About the course
This course is designed to guide you through the practical aspects of robotic kinematics and motion control using the NED2 robotic arm. Through a series of hands-on laboratories, you will learn how to model, program, and control the NED2 robot using Python.
Course Structure
This course is divided into four laboratories, each focusing on a crucial aspect of robotics modeling and programming:
Laboratory 1: Direct Geometric Model (DGM)
Concepts Covered:
- Denavit-Hartenberg Modified (DHM) parameterization
- Homogeneous transformation matrices
- Direct geometric modeling
Skills Gained:
- Positioning and parameterizing the robot
- Implementing DGM using Python
- Programming basic robot movements
Laboratory 2: Direct Kinematic Model (DKM)
Concepts Covered:
- Position, velocity, and acceleration in 3D space
- Calculation of the direct kinematic model
- Jacobian matrix calculation
Skills Gained:
- Representing the NED2 arm in specific configurations
- Computing transformation matrices
- Using Python for kinematic verification
Laboratory 3: Inverse Kinematics and Singularity Detection
Concepts Covered:
- Inverse kinematics calculations
- Jacobian matrix rank determination
- Detection of singularities using determinant and condition number
Skills Gained:
- Computing joint velocities
- Analyzing singularity conditions in robotic movement
- Implementing Python-based verification techniques
Laboratory 4: Motion Planning and Control
Concepts Covered:
- Differential kinematics for trajectory generation
- Python programming of motion control
- Precision improvement in robotic movement
Skills Gained:
- Implementing a straight-line trajectory in Python
- Controlling NED2 using Python
- Graphical verification and accuracy enhancement
Knowledge Prerequisites
Before starting, ensure you are familiar with:
- Python: Basic syntax, lists, dictionaries, loops, and function calls
- Mathematics: Matrix multiplication and transformation matrices
- Robotics: Coordinate frame setup, Denavit-Hartenberg parameterization, kinematic modeling
- Kinematics: Position, velocity, and acceleration in 3D, Jacobian matrix calculations
Required Equipment
- NED2 Robotic Arm (properly set up and connected)
- NiryoStudio (for robot interfacing)
- Python Console (with pyniryo library installed)
Getting Started
Make sure your NED2 robot is correctly set up, and your Python environment is ready before proceeding to the laboratory modules. Click on a lab module to begin your journey into robotics programming!
Course content
About the Author
Philippe Depoumayrac & Pascal Dalmeida
Teacher of Industrial Systems and Robotics.
IMT Mines D'ALES
Philippe de Poumayrac de Masredon is an aggregated instructor in Mechanics. For the past 28 years, he has shared his knowledge and expertise in Mechanics and Industrial Engineering Sciences at both pre-university and post-university levels, first in the Paris region and then at Albert Einstein High School in Bagnols-sur-Cèze. Since 2017, he has been developing the Robotics course at IMT Mines Alès for engineering students and apprentices in Mechatronics. He embraces the challenge of placing practical experience at the heart of Robotics education by creating innovative educational activities centered around a 6-axis robotic arm that combines Mechatronics with Additive Manufacturing. As a result, engineering students can apply their new knowledge in Robotics and programming on a concrete platform through his activities.
Pascal DALMEIDA obtained an engineering degree in Industrial Engineering from ENI de Tarbes in 1996, followed by the aggregation in Mechanical Engineering in 1997 (now known as the aggregation in Industrial Engineering Sciences). He has been teaching since then, first in the Paris region and later in Bagnols-sur-Cèze in high school, primarily at the pre-university level. In 2017, he established and has since developed the Robotics course at IMT Mines d’Alès. He is also developing a 6-axis 3D-printed robotic arm, which allows for better alignment between the theoretical teaching of robotics and practical application on an open platform for the knowledge acquired. In 2017, he also became the Operational Director of the Campus of Trades and Qualifications in Process and Technology in Sensitive Environments. This structure bridges the various educational environments from high school to post-university and the industrial sector regarding intervention in sensitive environments in the eastern part of the Montpellier academy.
Enrolment options
Learning Path: Modeling of the Ned2
- Length: 20h
- Content Type: Lab
- Programming: Python
- Equipment: Bundle STEM
This course is designed to guide you through the practical aspects of robotic kinematics and motion control using the NED2 robotic arm. Through a series of hands-on laboratories, you will learn how to model, program, and control the NED2 robot using Python.
Course Structure
This course is divided into four laboratories, each focusing on a crucial aspect of robotics modeling and programming:
Laboratory 1: Direct Geometric Model (DGM)
Concepts Covered:
- Denavit-Hartenberg Modified (DHM) parameterization
- Homogeneous transformation matrices
- Direct geometric modeling
Skills Gained:
- Positioning and parameterizing the robot
- Implementing DGM using Python
- Programming basic robot movements
Laboratory 2: Direct Kinematic Model (DKM)
Concepts Covered:
- Position, velocity, and acceleration in 3D space
- Calculation of the direct kinematic model
- Jacobian matrix calculation
Skills Gained:
- Representing the NED2 arm in specific configurations
- Computing transformation matrices
- Using Python for kinematic verification
Laboratory 3: Inverse Kinematics and Singularity Detection
Concepts Covered:
- Inverse kinematics calculations
- Jacobian matrix rank determination
- Detection of singularities using determinant and condition number
Skills Gained:
- Computing joint velocities
- Analyzing singularity conditions in robotic movement
- Implementing Python-based verification techniques
Laboratory 4: Motion Planning and Control
Concepts Covered:
- Differential kinematics for trajectory generation
- Python programming of motion control
- Precision improvement in robotic movement
Skills Gained:
- Implementing a straight-line trajectory in Python
- Controlling NED2 using Python
- Graphical verification and accuracy enhancement
Knowledge Prerequisites
Before starting, ensure you are familiar with:
- Python: Basic syntax, lists, dictionaries, loops, and function calls
- Mathematics: Matrix multiplication and transformation matrices
- Robotics: Coordinate frame setup, Denavit-Hartenberg parameterization, kinematic modeling
- Kinematics: Position, velocity, and acceleration in 3D, Jacobian matrix calculations
Required Equipment
- NED2 Robotic Arm (properly set up and connected)
- NiryoStudio (for robot interfacing)
- Python Console (with pyniryo library installed)
Getting Started
Make sure your NED2 robot is correctly set up, and your Python environment is ready before proceeding to the laboratory modules. Click on a lab module to begin your journey into robotics programming!
- Enrolled students: 59
- Length: 20h
- Content Type: Lab
- Programming: Python
- Equipment: Bundle STEM
This course includes
Resources