Curriculum Overview
The Bachelor of Robotics curriculum at Prashanti Institute of Technology and Science is designed to provide students with a solid foundation in both theoretical concepts and practical skills required for designing, building, and deploying robotic systems. The program spans eight semesters and includes core courses, departmental electives, science electives, and laboratory work.
Course Structure by Semester
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | PHY101 | Engineering Physics | 3-1-0-4 | - |
| 1 | MAT101 | Calculus and Linear Algebra | 3-1-0-4 | - |
| 1 | CSE101 | Introduction to Programming | 2-1-2-5 | - |
| 1 | MAT102 | Differential Equations | 3-1-0-4 | - |
| 1 | CSE102 | Data Structures and Algorithms | 3-1-0-4 | CSE101 |
| 1 | ME101 | Engineering Mechanics | 3-1-0-4 | - |
| 2 | PHY201 | Electromagnetic Fields and Waves | 3-1-0-4 | PHY101 |
| 2 | MAT201 | Probability and Statistics | 3-1-0-4 | MAT101 |
| 2 | CSE201 | Object-Oriented Programming with C++ | 2-1-2-5 | CSE101 |
| 2 | ME201 | Mechanics of Materials | 3-1-0-4 | ME101 |
| 2 | ECE201 | Basic Electronics Circuits | 3-1-0-4 | - |
| 3 | CSE301 | Database Management Systems | 3-1-0-4 | CSE102 |
| 3 | ECE301 | Signals and Systems | 3-1-0-4 | ECE201 |
| 3 | ME301 | Thermodynamics | 3-1-0-4 | ME101 |
| 3 | CSE302 | Operating Systems | 3-1-0-4 | CSE102 |
| 3 | ME302 | Mechanical Design and Drafting | 2-1-2-5 | ME101 |
| 4 | CSE401 | Computer Vision | 3-1-0-4 | ECE301 |
| 4 | ME401 | Robotics Fundamentals | 3-1-0-4 | ME302 |
| 4 | ECE401 | Embedded Systems | 3-1-0-4 | ECE201 |
| 4 | CSE402 | Machine Learning Basics | 3-1-0-4 | CSE102 |
| 4 | ME402 | Control Systems | 3-1-0-4 | ME301 |
| 5 | CSE501 | Advanced Machine Learning | 3-1-0-4 | CSE402 |
| 5 | ECE501 | Robot Sensors and Actuators | 3-1-0-4 | ECE401 |
| 5 | ME501 | Robot Dynamics and Kinematics | 3-1-0-4 | ME402 |
| 5 | CSE502 | Software Engineering for Robotics | 3-1-0-4 | CSE301 |
| 5 | ME502 | Industrial Robotics Applications | 3-1-0-4 | ME401 |
| 6 | CSE601 | Deep Learning for Robotics | 3-1-0-4 | CSE501 |
| 6 | ECE601 | Advanced Control Theory | 3-1-0-4 | ECE501 |
| 6 | ME601 | Human-Robot Interaction | 3-1-0-4 | ME501 |
| 6 | CSE602 | Autonomous Navigation Systems | 3-1-0-4 | CSE502 |
| 6 | ME602 | Biomedical Robotics | 3-1-0-4 | ME502 |
| 7 | CSE701 | Robotics Capstone Project I | 3-1-0-4 | CSE602 |
| 7 | ECE701 | Robotic Hardware Design | 3-1-0-4 | ECE601 |
| 7 | ME701 | Advanced Robotics Simulation | 3-1-0-4 | ME602 |
| 7 | CSE702 | AI in Robotics Applications | 3-1-0-4 | CSE701 |
| 8 | CSE801 | Robotics Capstone Project II | 6-2-0-10 | CSE702 |
| 8 | ECE801 | Robotic Systems Integration | 3-1-0-4 | ECE701 |
| 8 | ME801 | Robotics Internship Experience | 3-1-0-4 | ME701 |
Advanced Departmental Electives
The following advanced departmental electives are offered in the second year and beyond, providing students with specialized knowledge in various robotics domains:
- Computer Vision for Robotics: This course introduces students to image processing techniques, feature detection, object recognition, and camera calibration. It covers both classical and deep learning-based approaches to computer vision tasks relevant to robotics.
- Embedded Systems Design: Students learn how to design and implement embedded systems using microcontrollers and real-time operating systems. The course includes hands-on projects involving sensor integration and motor control.
- Control Systems for Robots: This elective delves into advanced topics in feedback control theory, including state-space modeling, PID controllers, and stability analysis of robotic systems.
- Human-Robot Interaction (HRI): Focuses on designing intuitive interfaces and communication protocols between humans and robots. Students explore ethical considerations, user experience design, and social robotics.
- Machine Learning for Robotics: Covers machine learning algorithms specifically tailored for robotics applications such as path planning, perception, and decision-making in uncertain environments.
- Mobile Robotics: Introduces students to the design and implementation of mobile robots, covering navigation strategies, SLAM algorithms, and localization techniques.
- Robot Simulation Tools: Students gain experience using industry-standard simulation platforms like Gazebo, ROS, and MATLAB/Simulink for testing and validating robotic designs before physical prototyping.
- Industrial Automation Technologies: Explores automation technologies used in manufacturing, including programmable logic controllers (PLCs), SCADA systems, and industrial communication protocols.
- Bio-inspired Robotics: This course examines how biological systems inspire robotic design, focusing on locomotion mechanisms, sensing strategies, and adaptive behaviors found in nature.
- Swarm Robotics: Teaches students about multi-agent systems, coordination algorithms, and distributed control methods used in swarm robotics applications.
Project-Based Learning Philosophy
The program follows a strong project-based learning model that emphasizes hands-on experience and real-world problem-solving. From the first semester, students are introduced to mini-projects that help them apply theoretical concepts learned in class. These projects are designed to be collaborative, encouraging teamwork and communication skills.
Mini-Projects
Mini-projects are conducted throughout the program's duration, starting from the second year. Each project lasts approximately 4-6 weeks and involves teams of 3-5 students working under faculty supervision. Projects can range from simple mechanical designs to complex AI-based solutions.
Final-Year Thesis/Capstone Project
The capstone project is a significant milestone in the program, requiring students to undertake an original research or design project that integrates knowledge from all areas of robotics. The final project must be completed over two semesters and submitted as a thesis along with a working prototype or simulation.
Project Selection and Mentorship
Students are encouraged to propose their own ideas for projects, subject to approval by faculty mentors. However, if students require guidance, they can choose from a list of approved research topics provided by faculty members. Mentors play a crucial role in guiding students through the project lifecycle, from concept development to execution and presentation.