Curriculum Overview for Robotics Program at Nagaji Institute of Technology and Management

Semester-wise Course Structure

The Robotics program follows a rigorous 8-semester curriculum designed to progressively build technical expertise, problem-solving capabilities, and industry readiness. The structure includes core courses, departmental electives, science electives, and laboratory components.

Semester	Course Code	Course Title	Credits (L-T-P-C)	Prerequisites
1	ENG101	English for Engineers	2-0-0-2	-
1	MAT101	Mathematics I	4-0-0-4	-
1	PHY101	Physics for Engineers	3-0-0-3	-
1	CSE101	Introduction to Programming	2-0-2-4	-
1	ME101	Engineering Drawing & Graphics	2-0-0-2	-
1	CHM101	Chemistry for Engineers	3-0-0-3	-
1	L101	Programming Lab	0-0-2-2	CSE101
2	MAT102	Mathematics II	4-0-0-4	MAT101
2	PHY102	Physics of Motion	3-0-0-3	PHY101
2	CSE102	Data Structures & Algorithms	3-0-0-3	CSE101
2	ME102	Engineering Mechanics	3-0-0-3	-
2	ECE101	Basic Electronics	3-0-0-3	-
2	L201	Lab: Data Structures & Algorithms	0-0-2-2	CSE102
3	MAT201	Mathematics III	4-0-0-4	MAT102
3	DIG101	Digital Electronics	3-0-0-3	ECE101
3	CSE201	Database Systems	3-0-0-3	CSE102
3	ME201	Mechanics of Materials	3-0-0-3	ME102
3	ECE201	Signals & Systems	3-0-0-3	-
3	L301	Lab: Digital Electronics	0-0-2-2	DIG101
4	MAT202	Mathematics IV	4-0-0-4	MAT201
4	CSE301	Operating Systems	3-0-0-3	CSE201
4	ME301	Mechanics of Machines	3-0-0-3	ME201
4	ECE301	Control Systems	3-0-0-3	ECE201
4	L401	Lab: Control Systems	0-0-2-2	ECE301
5	CSE401	Artificial Intelligence	3-0-0-3	CSE301
5	ME401	Robot Kinematics	3-0-0-3	ME301
5	ECE401	Sensor Technology	3-0-0-3	ECE301
5	L501	Lab: Robotics Fundamentals	0-0-2-2	-
6	CSE501	Computer Vision	3-0-0-3	CSE401
6	ME501	Robotic Manipulation	3-0-0-3	ME401
6	ECE501	Embedded Systems	3-0-0-3	ECE401
6	L601	Lab: Embedded Robotics	0-0-2-2	-
7	CSE601	Human-Robot Interaction	3-0-0-3	CSE501
7	ME601	Swarm Robotics	3-0-0-3	ME501
7	ECE601	Robotic Perception	3-0-0-3	ECE501
7	L701	Lab: Advanced Robotics	0-0-2-2	-
8	CSE701	Final Year Project	4-0-0-4	-
8	L801	Project Lab	0-0-4-4	-

Advanced Departmental Electives

The following are advanced departmental elective courses offered in the Robotics program:

1. Artificial Intelligence for Robotics

This course focuses on integrating AI techniques into robotic systems, including machine learning algorithms, neural networks, and deep learning applications for perception and decision-making. Students learn to develop intelligent robotic agents capable of autonomous behavior.

2. Computer Vision in Robotics

Students explore image processing, feature detection, object recognition, and real-time video analysis using OpenCV, MATLAB, and TensorFlow. This course is essential for developing robots that can interpret visual information.

3. Robotic Manipulation

This advanced course covers the mechanics of robotic arms, grasping strategies, force control, and motion planning. Students learn to design and implement manipulation systems using industrial robot platforms and simulation tools.

4. Human-Robot Interaction (HRI)

This elective delves into the psychology and ethics of human-robot collaboration. Topics include user experience design, emotional AI, natural language processing for robots, and designing inclusive robotics interfaces.

5. Embedded Systems for Robotics

Focused on microcontrollers, real-time operating systems, and hardware-software integration, this course prepares students to build embedded robotic systems using ARM Cortex-M series, Arduino, and Raspberry Pi.

6. Sensor Technology for Robots

This course introduces various sensors used in robotics—such as LiDAR, IMU, ultrasonic sensors, and cameras—and their integration into robotic platforms for navigation and environmental awareness.

7. Swarm Robotics

Students learn about decentralized control, collective behavior algorithms, communication protocols, and simulation of multi-robot systems using tools like ROS and Gazebo.

8. Bio-Inspired Robotics

This course explores how nature inspires robotic design, including legged locomotion, flight dynamics, and soft robotics. It includes hands-on projects involving biomimetic robots.

9. Robotic Perception and Mapping

Focuses on SLAM (Simultaneous Localization and Mapping) algorithms, sensor fusion techniques, and localization methods for mobile robots in indoor and outdoor environments.

10. Industrial Automation with Robotics

This elective bridges robotics with manufacturing automation, covering topics such as PLC programming, SCADA systems, robot safety standards, and integration of robotic cells into production lines.

11. Mobile Robotics

Students study the design and control of wheeled, legged, and aerial robots. Emphasis is placed on navigation, path planning, obstacle avoidance, and localization in dynamic environments.

12. Energy-Efficient Robotics

This course focuses on designing low-power robotic systems using renewable energy sources, battery management, and optimization of power consumption for long-term deployment.

Project-Based Learning Philosophy

Nagaji Institute's approach to robotics education emphasizes project-based learning as a core component of the curriculum. This philosophy encourages students to apply theoretical knowledge in real-world scenarios, fostering innovation, teamwork, and critical thinking.

Mini-Projects (First Year)

In the first year, students work on mini-projects that introduce them to robotics fundamentals. These projects are typically completed in groups of 3–5 students over a period of 6 weeks. Examples include building a line-following robot or designing a simple manipulator using Arduino.

Final-Year Thesis/Capstone Project

The final year involves a major capstone project where students develop an original robotic solution from concept to implementation. The project is guided by faculty mentors and often collaborates with industry partners. Students must present their work at the annual Robotics Exhibition, where they are evaluated by experts from academia and industry.

Project Selection Process

Students can choose their projects based on personal interests or assigned topics from faculty research areas. Projects are reviewed for feasibility, originality, and alignment with program learning outcomes. Faculty mentors are assigned based on expertise and availability, ensuring personalized guidance throughout the project lifecycle.

Evaluation Criteria

Projects are evaluated based on several criteria:

• Technical Execution: Adherence to specifications, use of appropriate technologies, and quality of implementation.
• Innovation: Originality of approach, creative solutions, and contribution to the field.
• Presentation: Clarity of explanation, visual aids, and ability to defend the project.
• Teamwork: Collaboration, role distribution, and group dynamics.
• Documentation: Quality of reports, code documentation, and adherence to academic standards.