3-1-0-4 | MATH-102 |
| 3 | PHY-201 | Electromagnetic Fields | 3-1-0-4 | PHY-102 |
| 3 | CSE-201 | Object-Oriented Programming | 2-0-2-3 | CSE-102 |
| 3 | MEE-201 | Thermodynamics | 3-1-0-4 | MEE-102 |
| 3 | ECE-201 | Signals and Systems | 3-1-0-4 | ECE-102 |
| 3 | DEP-101 | Introduction to Robotics | 2-0-2-3 | - |
| 4 | MATH-202 | Mathematics IV | 3-1-0-4 | MATH-201 |
| 4 | PHY-202 | Optics and Modern Physics | 3-1-0-4 | PHY-201 |
| 4 | CSE-202 | Database Management Systems | 3-1-0-4 | CSE-201 |
| 4 | MEE-202 | Mechanics of Solids | 3-1-0-4 | MEE-201 |
| 4 | ECE-202 | Control Systems | 3-1-0-4 | ECE-201 |
| 4 | DEP-102 | Robotics Lab I | 0-0-6-3 | DEP-101 |
| 5 | MATH-301 | Mathematics V | 3-1-0-4 | MATH-202 |
| 5 | PHY-301 | Nuclear Physics | 3-1-0-4 | PHY-202 |
| 5 | CSE-301 | Computer Architecture | 3-1-0-4 | CSE-202 |
| 5 | MEE-301 | Manufacturing Processes | 3-1-0-4 | MEE-202 |
| 5 | ECE-301 | Microprocessors and Microcontrollers | 3-1-0-4 | ECE-202 |
| 5 | DEP-201 | Robotics Lab II | 0-0-6-3 | DEP-102 |
| 6 | MATH-302 | Mathematics VI | 3-1-0-4 | MATH-301 |
| 6 | PHY-302 | Quantum Mechanics | 3-1-0-4 | PHY-301 |
| 6 | CSE-302 | Operating Systems | 3-1-0-4 | CSE-301 |
| 6 | MEE-302 | Machine Design | 3-1-0-4 | MEE-301 |
| 6 | ECE-302 | Embedded Systems | 3-1-0-4 | ECE-301 |
| 6 | DEP-202 | Robotics Lab III | 0-0-6-3 | DEP-201 |
| 7 | MATH-401 | Mathematics VII | 3-1-0-4 | MATH-302 |
| 7 | PHY-401 | Statistical Physics | 3-1-0-4 | PHY-302 |
| 7 | CSE-401 | Artificial Intelligence | 3-1-0-4 | CSE-302 |
| 7 | MEE-401 | Advanced Manufacturing | 3-1-0-4 | MEE-302 |
| 7 | ECE-401 | Robotics and Automation | 3-1-0-4 | ECE-302 |
| 7 | DEP-301 | Advanced Robotics Lab | 0-0-6-3 | DEP-202 |
| 8 | MATH-402 | Mathematics VIII | 3-1-0-4 | MATH-401 |
| 8 | PHY-402 | Condensed Matter Physics | 3-1-0-4 | PHY-401 |
| 8 | CSE-402 | Machine Learning | 3-1-0-4 | CSE-401 |
| 8 | MEE-402 | Robotics Project | 0-0-6-3 | - |
| 8 | ECE-402 | Sensors and Actuators | 3-1-0-4 | ECE-401 |
| 8 | DEP-302 | Final Year Project | 0-0-12-6 | DEP-301 |
Advanced Departmental Electives
After completing foundational courses, students can choose from a wide range of advanced departmental electives that align with their interests and career goals:
- Computer Vision for Robotics: This course introduces students to image processing techniques, feature extraction, object recognition, and real-time computer vision applications in robotics. Students learn to implement algorithms using OpenCV and TensorFlow.
- Robotics Simulation and Modeling: Focused on simulation environments like ROS, Gazebo, and MATLAB/Simulink, this course teaches students how to model robotic systems and validate designs before physical prototyping.
- Reinforcement Learning for Autonomous Robots: This elective explores how reinforcement learning algorithms can be applied to teach robots complex behaviors such as navigation, manipulation, and task execution.
- Soft Robotics Design: Students learn to design flexible and compliant robotic systems inspired by biological structures. The course covers materials science, fabrication techniques, and control strategies for soft robots.
- Human-Robot Interaction Systems: This course focuses on developing interfaces that enable seamless communication between humans and robots, including gesture recognition, voice command systems, and haptic feedback mechanisms.
- Mobile Robot Navigation and SLAM: Students study algorithms for robot localization, mapping, and path planning using sensor data. The course includes hands-on implementation of Simultaneous Localization and Mapping (SLAM) techniques.
- Industrial Robotics and Automation: This elective covers the integration of robots in manufacturing environments, including PLC programming, industrial communication protocols, and collaborative robotics.
- Robotics in Healthcare Applications: Students explore how robotics can improve patient care, rehabilitation, and surgical procedures. Topics include assistive devices, prosthetics, and robotic surgery systems.
- Autonomous Vehicles and Navigation: This course covers autonomous driving technologies, including sensor fusion, localization, and decision-making in complex traffic scenarios.
- Robotics Ethics and Governance: An interdisciplinary course examining ethical dilemmas in robotics, including safety, privacy, bias, and societal impact of AI-driven systems.
Project-Based Learning Philosophy
The department emphasizes a project-based learning approach throughout the curriculum to ensure that students gain real-world experience and develop critical problem-solving skills. Projects are structured to progress from simple laboratory experiments to complex, multidisciplinary capstone projects.
In the early semesters, students engage in mini-projects, which are typically short-term assignments designed to reinforce classroom concepts. These projects often involve building and testing small robotic systems such as line-following robots or basic manipulator arms.
As students advance, they move into more complex capstone projects, where they collaborate in teams to design and implement full-scale robotic solutions. These projects span multiple disciplines and require integration of mechanical design, software development, control theory, and data analysis.
The final-year project is an individual endeavor that allows students to pursue a topic of personal interest under the guidance of a faculty mentor. Students are encouraged to select projects that align with current industry trends or emerging research areas in robotics.
Evaluation criteria for these projects include:
- Technical Competence
- Innovation and Creativity
- Team Collaboration
- Presentation and Documentation
- Impact and Relevance to Industry Needs