Modern Robotics, Course 4: Robot Motion Planning and Control
This course is part of Modern Robotics: Mechanics, Planning, and Control.
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 Modern Robotics: Mechanics, Planning, and Control 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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English
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What you'll learn
Master motion planning for obstacle avoidance
Implement graph search and sampling-based planners
Design feedback control systems for robots
Develop hybrid motion-force control strategies
Create complete robot motion solutions
Skills you'll gain
This course includes:
1.77 Hours PreRecorded video
26 quizzes, 1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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Get a Completion Certificate
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There are 4 modules in this course
This comprehensive course covers robot motion planning and control, focusing on both theoretical foundations and practical implementations. Students learn various motion planning techniques including graph search, sampling-based methods, and potential fields, along with control strategies for motion tracking, force control, and hybrid systems. The curriculum utilizes the V-REP simulator for hands-on practice.
Chapter 10: Motion Planning (Part 1 of 2)
Module 1 · 9 Hours to complete
Chapter 10: Motion Planning (Part 2 of 2)
Module 2 · 9 Hours to complete
Chapter 11: Robot Control (Part 1 of 2)
Module 3 · 7 Hours to complete
Chapter 11: Robot Control (Part 2 of 2)
Module 4 · 5 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Modern Robotics: Mechanics, Planning, and Control
Instructor
Leader in Robotics Research and Education at Northwestern University's Mechanical Engineering Department.
Kevin Lynch is the Professor and Chair of the Mechanical Engineering Department at Northwestern University. He is also affiliated with the Neuroscience and Robotics Lab and the Northwestern Institute on Complex Systems. His research primarily focuses on dynamics, motion planning, and control for robot manipulation and locomotion, as well as self-organizing multi-agent systems and functional electrical stimulation for restoring human function.
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Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.