Curriculum Overview
The robotics program at Institute of Engineering Jiwaji University Gwalior is structured to provide a comprehensive and progressive learning experience. The curriculum is divided into 8 semesters, with each semester building upon the previous one to ensure that students develop both theoretical knowledge and practical skills.
Semester-wise Course Structure
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | PHYS101 | Physics for Engineering | 3-1-0-4 | - |
| 1 | MATH101 | Mathematics I | 4-0-0-4 | - |
| 1 | CSE101 | Introduction to Programming | 3-0-2-5 | - |
| 1 | ENG101 | Engineering Graphics & Design | 2-1-0-3 | - |
| 1 | MECH101 | Introduction to Mechanics | 3-0-0-3 | - |
| 1 | ENG102 | Technical Communication | 2-0-0-2 | - |
| 2 | MATH102 | Mathematics II | 4-0-0-4 | MATH101 |
| 2 | PHYS102 | Electromagnetic Fields and Waves | 3-1-0-4 | PHYS101 |
| 2 | CSE102 | Data Structures and Algorithms | 3-0-2-5 | CSE101 |
| 2 | MECH102 | Strength of Materials | 3-0-0-3 | MECH101 |
| 2 | ELEC101 | Basic Electrical Engineering | 3-1-0-4 | - |
| 2 | ENG103 | Introduction to Robotics | 2-0-0-2 | - |
| 3 | MATH103 | Mathematics III | 4-0-0-4 | MATH102 |
| 3 | ELEC102 | Circuit Analysis | 3-1-0-4 | ELEC101 |
| 3 | CSE103 | Object-Oriented Programming in C++ | 3-0-2-5 | CSE102 |
| 3 | MECH103 | Thermodynamics | 3-0-0-3 | MECH102 |
| 3 | ROBO101 | Robotics Fundamentals | 3-1-0-4 | ENG103 |
| 3 | STAT101 | Probability and Statistics | 3-0-0-3 | - |
| 4 | MATH104 | Mathematics IV | 4-0-0-4 | MATH103 |
| 4 | ELEC103 | Electronics Devices and Circuits | 3-1-0-4 | ELEC102 |
| 4 | CSE104 | Database Systems | 3-0-2-5 | CSE103 |
| 4 | MECH104 | Mechanics of Solids | 3-0-0-3 | MECH103 |
| 4 | ROBO102 | Control Systems | 3-1-0-4 | ROBO101 |
| 4 | SIGSYS101 | Signals and Systems | 3-1-0-4 | - |
| 5 | MATH105 | Mathematics V | 4-0-0-4 | MATH104 |
| 5 | ELEC104 | Power Electronics | 3-1-0-4 | ELEC103 |
| 5 | CSE105 | Computer Architecture | 3-0-2-5 | CSE104 |
| 5 | MECH105 | Machine Design | 3-0-0-3 | MECH104 |
| 5 | ROBO103 | Mechatronics | 3-1-0-4 | ROBO102 |
| 5 | ROBO104 | Sensor Technologies | 3-1-0-4 | - |
| 6 | MATH106 | Mathematics VI | 4-0-0-4 | MATH105 |
| 6 | ELEC105 | Communications Systems | 3-1-0-4 | ELEC104 |
| 6 | CSE106 | Operating Systems | 3-0-2-5 | CSE105 |
| 6 | MECH106 | Manufacturing Processes | 3-0-0-3 | MECH105 |
| 6 | ROBO105 | Robotics Algorithms | 3-1-0-4 | ROBO103 |
| 6 | ROBO106 | Embedded Systems | 3-1-0-4 | - |
| 7 | ROBO201 | Advanced Robotics Concepts | 3-1-0-4 | ROBO105 |
| 7 | ROBO202 | Artificial Intelligence in Robotics | 3-1-0-4 | - |
| 7 | ROBO203 | Human-Robot Interaction | 3-1-0-4 | - |
| 7 | ROBO204 | Autonomous Navigation | 3-1-0-4 | - |
| 7 | ROBO205 | Research Methodology | 2-0-0-2 | - |
| 8 | ROBO301 | Final Year Project | 4-0-0-8 | ROBO201, ROBO202, ROBO203, ROBO204 |
| 8 | ROBO302 | Capstone Seminar | 2-0-0-2 | - |
Advanced Departmental Electives
Students can choose from a variety of advanced elective courses based on their interests and career goals:
Artificial Intelligence in Robotics
This course explores how AI techniques such as machine learning, neural networks, and deep learning are applied to robotics. Students will learn to develop intelligent algorithms that enable robots to perceive their environment, reason about decisions, and adapt to changing conditions.
Learning Objectives:
- Understand the fundamentals of AI and its application in robotics
- Develop neural networks for robotic perception and decision-making
- Implement machine learning algorithms for robot control and behavior
- Analyze real-world case studies in AI-driven robotics
Human-Robot Interaction
This course focuses on designing interfaces and communication protocols that allow effective interaction between humans and robots. It covers topics such as cognitive systems, user experience design, and ethical considerations in robotics.
Learning Objectives:
- Understand principles of human factors in robotics
- Design intuitive interfaces for robotic systems
- Evaluate the impact of robotics on society and ethics
- Develop collaborative robots that work effectively with humans
Autonomous Navigation
This course covers the techniques used for autonomous navigation in robotics, including SLAM algorithms, localization, path planning, and sensor fusion. Students will gain hands-on experience with autonomous robots.
Learning Objectives:
- Understand principles of robot navigation and localization
- Implement SLAM algorithms for mapping environments
- Design path planning strategies for dynamic obstacles
- Integrate sensor data for accurate navigation systems
Mobile Manipulation
This course focuses on robots that combine mobility with manipulation capabilities. Students will learn about mobile platforms, manipulator arms, and the integration of both functionalities.
Learning Objectives:
- Understand design principles for mobile manipulators
- Implement control strategies for combined mobility and manipulation
- Simulate and test mobile manipulator systems
- Evaluate performance in various environments
Robotics Algorithms
This course delves into the mathematical foundations of robotics algorithms, including kinematics, dynamics, control theory, and optimization techniques. Students will implement these algorithms using programming languages like Python and MATLAB.
Learning Objectives:
- Master mathematical tools for robotics analysis
- Implement kinematic and dynamic models for robotic systems
- Apply control theory to real-world robot systems
- Optimize robotic algorithms for performance
Rehabilitation Robotics
This elective explores the application of robotics in healthcare, particularly in rehabilitation and assistive technologies. Students will study prosthetics, exoskeletons, and other assistive devices.
Learning Objectives:
- Understand biomechanics and human movement patterns
- Design robotic systems for physical therapy applications
- Develop assistive technologies for individuals with disabilities
- Evaluate effectiveness of rehabilitation robots
Space Robotics
This course examines the challenges and solutions involved in designing robots for space exploration. Topics include microgravity environments, radiation resistance, communication delays, and autonomous operation.
Learning Objectives:
- Understand unique challenges of space robotics
- Design robots for planetary exploration
- Implement autonomous systems for remote operations
- Simulate space environments for testing purposes
Cybersecurity in Robotics
This course addresses the security aspects of robotic systems, including threats, vulnerabilities, and mitigation strategies. Students will learn to protect robots from cyber attacks and ensure data integrity.
Learning Objectives:
- Identify common cybersecurity threats in robotics
- Implement secure communication protocols for robots
- Develop intrusion detection systems for robotic networks
- Evaluate security measures in real-world applications
Sensor Fusion and Integration
This course covers the integration of multiple sensors to enhance robot perception and decision-making. Students will learn about sensor calibration, data fusion techniques, and implementation strategies.
Learning Objectives:
- Understand principles of sensor integration
- Implement sensor fusion algorithms for improved accuracy
- Calibrate various types of sensors
- Evaluate performance of integrated sensor systems
Industrial Automation
This course focuses on the application of robotics in industrial environments. Students will study automation systems, PLC programming, and integration with manufacturing processes.
Learning Objectives:
- Understand industrial automation principles
- Program PLCs for robotic control
- Integrate robots into manufacturing workflows
- Evaluate productivity improvements from automation
Project-Based Learning Philosophy
The robotics program at Institute of Engineering Jiwaji University Gwalior emphasizes project-based learning as a core component of education. This approach ensures that students apply theoretical knowledge to real-world problems and develop practical skills.
Mini-Projects
Mini-projects are conducted throughout the academic year, typically lasting 2-3 months. These projects allow students to:
- Apply concepts learned in classroom settings
- Work collaboratively in teams
- Develop problem-solving and critical thinking skills
- Present findings to faculty and peers
Mini-projects are evaluated based on:
- Technical competence
- Innovation and creativity
- Teamwork and communication
- Presentation quality
- Documentation and report writing
Final-Year Thesis/Capstone Project
The final-year capstone project is a significant undertaking that spans the entire semester. Students work on a substantial research or development project under faculty guidance, typically involving:
- Original research contributions
- Advanced technical implementation
- Integration of multiple disciplines
- Real-world application and impact
The project is selected through a process that includes:
- Faculty mentorship matching based on interests
- Project proposal submission and review
- Final approval from academic committee
- Regular progress reports and milestones
Evaluation criteria for the capstone project include:
- Technical depth and rigor
- Originality and innovation
- Practical relevance and potential impact
- Documentation quality and clarity
- Presentation and defense of results