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”.

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Introduction to Robotics with Webots Specialization
Launch Your Career in Robotics.. Implement a Complete Mobile Manipulation Pipeline in The Webots Simulator Using Python!


Instructors: Nikolaus Correll
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What you'll learn
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
Overview
Skills you'll gain
- Mechanics
- Control Systems
- Engineering, Scientific, and Technical Instruments
- Automation
- Graph Theory
- Simulation and Simulation Software
- Data Structures
- Algorithms
- Planning
- Computer Science
- Engineering
- Robotic Process Automation
- Computer Vision
- Global Positioning Systems
- Computer Programming
- Data Mapping
- Artificial Intelligence
- Design
- Linear Algebra
Tools you'll learn
What’s included

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- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from University of Colorado Boulder

Specialization - 3 course series
What you'll learn
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.
Skills you'll gain
What you'll learn
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.
Skills you'll gain
What you'll learn
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.
Skills you'll gain
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Build toward a degree
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
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Frequently asked questions
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.
More questions
Financial aid available,