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.

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