Computing and Simulation Laboratory

The Computing and Simulation Laboratory in the Mechatronics Department is a cutting-edge facility designed to foster innovation and practical expertise in the integration of computational techniques, artificial intelligence and simulation into mechatronic systems. This laboratory serves as a dynamic space where students and researchers can explore advanced concepts and develop hands-on skills in areas such as visual computing, machine learning, robotics and autonomous systems. The lab emphasizes the application of computational thinking and problem-solving techniques to model, simulate and analyze complex mechatronic systems. Students gain experience in designing and implementing algorithms for tasks such as image processing, object recognition and real-time decision-making, which are critical for applications like autonomous vehicles and vision-guided robotics. The facility also supports the development and training of neural networks and deep learning models, enabling students to tackle challenges in perception, planning and control. In addition to computational techniques, the laboratory focuses on the integration of artificial intelligence into robotic systems, allowing students to program and test robots for autonomous navigation, manipulation and interaction with their environments. The lab’s resources and tools are tailored to bridge the gap between theoretical knowledge and practical implementation, preparing students for careers in fields such as robotics, automation and AI-driven systems. Overall, the Computing and Simulation Laboratory is a vital hub for innovation providing students with the skills and experience needed to design, simulate and optimize intelligent mechatronic systems for real-world applications. It plays a crucial role in shaping the next generation of engineers and researchers in the field of mechatronics.

• To provide hands-on experience in computational techniques and simulation tools for modeling, analyzing and optimizing complex mechatronic systems.
• To enable students to design and implement algorithms for visual computing, image processing and real-time decision-making in applications such as robotics and autonomous systems.
• To foster expertise in artificial intelligence and machine learning by offering resources for development, training and testing neural networks and deep learning models.
• To facilitate the integration of AI and vision systems into robotics for tasks such as autonomous navigation, object manipulation and environment interaction.
• To bridge the gap between theoretical knowledge and practical implementation by providing a state-of-the-art environment for experimentation, innovation and problem-solving in mechatronics.