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ROS Diploma Part 2

Name: ROS Diploma Part 2
Price: 199.99 USD
Availability: InStock

About this course

Autonomous Mobile Robot ROS Diploma Part II" is designed to take your ROS (Robot Operating System) skills to the next level, focusing on advanced topics essential for developing sophisticated autonomous mobile robots. Building on the foundational knowledge from Part I, this course delves into forward and inverse kinematics, hardware integration, sensor fusion, and real-world application of ROS on hardware platforms like Raspberry Pi.In this course, you'll learn how to calculate and implement forward and inverse kinematics for differential drive robots, allowing precise control over robot movement. You will also explore how to calculate wheel velocities from encoder data and publish odometry in ROS, a crucial step for accurate robot navigation.The course provides hands-on experience in designing and assembling a robot, connecting and configuring hardware for low-level control, and writing custom C++ nodes for tasks like goal setting and sensor data visualization. You’ll also learn how to set up and run ROS on a Raspberry Pi, enabling the deployment of your robot systems on this popular and versatile platform.Additionally, the course covers sensor fusion using the Extended Kalman Filter (EKF) for accurate robot localization, integrating multiple sensors like LIDAR and depth cameras to improve robot perception. By the end of the course, you'll have the advanced skills needed to develop and control autonomous robots in real-world environments, making this course invaluable for anyone serious about advancing in the field of robotics.

69/100

CourseAsk score

What the provider tells you: 45/45
Who stands behind it: 8/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

calculate and implement forward and inverse kinematics for differential drive robots
compute wheel velocities from encoder data
publish odometry in ROS for navigation
design and assemble a robot and configure hardware
write custom C++ nodes for goal setting and sensor data visualization
set up and run ROS on a Raspberry Pi
execute sensor fusion using the Extended Kalman Filter for localization

Course objectives

develop advanced skills for creating autonomous robots
integrate multiple sensors to enhance robot perception

Machine Learning #c# #kinematics #robotics #odometry #raspberry pi #ROS #hardware integration #mobile robots #sensor fusion #extended kalman filter #differential drive

$199.99

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