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Sebastian Thrun,
Julia Chernushevich,
Karim Chamaa,
and
David Silver
Learn different Path Planning and Navigation algorithms. Then, combine SLAM and Navigation into a home service robot that can autonomously transport objects in your home!
Register for this course and see more details by visiting:
OpenCourser.com/course/p2iu74/path
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What's inside
Syllabus
Learn what the lessons in Path Planning and Navigation will cover.
Learn a number of classic path planning approaches that can be applied to low-dimensional robotic systems.
Read more
Syllabus
Learn what the lessons in Path Planning and Navigation will cover.
Learn a number of classic path planning approaches that can be applied to low-dimensional robotic systems.
Read more
Learn to code the BFS and A* algorithms in C++.
Learn about sample-based and probabilistic path planning and how they can improve on the classic approach.
Program a home service robot that will autonomously map an environment and navigate to pickup and deliver objects!
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops path planning and navigation algorithms and home service robot programming skills, which are core skills for robotics and autonomous systems design
Taught by Sebastian Thrun, Julia Chernushevich, Karim Chamaa, and David Silver, who are recognized for their work in robotics, path planning, and navigation
Takes a creative approach to path planning and navigation by teaching SLAM and home service robot programming
Explores classic path planning approaches, sample-based and probabilistic path planning, and SLAM, which are standard in the robotics industry
Teaches the BFS and A* algorithms in C++, which helps learners develop strong programming skills in robotics
Explicitly requires that learners come in with extensive background knowledge
Save this course
Save Path Planning and Navigation to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Path Planning and Navigation with these
activities:
Review probability theory
Show steps
Reviewing probability theory will help you understand how to model the uncertainty and randomness inherent in autonomous navigation.
Browse courses on
Probability Theory
Show steps
-
Read the section on probability theory in your textbook or online resources.
-
Solve some practice problems on probability theory.
Review linear algebra and calculus
Show steps
Reviewing linear algebra and calculus will help you understand the mathematical foundations of autonomous navigation.
Browse courses on
Linear Algebra
Show steps
-
Read the section on linear algebra and calculus in your textbook or online resources.
-
Solve some practice problems on linear algebra and calculus.
Organize your notes, assignments, quizzes, and exams
Show steps
Keeping your materials organized will help you study more efficiently and prepare for assessments.
Show steps
-
Create a system for organizing your materials.
-
Organize your materials according to your system.
-
Review your materials regularly.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve coding problems on BFS and A* algorithms
Show steps
Coding problems will test your understanding of the concepts of BFS and A* algorithms.
Browse courses on
BFS
Show steps
-
Find a website or textbook with coding problems on BFS and A* algorithms.
-
Solve the coding problems on your own.
-
Check your solutions with the provided solutions.
Participate in a study group for path planning and navigation
Show steps
Study groups will provide you with opportunities to discuss concepts with other students and clarify your understanding.
Browse courses on
Path Planning
Show steps
-
Find a study group or create your own.
-
Discuss course materials and work on practice problems together.
-
Help each other understand concepts.
Create a visual guide to path planning algorithms
Show steps
Creating a visual guide will help you understand the different path planning algorithms and their advantages and disadvantages.
Browse courses on
Path Planning
Show steps
-
Research the different path planning algorithms.
-
Create a flowchart or diagram for each algorithm.
-
Write a brief description of each algorithm.
Follow tutorials on SLAM and Navigation
Show steps
Following tutorials will help you understand how SLAM and Navigation work and how to implement them.
Browse courses on
SLAM
Show steps
-
Find a website or textbook with tutorials on SLAM and Navigation.
-
Follow the tutorials and implement the code.
-
Test your implementation on a simulated environment.
Contribute to open-source path planning or SLAM projects
Show steps
Contributing to open-source projects will give you practical experience and help you understand the real-world applications of path planning and SLAM.
Browse courses on
Path Planning
Show steps
-
Find an open-source path planning or SLAM project that you are interested in.
-
Read the documentation and tutorials for the project.
-
Make a small contribution to the project, such as fixing a bug or adding a new feature.
Review probability theory
Show steps
Reviewing probability theory will help you understand how to model the uncertainty and randomness inherent in autonomous navigation.
Browse courses on
Probability Theory
Show steps
Show steps
Show steps
- Read the section on probability theory in your textbook or online resources.
- Solve some practice problems on probability theory.
Review linear algebra and calculus
Show steps
Reviewing linear algebra and calculus will help you understand the mathematical foundations of autonomous navigation.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Read the section on linear algebra and calculus in your textbook or online resources.
- Solve some practice problems on linear algebra and calculus.
Organize your notes, assignments, quizzes, and exams
Show steps
Keeping your materials organized will help you study more efficiently and prepare for assessments.
Show steps
Show steps
Show steps
- Create a system for organizing your materials.
- Organize your materials according to your system.
- Review your materials regularly.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve coding problems on BFS and A* algorithms
Show steps
Coding problems will test your understanding of the concepts of BFS and A* algorithms.
Browse courses on
BFS
Show steps
Show steps
Show steps
- Find a website or textbook with coding problems on BFS and A* algorithms.
- Solve the coding problems on your own.
- Check your solutions with the provided solutions.
Participate in a study group for path planning and navigation
Show steps
Study groups will provide you with opportunities to discuss concepts with other students and clarify your understanding.
Browse courses on
Path Planning
Show steps
Show steps
Show steps
- Find a study group or create your own.
- Discuss course materials and work on practice problems together.
- Help each other understand concepts.
Create a visual guide to path planning algorithms
Show steps
Creating a visual guide will help you understand the different path planning algorithms and their advantages and disadvantages.
Browse courses on
Path Planning
Show steps
Show steps
Show steps
- Research the different path planning algorithms.
- Create a flowchart or diagram for each algorithm.
- Write a brief description of each algorithm.
Follow tutorials on SLAM and Navigation
Show steps
Following tutorials will help you understand how SLAM and Navigation work and how to implement them.
Browse courses on
SLAM
Show steps
Show steps
Show steps
- Find a website or textbook with tutorials on SLAM and Navigation.
- Follow the tutorials and implement the code.
- Test your implementation on a simulated environment.
Contribute to open-source path planning or SLAM projects
Show steps
Contributing to open-source projects will give you practical experience and help you understand the real-world applications of path planning and SLAM.
Browse courses on
Path Planning
Show steps
Show steps
Show steps
- Find an open-source path planning or SLAM project that you are interested in.
- Read the documentation and tutorials for the project.
- Make a small contribution to the project, such as fixing a bug or adding a new feature.
Career center
Learners who complete Path Planning and Navigation will develop knowledge and skills
that may be useful to these careers:
Robotics Researcher
Robotics Researcher
Robotics Researchers work on the development and advancement of new robotics technologies, including path planning and navigation. This course explores several classic and state-of-the-art path planning algorithms.
Robotics Scientist
Robotics Scientist
Robotics Scientists work in many fields applying robotics to solve problems, including but not limited to manufacturing, space exploration, and healthcare. This course provides a valuable foundation in path planning and navigation for Robotics Scientists who work in any sector.
Software Engineer (Robotics)
Software Engineer (Robotics)
Software Engineers who specialize in robotics work on the software that controls the movements and other functions of robots. Path planning and navigation are critical areas of robotics software engineering. This course teaches about many related algorithms in depth.
Systems Engineer, Robotics
Systems Engineer, Robotics
Systems Engineers for robotics design and oversee the integration of robotic systems within larger systems. Path planning and navigation are critical areas of robotics system design, especially for systems that include multiple robots.
Robotics Technician
Robotics Technician
Robotics Technicians have various responsibilities, including programming, testing, and the servicing and maintenance of robots. This course helps build a foundation in path planning and navigation, which are core areas of robotics programming, testing, service, and maintenance.
Robotics Engineer
Robotics Engineer
Robotics Engineers work with many kinds of robots, including service robots. This course helps build a foundation in path planning, which is a critical capability for service robots. Its algorithms can improve a robot's awareness of its environment and objects in its environment. These are concepts that are fundamental for the development of home service robots.
Mechatronics Engineer
Mechatronics Engineer
Mechatronics Engineers apply engineering principles to the design of complex electromechanical systems, including robot. Path planning is a key part of the control system design for robots and other mechatronic systems.
Computer Vision Engineer
Computer Vision Engineer
Many robots rely on computer vision for collecting sensory data from their environment. This course is helpful for understanding the application of path planning to computer vision systems in robotics.
Automation Engineer
Automation Engineer
Designing, implementing, and managing robotic systems can be the work of Automation Engineers. Path planning algorithms are a core competency for the design and implementation of robotic systems
Aerospace Engineer
Aerospace Engineer
Aerospace Engineers design and oversee the production of aircraft and spacecraft. Path planning is a key part of designing the flight paths of these vehicles and is also used to design the robots used to build and maintain them.
Mechanical Engineer
Mechanical Engineer
Mechanical Engineers design, test, and oversee the production of mechanical systems. Many robots, including home service robots, use mechanical systems to move about and perform tasks. This course may be useful for Mechanical Engineers interested in the design of robotic systems.
Electrical Engineer
Electrical Engineer
Electrical Engineers design, test, and oversee the production of electrical systems. Many robots, including home service robots, use electrical systems to move about and perform tasks. This course may be useful for Electrical Engineers interested in the design of robotic systems.
Product Design Engineer
Product Design Engineer
Product Design Engineers design and develop new products, including robots. Path planning is a core competency for the design of robots for home use.
Quality Assurance Engineer
Quality Assurance Engineer
Quality Assurance Engineers test and oversee the production quality of many kinds of products, including robots. This course may be useful for Quality Assurance Engineers interested in the testing and production of robots.
Technical Writer
Technical Writer
Technical Writers create instruction manuals and other kinds of documentation for technical products and systems, including robots. This course may be useful for Technical Writers looking to specialize in robotics.
For more career information including salaries, visit:
OpenCourser.com/course/p2iu74/path
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Path Planning and Navigation.
Provides a comprehensive overview of probabilistic robotics, including path planning and navigation. It would be a valuable resource for those who want to learn more about the probabilistic approaches to path planning.
This textbook provides a comprehensive overview of autonomous mobile robots, including path planning. It would be a suitable replacement for the course, especially for those who are new to the field.
Save
Provides a comprehensive overview of deep learning. While it does not focus specifically on path planning, it would be a valuable resource for those who want to learn more about the deep learning techniques that can be used for path planning.
Save
Provides a comprehensive overview of computer vision. While it does not focus specifically on path planning, it would be a valuable resource for those who want to learn more about the computer vision techniques that can be used for path planning.
Provides a comprehensive overview of reinforcement learning. While it does not focus specifically on path planning, it would be a valuable resource for those who want to learn more about the reinforcement learning techniques that can be used for path planning.
Save
This textbook provides a comprehensive overview of machine learning, including reinforcement learning. It would be a valuable resource for those who want to learn more about the machine learning techniques that can be used for path planning.
Save
Covers a wide range of planning algorithms, including path planning and navigation. It would be a useful reference for those who want to learn more about the theoretical foundations of path planning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/p2iu74/path
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Time
30240 hours
Level
Advanced
Via
Udacity
Instructors
Sebastian Thrun
Julia Chernushevich
Karim Chamaa
David Silver
Language
English
Good to know
Develops path planning and navigation algorithms and home service robot programming skills, which are core skills for robotics and autonomous systems design
Taught by Sebastian Thrun, Julia Chernushevich, Karim Chamaa, and David Silver, who are recognized for their work in robotics, path planning, and navigation
Takes a creative approach to path planning and navigation by teaching SLAM and home service robot programming
Explores classic path planning approaches, sample-based and probabilistic path planning, and SLAM, which are standard in the robotics industry
Teaches the BFS and A* algorithms in C++, which helps learners develop strong programming skills in robotics
Explicitly requires that learners come in with extensive background knowledge
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