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This course is part of Introduction to Robotics with Webots Specialization
Instructor: Nikolaus Correll
Included with
Recommended experience
Intermediate level
Python, Linear Algebra, Basic Robotic Behaviors and Odometry
Recommended experience
Intermediate level
Python, Linear Algebra, Basic Robotic Behaviors and Odometry
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.
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In this second course of the Introduction to Robotics specialization, "Robotic Mapping and Trajectory Generation", you will learn how to perform basic inverse kinematics of (non-)holonomic systems using a feedback control approach. You will also learn how to process multi-dimensional sensor signals such as laser range scanners for mapping. Additionally, you will apply the overarching focus of mechanisms and sensors as sources of uncertainty and gain techniques to how to model and control them.
It is recommended that you complete the first course of this specialization, “Introduction to Robotics: Basic Behaviors”, before beginning this one. This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
Welcome to Week 1 of the course. You will get started by being introduced to the class of "range finder" devices, which have important applications in mapping, as well as the concept of homogeneous transforms to perform coordinate transformations.
8 videos5 readings4 assignments1 discussion prompt
In this week, you will begin to understand basic discrete map representations and their implementation.
2 videos4 readings3 assignments1 plugin
This week introduces simple ways to encode obstacles in terms of probability, the concept of "configuration space", and a simple algorithm for collision checking.
1 video3 readings2 assignments
In this week you will learn to define a robot trajectory based on a series of waypoints and implement a basic proportional controller in Webots to navigate in a 2D environment.
4 videos4 readings4 assignments
In this module you will transfer your mapping and trajectory following skills to a commercial robotic platform in a kitchen environment, introducing you to additional constraints of sensor integration on a real robotic platform.
1 video1 peer review
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.
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This course 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
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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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