In a time where cutting-edge technology and peak efficiency are the driving forces, the realm of industrial production is witnessing a significant shift, propelled by the advent of Collaborative Robotic Systems. These advanced systems, epitomizing a seamless fusion of artificial intelligence and state-of-the-art robotics, are reshaping the contours of industrial automation and production.
Our course on Collaborative Robotic Systems is meticulously crafted to immerse you deeply into the world of these intelligent machines. As a part of this course, you will be embarked on an enlightening journey that encompasses the nuanced aspects of designing, programming, and implementing collaborative robots (cobots) in modern industrial environments.
As you navigate through this course, you will unravel a diverse array of topics that are integral to understanding and leveraging collaborative robotic systems. These include the intricate mechanics of human-robot collaboration, the principles of AI that empower these robots, and the complex algorithms that enable them to operate autonomously and safely alongside human counterparts.
You will gain hands-on experience with state-of-the-art sensors, vision systems, and gripping technologies, which are the eyes and hands of cobots in a production setting. Moreover, the course will guide you through the nuances of machine learning, including supervised, unsupervised, and reinforcement learning, which are crucial for the adaptive and predictive capabilities of collaborative robots.
In addition, this course delves into the strategic implementation of cobots in the framework of Industry 4.0, highlighting their role in enhancing flexibility, efficiency, and customization in production processes. We will explore cutting-edge case studies and real-world applications of cobots across various sectors, from automotive to electronics, offering a panoramic view of their transformative impact.
This course not only equips you with technical knowledge but also encourages you to contemplate the ethical and safety considerations inherent in deploying robots in human-centric environments. You will learn about the standards and best practices for ensuring safe and harmonious human-robot interactions.
This course unit covers 100 hours, from which 14 hours lectures, 28 hours lab work, and 58 hours individual study and work.
Specific Objectives / Learning Outcomes
Alignment to Social and Economic Expectations
Unit 1: Foundations of Collaborative Robots: Concepts and Characteristics (2 hours)
- Lecture/Course Objectives and List of References
- Introduction to Basic Concepts of Collaborative Robots
- Specific Characteristics in the Construction and Use of Collaborative Robots
- Overview of the Evolution and Advancements in Collaborative Robotics
- Practical Case Studies Highlighting the Unique Features of Collaborative Robots
Unit 2: Mathematical Modelling of Collaborative Robots (2 hours)
- Introduction to Mathematical Modelling in Robotics
- Efficient Study Methods for Kinematics and Workspace Modelling of Collaborative Robots
- The Role and Benefits of the Supplementary Axis (Seventh Axis) in Robotic Design
- Case Studies and Examples of Mathematical Modelling in Collaborative Robotics
- Hands-on Exercises in Kinematic Analysis and Workspace Modelling
Unit 3: Intelligent Algorithms for Visual Object and Gesture Recognition (2 hours)
- Fundamentals of Intelligent Algorithms in Robotics
- Techniques for Visual Object Recognition in Collaborative Robots
- Gesture Recognition Technologies and Their Applications
- Practical Implementation of Visual and Gesture Recognition Algorithms
- Interactive Demos and Exercises in Object and Gesture Recognition
Unit 4: Interactive Control Platforms for Collaborative Robots (2 hours)
- Overview of Interactive Control Platforms in Robotics
- Utilization of Smart/Advanced Tools and Equipment in Collaborative Robotics
- Case Studies on Effective Interactive Control Systems
- Practical Exercises Using Different Interactive Control Platforms
- Evaluation of Advanced Control Technologies in Robotics
Unit 5: AI Algorithms in Collaborative Robots: Roles and Implementation (2 hours)
- Introduction to Artificial Intelligence Algorithms in Robotics
- Role and Functionality of AI in Collaborative Robots
- Step-by-Step Implementation of AI Algorithms in Robotic Applications
- Real-World Applications and Case Studies
- Hands-on Experience with AI-Driven Collaborative Robots
Unit 6: ROS Operating System in Collaborative Robotics (2 hours)
- Introduction to ROS (Robot Operating System) in Robotics
- Implementing Different Collaborative Robots Using ROS
- Advantages and Challenges of ROS in Collaborative Robotics
- Practical Demonstrations of ROS in Action with Collaborative Robots
- Exercises and Case Studies Focused on ROS Applications
Unit 7: Non-Conventional Algorithms for Human-Robot Interaction (2 hours)
- Exploration of Non-Conventional Algorithms in Robotics
- Innovative Approaches to Intelligent Human-Robot Interaction
- Use Cases and Applications of Advanced Interaction Algorithms
- Hands-on Implementation of Non-Conventional Interaction Techniques
- Practical Demonstrations and Interactive Sessions
Each unit is crafted to provide a comprehensive understanding of collaborative robots, starting from basic concepts to advanced applications, ensuring that students gain both theoretical knowledge and practical skills.
Unit 1: ABB-YuMi Collaborative Robot: Operation and Programming Basics (2 hours)
- Introduction to the ABB-YuMi collaborative robot
- Basics of operation and programming of ABB-YuMi
- Running example programs on the ABB-YuMi
- Hands-on practice with ABB-YuMi operation and programming
Unit 2: KUKA iiwa LBR: Operation and Programming Fundamentals (2 hours)
- Overview of the KUKA iiwa LBR collaborative robot
- Essential operation and programming techniques for KUKA iiwa LBR
- Executing sample programs on KUKA iiwa LBR
- Practical exercises in operating and programming the KUKA iiwa LBR
Unit 3: UR5e Collaborative Robot: Operation and Programming (2 hours)
- Introduction to the UR5e collaborative robot
- Basic operation and programming skills for UR5e
- Running UR5e example applications
- Hands-on activities with the UR5e robot
Unit 4: Operating and Programming the MAiRA Collaborative Robot (2 hours)
- Essentials of MAiRA collaborative robot operation
- Programming basics for the MAiRA robot
- Practical demonstrations with the MAiRA robot
- Interactive exercises in programming and operating MAiRA
Unit 5: Mathematical Modelling and Workspace Analysis of Robotic Arms (2 hours)
- Parametric mathematical modelling of 6 and 7-axis robotic arms
- Workspace analysis and trajectory generation techniques
- Case studies and examples of mathematical modelling
- Hands-on exercises in workspace analysis and trajectory planning
Unit 6: Interactive Application Development with ABB-YuMi (2 hours)
- Framework for developing interactive applications with ABB-YuMi
- Step-by-step guide to creating an ABB-YuMi interactive application
- Practical session on ABB-YuMi application development
- Group project on creating a custom interactive application
Unit 7: Interactive Application Development with UR5e (2 hours)
- Overview of developing interactive applications using UR5e
- Process of programming and implementing UR5e interactive applications
- Hands-on project to develop an interactive application with UR5e
- Collaborative workshop and discussion
Unit 8: Advanced Interaction with KUKA iiwa LBR: Voice, Visual, and Gesture Recognition (2 hours)
- Integrating voice, visual, and gesture recognition with KUKA iiwa LBR
- Development process for advanced interactive applications
- Practical exercises in advanced interaction techniques
- Group activity to implement a multifaceted interactive application
Unit 9: Haptic Feedback Control with KUKA iiwa LBR: Master-Slave Concept (2 hours)
- Fundamentals of haptic feedback control
- Implementing the master-slave concept on KUKA iiwa LBR
- Case study and practical demonstrations
- Hands-on practice in developing haptic feedback control systems
Unit 10: AI-Driven Event Detection in Collaborative Robotics Programming (2 hours)
- Utilizing AI tools for event detection in collaborative robot programming
- Techniques for programming collaborative robots in active environments
- Practical exercises with AI tools in robotic programming
- Collaborative project on AI integration in robotic event detection
Unit 11: Developing Cognitive Applications with MAiRA (2 hours)
- Cognitive applications in collaborative robotics
- Step-by-step guide to programming cognitive functions in MAiRA
- Interactive session on cognitive application development
- Group project on MAiRA-based cognitive applications
Unit 12: Adaptive Control in Dynamic Environments with Collaborative Robots (2 hours)
- Techniques for adaptive control in dynamic environments
- Case studies on adaptive control with collaborative robots
- Practical exercises in dynamic environment adaptation
- Collaborative workshop on adaptive control strategies
Unit 13: Interactive Applications with Multiple Collaborative Robots (2 hours)
- Framework for developing applications with multiple collaborative robots
- Techniques for synchronizing and coordinating multiple robots
- Hands-on group activity to develop a multi-robot interactive application
- Discussion and analysis of multi-robot system dynamics
Each unit is tailored to provide students with a comprehensive understanding and practical skills in specific aspects of collaborative robots, from basic operation to advanced application development.
- Collaborative Robots: Our lab is equipped with a range of cobots to provide diverse learning experiences:
- ABB-YuMi: A dual-arm cobot known for its precision and safety in close human interaction.
- KUKA iiwa LBR: Stands out for its sensitive touch and flexible task programming.
- UR5e: Renowned for its versatility and ease of integration in various applications.
- MAiRA: Known for its cognitive capabilities and advanced interaction features.
- Supplementary Equipment: Each cobot workstation will be equipped with necessary peripherals such as grippers, sensors, and tools for specific tasks and applications.
- Vendor-specific Software: Such as ABB’s RobotStudio, KUKA’s KUKA|prc, and UR’s Polyscope, providing interfaces specific to each robot model.
- MATLAB and SolidWorks: For mathematical modelling and integration of custom robot designs into simulation.