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Robotics – Design and Control
Robotics – Design and Control
Download this premium online course featuring high-quality video training, step-by-step lessons, practical demonstrations, and expert instruction. With Robotics – Design and Control, you'll gain practical knowledge through structured learning, hands-on examples, and real-world applications. This comprehensive eLearning resource is ideal for students, professionals, freelancers, and lifelong learners looking to develop valuable skills and stay current with modern industry practices at their own pace.
Published 9/2026
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 32m | Size: 654.03 MB
Learn the fundamentals of robotics including kinematics, mathematical modeling and control methods
What you'll learn
Introduction to Robotics and their types and Classifications
Forward and Inverse Kinematics: The Task-Joint Space Transitions
A systematic Approach – The Denavit-Hartenberg Method (DH)
More than Position – Velocity and the Jacobian Matrix
Trajectory Planning Algorithms
Kinetics – Lagrange and Newtonian Dynamics
Robot Control Algorithms and Methodologies
Case Study – 3D Printing Robots
Requirements
Mathematics, basic engineering concepts
Description
In this robotics online course, we will know what robots are used for and how they facilitate our lives in different fields, and we will be discussing more about the different forms a robot can take based on the application it serves and needs of the user. After designing the robot and identifying its main features, we will start controlling it by first determining how to transform orders given to move the robot joints into the position of the robot's end effector, which is the main tool to be used by the robot. This transformation process is also known as forward kinematics.
Not all applications require the usage of forward kinematics; in fact, most control applications require the robot's end effector to reach a desired position, and the controller is responsible for determining the joint angles to achieve this desired motion. This process is known as inverse kinematics and will be discussed further along with different approaches to get viable joint orientations. With our competency in utilizing the forward and inverse position kinematic transformations, we started to develop a similar approach to getting robot joint and end effector velocity relations.
The Jacobian Matrix shows the relationship between the velocity of joint and task spaces. We will understand how the Jacobian matrix is calculated and why we use it in getting robot velocities, accelerations, and forces. All the previous discussions did not involve forces acting on the robot, but we are interested in robot force dynamics as we need accurate controllers that take into consideration forces acting on the robot. We will discuss energy-based dynamic analysis known as the LaGrange approach and compare it to the conventional Newtonian approach.
All robot motions can be controlled in versatile manners to provide different trajectories involving the desired positions for the end effector. Based on how smooth we want the robot motion and how fast we want to perform the motion, we will discuss different trajectory calculation algorithms and compare them.
Finally, by the end of the course, we will discuss different applied controllers used in robotics and how they aim to minimize the error between the desired and current positions of the robot joints based on sensory data acquired from the robot assembly. Furthermore, we will apply our knowledge and set of skills acquired throughout the course on a case study related to robotics in the 3D printing field.
Who this course is for
Engineering students
Homepage
https://www.udemy.com/course/robotics-online-course/
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