Robotic Mapping and Trajectory Generation
Master robotic mapping and control with hands-on training in inverse kinematics, sensor processing, and trajectory generation using Webots simulator.
Master robotic mapping and control with hands-on training in inverse kinematics, sensor processing, and trajectory generation using Webots simulator.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Introduction to Robotics with Webots Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Master inverse kinematics for robotic systems
Implement coordinate transforms for sensor data processing
Develop probabilistic representations for handling uncertainty
Create and optimize robot trajectory generation
Apply feedback control techniques for robot navigation
Skills you'll gain
This course includes:
3.18 Hours PreRecorded video
13 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course focuses on advanced robotics concepts including robotic mapping and trajectory generation. Students learn to implement inverse kinematics for various robotic systems, process multi-dimensional sensor data, and develop probabilistic representations for handling measurement uncertainty. The curriculum covers range finder devices, coordinate transformations, mapping techniques, and trajectory following using the Webots simulator. Through hands-on projects and practical exercises, students gain experience in implementing mapping algorithms and control systems for robotic applications.
Advanced Sensor: Range finders and Homogeneous transforms
Module 1 · 4 Hours to complete
Mapping: Basic Representations
Module 2 · 6 Hours to complete
Mapping: Probabilistic Representations and Configuration Space
Module 3 · 3 Hours to complete
Inverse Kinematics: Trajectory Following
Module 4 · 5 Hours to complete
Implementing Mapping and Trajectory Generation
Module 5 · 6 Hours to complete
Fee Structure
Instructor
Professor of Computer Science
Nikolaus Correll is a Professor of Computer Science at the University of Colorado Boulder, where he has been a faculty member since 2009. He previously served as a post-doctoral associate at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT). Nikolaus earned his Ph.D. in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL) in 2007 and holds a degree in Electrical Engineering from Eidgenössische Technische Hochschule (ETH) Zurich, obtained in 2003.His research focuses on reasoning under uncertainty in robotic manipulation and swarm robotics, areas that are critical for advancing autonomous systems. Nikolaus has received several prestigious awards, including the NASA Early Career Faculty Fellowship in 2012, the National Science Foundation's CAREER award, and the Provost Achievement Award at CU Boulder in 2016. He is recognized for his contributions to the field through keynote talks at international conferences and has received multiple best paper awards. At CU Boulder, he teaches courses such as "Basic Robotic Behaviors and Odometry," "Robotic Mapping and Trajectory Generation," and "Robotic Path Planning and Task Execution," equipping students with essential skills in robotics and automation. Through his work, Nikolaus Correll continues to shape the future of robotics research and education.
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