Collaborative Robotics and Smart Mechatronic Systems
Course provided by Model Institute of Engineering & Technology
8 modules
Explore the fundamentals of Cyber Physical Systems
5 Level NCrF
National Credit Framework
60 Hours
Flexible Learning
Beginner Level
No prior experience required
Diploma Program
02 Credits
Course Overview
This course provides hands-on knowledge and practical skills in robotic system design, integration, and control. Learners will explore the fundamentals of robotic manipulators and end-effectors, integrating them with sensors, actuators, and embedded controllers. The course emphasizes the use of both electrical and hydraulic drive systems for robotic movement and precision control. Students will also gain experience programming robotic arms using Mitsubishi robotic kits alongside open-source platforms. Additionally, MATLAB-Simulink will be applied for control system modeling, simulation, and diagnostics, equipping learners with the ability to design, test, and optimize robotic systems for real-world industrial applications.
Key Learning Highlights
- Design and simulate robotic manipulators and end-effectors for industrial applications.
- Integrate sensors, actuators, and embedded controllers into robotic systems.
- Implement electrical and hydraulic drive systems for robotic motion control.
- Program robotic arms using Mitsubishi kits and open-source tools.
- Apply MATLAB-Simulink for system modeling, simulation, and troubleshooting.
Tools & Platform Used
Learning Outcome
After completing this course, learners will be able to:
Design and simulate robotic manipulators, grippers, and end-effectors.
Integrate robotic systems with sensors, actuators, and embedded controllers for automation.
Implement electrical and hydraulic drive systems for precise robotic motion.
Program and operate robotic arms using Mitsubishi kits and open-source platforms.
Use MATLAB-Simulink for modeling, simulation, and performance diagnostics of robotic systems.
Master the course with just 8 Modules
This course introduces the foundations of industrial robotics, covering the history, types, and collaborative systems. Learners will study mechatronic design principles, manipulator and end-effector kinematics, and integration of sensors, actuators, and electro-hydraulic drives. The course also explores robotic vision and machine vision techniques, IIoT-enabled robotic applications, and the use of MATLAB-Simulink for control modeling, simulation, and troubleshooting.
Introduction to Industrial Robotics
Evolution of robotics from traditional automation to collaborative robots (cobots).
Classification of industrial robots: articulated, SCARA, Cartesian, delta.
Applications across manufacturing, assembly, and service industries.
Mechatronic Design Principles
Integration of mechanical, electrical, and fluid subsystems in robotics.
Design considerations for efficiency, precision, and safety.
Troubleshooting methods for mechatronic systems.
Robotic Manipulator & End-Effector Design
- Principles of actuation and degrees of freedom (DOF).
- Kinematic modeling for motion control and precision.
- Types and applications of grippers and end-effectors.
Sensor & Transducer Integration
- Role of IR, pressure, force, and vision sensors in robotics.
- Techniques for sensor calibration and signal conditioning.
- Feedback control using multi-sensor integration.
Electro-Hydraulic Drive Systems
Components of hydraulic systems: cylinders, valves, pumps.
Integration with electrical controls for precision movement.
Use of controllers for robotic motion and force regulation.
Robotic Vision and Machine Vision Systems
Fundamentals of robotic and machine vision using cameras.
Image processing and feature extraction techniques.
Applications in object recognition, defect detection, and automation.
IIoT in Robotics
- Real-time monitoring of robotic systems via IIoT.
- Use of gateways and data communication protocols (MQTT, OPC-UA).
- Role of IIoT in predictive maintenance and smart robotics.
MATLAB-Simulink for Control Modeling and Troubleshooting
Simulation of robotic control systems in MATLAB-Simulink.
Modeling kinematics, dynamics, and control strategies.
Troubleshooting and performance optimization using simulations.
Roles
Robotics Engineer
Mechatronics Engineer
Automation Engineer
Control Systems Engineer
Industrial IoT Engineer
Robotic Vision Engineer
Hydraulics & Drive Systems Specialist
Research & Development Engineer
