AI for Robotics in Mechanical Engineering
Lead the Future: Integrate AI into Robotics for Real-World Innovation
Early access to e-LMS included
About This Course
The AI for Robotics in Mechanical Engineering program at NanoSchool.in is designed to bridge the gap between artificial intelligence and robotics in industrial applications. Participants will learn the fundamentals of robotic programming and control, machine learning for predictive maintenance, and real-time control applications. This program prepares learners to thrive in high-tech environments like smart manufacturing, where AI-driven solutions are essential for efficiency and innovation.
Aim
To equip mechanical engineers and automation professionals with advanced skills in robotic programming, machine learning, and real-time control to address complex industrial automation challenges using AI-driven robotic systems.
Program Objectives
- Understand: Core concepts of robotics, AI, and their combined applications in mechanical engineering.
- Learn: To program robots with Python and C++ for real-time control and motion planning.
- Build: Machine learning models for predictive maintenance in robotics.
- Implement: AI solutions for automation and quality control in manufacturing settings.
Program Structure
The program is structured into five modules, building from foundational concepts in AI and robotics to advanced applications for industrial settings.
Module 1: Fundamentals of Robotics and AI Integration
- Overview: This module introduces basic robotic systems and how AI can be integrated to enhance their capabilities, focusing on control systems and robotic kinematics.
- Topics Covered:
- Basics of robotics: Kinematics, dynamics, and control
- Overview of AI algorithms in robotics
- Programming fundamentals for robots
- Project: Program a robotic arm to perform simple movements based on AI-driven instructions.
Module 2: Robotic Programming and Control Systems
- Overview: Learn programming for robotic control systems using languages such as Python and C++, focusing on AI applications in real-time control and robotic automation.
- Topics Covered:
- Programming basics for robotic control systems
- Real-time control in robotic applications
- Motion planning and pathfinding with AI
- Project: Program a robot to navigate a simple environment using AI-based pathfinding.
Module 3: Machine Learning for Predictive Maintenance in Robotics
- Overview: This module focuses on applying machine learning for predictive maintenance in robotics, enabling systems to anticipate and prevent failures before they occur.
- Topics Covered:
- Machine learning algorithms for predictive maintenance
- Sensor data processing and anomaly detection
- Implementing predictive models in robotic systems
- Project: Build a predictive maintenance model using sensor data from robotic arms to detect potential faults.
Module 4: AI-Driven Robotics in Industrial Automation
- Overview: Dive into the applications of AI-driven robotics in industrial automation, covering areas such as robotic welding, assembly, and quality control in manufacturing.
- Topics Covered:
- Industrial robotic applications in manufacturing
- AI in quality control and defect detection
- Integration of AI in assembly line robotics
- Project: Design a robotic workflow using AI for defect detection in a simulated manufacturing environment.
Module 5: Capstone Project in AI for Robotics
- Overview: The capstone project allows you to showcase your skills by developing an AI-integrated robotic solution for a real-world application.
- Project Options:
- Develop a robotic system for automated inspection and quality control using AI vision.
- Create an AI-driven robotic arm that performs tasks based on real-time sensor data.
- Design a predictive maintenance program for an industrial robotic system.
- Outcome: Demonstrate your ability to integrate AI into robotic systems, providing innovative solutions to complex industrial challenges.
Tools and Software Used
Gain hands-on experience with tools essential for AI and robotics:
- Robot Operating System (ROS): For programming and controlling robotic systems.
- Python and C++: Programming languages for AI-driven robotic applications.
- TensorFlow and PyTorch: For machine learning models in predictive maintenance.
- MATLAB: For data analysis and control system simulations.
Who Should Enrol?
This program is best suited for:
- Mechanical Engineers interested in advancing their knowledge in AI-driven automation and robotics.
- Robotics Professionals seeking to enhance their skills in programming and AI integration.
- Automation Engineers looking to optimize robotic systems in industrial environments.
Program Outcomes
- Gain a solid foundation in robotic control systems and AI integration.
- Apply machine learning to predict and prevent robotic system failures.
- Develop and implement AI-driven automation solutions for industrial robotics.
- Enhance productivity and quality control in manufacturing through innovative AI applications.
Fee Structure
Standard: ₹9,998 | $298
Discounted: ₹4999 | $149
We accept 20+ global currencies. View list →
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- 1:1 project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
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