Curriculum Overview
The Bachelor of Robotics program at Iasscom Fortune Institute of Technology is meticulously structured to provide students with a robust foundation in both theoretical knowledge and practical application. The curriculum emphasizes interdisciplinary learning, encouraging students to integrate concepts from multiple fields such as computer science, electrical engineering, mechanical engineering, and physics.
Core Subjects
The core subjects are designed to build essential skills required for advanced robotics applications:
- Mathematics: Calculus, differential equations, linear algebra, probability, statistics, optimization, numerical methods
- Physics: Classical mechanics, electromagnetism, thermodynamics, quantum physics, optics, modern physics
- Computer Science: Programming fundamentals, data structures, algorithms, databases, machine learning, AI techniques
- Electrical Engineering: Circuits and systems, digital electronics, microprocessors, control systems, signal processing
- Mechanical Engineering: Mechanics of materials, design principles, manufacturing processes, kinematics, dynamics
Departmental Electives
Students are exposed to a wide range of departmental electives that allow them to specialize according to their interests and career goals:
- Deep Learning and Neural Networks: Covers neural network architectures, backpropagation, convolutional networks, recurrent networks, transformers
- Computer Vision and Image Processing: Focuses on image acquisition, filtering, segmentation, feature extraction, object recognition
- Reinforcement Learning and Autonomous Agents: Explores Q-learning, policy gradients, actor-critic methods, multi-agent systems
- Human-Robot Interaction and Interface Design: Addresses gesture recognition, voice commands, tactile feedback, user experience design
- Advanced Control Systems for Robotics: Discusses optimal control, robust control, adaptive control, nonlinear control strategies
- Robotics Hardware and Embedded System Integration: Covers sensor integration, microcontroller programming, motor drives, real-time systems
- AI Ethics and Responsible AI Development: Examines bias mitigation, fairness, transparency, accountability in autonomous systems
- Autonomous Navigation and SLAM Algorithms: Studies simultaneous localization and mapping algorithms, sensor fusion, graph optimization
- Bio-Inspired Robotics: Investigates biological systems such as insect flight, fish swimming, mammalian locomotion
- Swarm Robotics and Collective Behavior: Focuses on decentralized control algorithms, flocking behavior, consensus protocols
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that hands-on experience drives deeper understanding and fosters innovation. Mini-projects are introduced early in the curriculum to familiarize students with problem-solving approaches and teamwork dynamics. These projects typically last 3-4 weeks and involve small groups of 3-5 students working under faculty guidance.
Final-year capstone projects span 6 months and require students to propose, design, implement, and present a comprehensive solution addressing a real-world challenge in robotics. Projects are selected through a competitive process involving faculty advisors, industry partners, and student proposals. Students receive mentorship throughout the project lifecycle, from concept development to final demonstration.
Course Structure Table
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | MATH101 | Calculus and Differential Equations | 4-0-0-4 | - |
| 1 | PHYS101 | Basic Physics for Engineers | 3-0-0-3 | - |
| 1 | CS101 | Introduction to Programming | 3-0-2-4 | - |
| 1 | ME101 | Engineering Mechanics | 3-0-0-3 | - |
| 1 | EE101 | Basic Electrical Circuits | 3-0-0-3 | - |
| 1 | PHYS102 | Modern Physics and Applications | 3-0-0-3 | - |
| 1 | LAB101 | Programming Lab | 0-0-2-2 | - |
| 2 | MATH201 | Linear Algebra and Statistics | 4-0-0-4 | MATH101 |
| 2 | PHYS201 | Thermodynamics and Fluid Mechanics | 3-0-0-3 | PHYS101 |
| 2 | CS201 | Data Structures and Algorithms | 3-0-2-4 | CS101 |
| 2 | ME201 | Mechanics of Materials | 3-0-0-3 | ME101 |
| 2 | EE201 | Electromagnetic Fields and Circuits | 3-0-0-3 | EE101 |
| 2 | LAB201 | Computer Programming Lab | 0-0-2-2 | CS101 |
| 3 | MATH301 | Probability and Random Processes | 4-0-0-4 | MATH201 |
| 3 | PHYS301 | Quantum Physics and Applications | 3-0-0-3 | PHYS102 |
| 3 | CS301 | Database Systems and Machine Learning Fundamentals | 3-0-2-4 | CS201 |
| 3 | ME301 | Design of Mechanical Components | 3-0-0-3 | ME201 |
| 3 | EE301 | Digital Electronics and Microprocessors | 3-0-0-3 | EE201 |
| 3 | LAB301 | Electronics Lab | 0-0-2-2 | EE201 |
| 4 | MATH401 | Advanced Calculus and Optimization | 4-0-0-4 | MATH301 |
| 4 | PHYS401 | Optics and Modern Physics Applications | 3-0-0-3 | PHYS301 |
| 4 | CS401 | Advanced Algorithms and AI Techniques | 3-0-2-4 | CS301 |
| 4 | ME401 | Manufacturing Processes and Automation | 3-0-0-3 | ME301 |
| 4 | EE401 | Control Systems and Signal Processing | 3-0-0-3 | EE301 |
| 4 | LAB401 | Microcontroller and Embedded Systems Lab | 0-0-2-2 | EE301 |
| 5 | MATH501 | Numerical Methods and Computational Techniques | 4-0-0-4 | MATH401 |
| 5 | PHYS501 | Relativity and Quantum Mechanics | 3-0-0-3 | PHYS401 |
| 5 | CS501 | Computer Vision and Image Processing | 3-0-2-4 | CS401 |
| 5 | ME501 | Robotics and Automation Systems | 3-0-0-3 | ME401 |
| 5 | EE501 | Power Electronics and Drives | 3-0-0-3 | EE401 |
| 5 | LAB501 | Robotics Lab | 0-0-2-2 | - |
| 6 | MATH601 | Advanced Probability and Stochastic Processes | 4-0-0-4 | MATH501 |
| 6 | PHYS601 | Applications of Quantum Physics | 3-0-0-3 | PHYS501 |
| 6 | CS601 | Deep Learning and Neural Networks | 3-0-2-4 | CS501 |
| 6 | ME601 | Advanced Manufacturing and Industrial Robotics | 3-0-0-3 | ME501 |
| 6 | EE601 | Robotics Control Systems | 3-0-0-3 | EE501 |
| 6 | LAB601 | Advanced Robotics Lab | 0-0-2-2 | - |
| 7 | MATH701 | Mathematical Modeling and Simulation | 4-0-0-4 | MATH601 |
| 7 | PHYS701 | Applications in Nanotechnology and Biophysics | 3-0-0-3 | PHYS601 |
| 7 | CS701 | Reinforcement Learning and Autonomous Agents | 3-0-2-4 | CS601 |
| 7 | ME701 | Human-Robot Interaction and Interface Design | 3-0-0-3 | ME601 |
| 7 | EE701 | Advanced Control Theory for Robotics | 3-0-0-3 | EE601 |
| 7 | LAB701 | Capstone Project Lab | 0-0-2-2 | - |
| 8 | MATH801 | Advanced Optimization and Numerical Methods | 4-0-0-4 | MATH701 |
| 8 | PHYS801 | Emerging Technologies in Physics and Robotics | 3-0-0-3 | PHYS701 |
| 8 | CS801 | AI Ethics and Responsible AI Development | 3-0-2-4 | CS701 |
| 8 | ME801 | Advanced Robotics Systems Design | 3-0-0-3 | ME701 |
| 8 | EE801 | Robotics Hardware and Embedded System Integration | 3-0-0-3 | EE701 |
| 8 | LAB801 | Final Year Capstone Project Lab | 0-0-2-2 | - |