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Launch Your Career in Robotics. . Implement a Complete Mobile Manipulation Pipeline in The Webots Simulator Using Python!
Instructors: Nikolaus Correll
2,416 already enrolled
Included with
(26 reviews)
Recommended experience
Beginner level
Linear Algebra, Python
(26 reviews)
Recommended experience
Beginner level
Linear Algebra, Python
Forward and inverse kinematics of holonomic and non-holonomic mechanisms
Discrete planning of trajectories and behaviors for robots
Understand the sources of uncertainty in robotic sensing and actuation
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The overarching learning goal of this specialization in robotics is to create an appreciation for the tight interplay between mechanism, sensor, and control in the design of intelligent systems. By the end of this specialization, you will be able to (1) formally describe the forward and inverse kinematics of a mechanism, (2) discretize the robot’s state from algorithmic reasoning, and (3) understand the sources of uncertainty in sensing or actuation and describe them mathematically. During this specialization, you will gain hands-on experience in Python and use the realistic robotic system simulator, “Webots”.
Applied Learning Project
Learners will utilize the robotics simulator Webots to build their own simulations while learning. In this specialization, you will get "hands-on" with step-by-step instructions to implement a certain device or algorithm in Webots, then encourage you to explore this solution, extend or change it, and finally ask a question that ensures you have understood the concept. Hands-on activities lead to graded peer evaluations that will require reproducing previously learned concepts in the form of a well-defined behavior.
Emphasis on the first course of this specialization is on learning Webots and reading up on key concepts to build a foundation. Activities then gradually shift to include more hands-on activities in the second course of this specialization and culminate into a large project requiring the implementation of a complete mobile manipulation solution.
Model mechanisms, sensors and actuators in a physics-based online simulator.
Understand basic reactive and discrete controllers.
Perform forward kinematics computations for simple (non-)Holonomic mechanisms.
Use basic feedback control techniques for inverse kinematics of (non-)Holonomic mechanisms.
Apply coordinate transforms to multi-dimensional sensor signals.
Understand basic probabilistic representations to deal with uncertainty from measurement noise.
Use discrete planning techniques such as Dijkstra and A* to compute optimal robot trajectories.
Implement complex sequences of behaviors using behavior trees.
Plan and implement a complex robotic controller for autonomous mobile manipulation behavior.
CU Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
This Specialization is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
This Specialization is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
University of Colorado Boulder
Degree · 24 months
University of Colorado Boulder
Degree · 2 years
University of Colorado Boulder
Degree · 24 months
University of Colorado Boulder
Degree · 2 years
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
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You should expect to complete the specialization in 15 weeks.
The specialization heavily relies on Python programming. Basic knowledge in linear algebra and probability will be helpful.
Yes, the courses build upon each other and it is recommended to take them in the suggested order.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
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