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Roland Siegwart,
Marco Hutter,
Margarita Chli,
Davide Scaramuzza,
Martin Rufli,
and
Nicholas Lawrance
Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily environment. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. The main emphasis is put on mobile robot locomotion and kinematics, environment perception, probabilistic map based localization and mapping, and motion planning. The lectures and exercises of this course introduce several types of robots such as wheeled robots, legged robots and drones.
Read more
Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily environment. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. The main emphasis is put on mobile robot locomotion and kinematics, environment perception, probabilistic map based localization and mapping, and motion planning. The lectures and exercises of this course introduce several types of robots such as wheeled robots, legged robots and drones.
Read more
Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily environment. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. The main emphasis is put on mobile robot locomotion and kinematics, environment perception, probabilistic map based localization and mapping, and motion planning. The lectures and exercises of this course introduce several types of robots such as wheeled robots, legged robots and drones.
This lecture closely follows the textbook Introduction to Autonomous Mobile Robots by Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, second edition 2011.
Register for this course and see more details by visiting:
OpenCourser.com/course/gilrth/autonomous
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What's inside
Learning objectives
- Be able to describe the basic concepts and algorithms required for mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning
- Be able to apply these concepts for the design and implementation of autonomous mobile robots acting in complex environment
- Be able to describe the basic concepts and algorithms required for mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning
- Be able to apply these concepts for the design and implementation of autonomous mobile robots acting in complex environment
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds a strong foundation for beginners wanting to create mobile robots that act autonomously in complex environments
Applies concepts for the design and implementation of autonomous mobile robots acting in complex environments
Taught by five instructors who are well-known for their work in robotics
Closely follows the textbook 'Introduction to Autonomous Mobile Robots' by Roland Siegwart and others
Describes the basic concepts and algorithms required for mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning
Save this course
Save Autonomous Mobile Robots to your list so you can find it easily later:
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Reviews summary
Autonomous mobile robots course review
According to students, Autonomous Mobile Robots provides engaging assignments and concepts, however, access to course videos in archived materials may be an issue. Students largely agree that the topics covered in this course align with the future of mobile robotics and career paths. Other students note the difficulty of the course, so enrollees should be ready to put in some serious effort.
Concepts are engaging and will prepare you for a future in the field.
This course is difficult.
There are issues accessing videos.
"I can't get access to the videos on edx archibed course on AUTONOMOUS MOBILE ROBOTS."
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 Autonomous Mobile Robots with these
activities:
Organize a study group
Show steps
Enhance understanding and recall by discussing course concepts and working through problems collaboratively.
Show steps
-
Recruit a group of classmates who are motivated and committed to active participation.
-
Establish a regular meeting schedule and create a shared workspace for notes and resources.
-
Take turns presenting on different topics, leading discussions, and solving problems.
Explore open-source mobile robot software frameworks
Show steps
Gain practical experience by working with open-source frameworks used in mobile robotics.
Browse courses on
ROS
Show steps
-
Identify and select relevant open-source software frameworks for mobile robot development.
-
Follow tutorials and documentation to set up and use these frameworks for robot simulation and control.
Review core textbook
Show steps
Reinforce understanding of course concepts and deepen knowledge of autonomous mobile robots.
View
Introduction to Autonomous Mobile Robots,...
on Amazon
Show steps
-
Read the designated chapters and sections that align with the course lessons.
-
Take notes and summarize key points, highlighting concepts and algorithms related to mobile robot locomotion, environment perception, probabilistic map-based localization and mapping, and motion planning.
-
Identify any areas of difficulty or confusion and seek clarification through discussion forums, online resources, or by reaching out to the instructors.
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice robot motion planning algorithms
Show steps
Develop proficiency in motion planning algorithms for autonomous navigation.
Browse courses on
Motion Planning
Show steps
-
Study different motion planning algorithms such as A*, RRT, and D*.
-
Implement these algorithms in a simulated environment or on a physical robot.
-
Test and compare the performance of the algorithms in various scenarios.
Solve mapping and localization problems
Show steps
Develop skills in probabilistic map-based localization and mapping through problem-solving.
Show steps
-
Obtain datasets or create simulated environments for mobile robot navigation.
-
Implement algorithms for robot localization using sensor data and probabilistic models.
-
Design and test mapping algorithms to build and update maps of the robot's environment.
Design a custom robot
Show steps
Practice applying concepts of mobile robot locomotion and kinematics by designing a custom robot.
Browse courses on
Robot Design
Show steps
-
Research different robot designs, types of sensors, and locomotion systems.
-
Sketch and model your custom robot, considering factors such as mobility, perception capabilities, and computational requirements.
-
Create a detailed technical design document outlining the robot's specifications, components, and functionality.
Organize a study group
Show steps
Enhance understanding and recall by discussing course concepts and working through problems collaboratively.
Show steps
Show steps
Show steps
- Recruit a group of classmates who are motivated and committed to active participation.
- Establish a regular meeting schedule and create a shared workspace for notes and resources.
- Take turns presenting on different topics, leading discussions, and solving problems.
Explore open-source mobile robot software frameworks
Show steps
Gain practical experience by working with open-source frameworks used in mobile robotics.
Browse courses on
ROS
Show steps
Show steps
Show steps
- Identify and select relevant open-source software frameworks for mobile robot development.
- Follow tutorials and documentation to set up and use these frameworks for robot simulation and control.
Review core textbook
Show steps
Reinforce understanding of course concepts and deepen knowledge of autonomous mobile robots.
View
Introduction to Autonomous Mobile Robots,...
on Amazon
Show steps
Show steps
Show steps
- Read the designated chapters and sections that align with the course lessons.
- Take notes and summarize key points, highlighting concepts and algorithms related to mobile robot locomotion, environment perception, probabilistic map-based localization and mapping, and motion planning.
- Identify any areas of difficulty or confusion and seek clarification through discussion forums, online resources, or by reaching out to the instructors.
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice robot motion planning algorithms
Show steps
Develop proficiency in motion planning algorithms for autonomous navigation.
Browse courses on
Motion Planning
Show steps
Show steps
Show steps
- Study different motion planning algorithms such as A*, RRT, and D*.
- Implement these algorithms in a simulated environment or on a physical robot.
- Test and compare the performance of the algorithms in various scenarios.
Solve mapping and localization problems
Show steps
Develop skills in probabilistic map-based localization and mapping through problem-solving.
Show steps
Show steps
Show steps
- Obtain datasets or create simulated environments for mobile robot navigation.
- Implement algorithms for robot localization using sensor data and probabilistic models.
- Design and test mapping algorithms to build and update maps of the robot's environment.
Design a custom robot
Show steps
Practice applying concepts of mobile robot locomotion and kinematics by designing a custom robot.
Browse courses on
Robot Design
Show steps
Show steps
Show steps
- Research different robot designs, types of sensors, and locomotion systems.
- Sketch and model your custom robot, considering factors such as mobility, perception capabilities, and computational requirements.
- Create a detailed technical design document outlining the robot's specifications, components, and functionality.
Career center
Learners who complete Autonomous Mobile Robots will develop knowledge and skills
that may be useful to these careers:
Technical Writer
Technical Writer
Technical Writers create documentation for technical products and services. This documentation can include user manuals, white papers, and training materials. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Project Manager
Project Manager
Project Managers plan, execute, and track projects. They work with a team of people to achieve a common goal. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Systems Engineer
Systems Engineer
Systems Engineers design, develop, and test complex systems. These systems are typically composed of multiple components, such as hardware, software, and people. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Mechanical Engineer
Mechanical Engineer
Mechanical Engineers design, develop, and test mechanical systems. These systems are used to move and control a wide variety of devices, such as robots, drones, and autonomous vehicles. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Electrical Engineer
Electrical Engineer
Electrical Engineers design, develop, and test electrical systems. These systems are used to power and control a wide variety of devices, such as robots, drones, and autonomous vehicles. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Software Engineer
Software Engineer
Software Engineers design, develop, and test software applications. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Data Scientist
Data Scientist
Data Scientists collect, analyze, and interpret data. This information is used to make informed decisions. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and test machine learning models. These models are used to give computers the ability to learn from data. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design, develop, and test computer vision systems. These systems are used to give computers the ability to see and understand the world around them. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Control Systems Engineer
Control Systems Engineer
Control Systems Engineers design, develop, and test control systems. These systems are used to control a wide variety of devices, such as robots, drones, and autonomous vehicles. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Mechatronics Engineer
Mechatronics Engineer
Mechatronics Engineers design, develop, and test mechatronic systems. These systems combine mechanical, electrical, and computer engineering. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Drone Engineer
Drone Engineer
Drone Engineers design, develop, and test drones. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Autonomous Vehicle Engineer
Autonomous Vehicle Engineer
Autonomous Vehicle Engineers design, develop, and test autonomous vehicles. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning.
Robotics Software Engineer
Robotics Software Engineer
Robotics Software Engineers design, develop, and maintain software for robots. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning. These will help you to build a foundation for developing self-driving vehicle navigation software.
Robotics Engineer
Robotics Engineer
As a Robotics Engineer, you will be responsible for designing, building, and testing robots. This course may be useful in helping you to develop the skills and knowledge you need to be successful in this role. The course covers topics such as mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning. These are all essential concepts for Robotics Engineers to understand.
For more career information including salaries, visit:
OpenCourser.com/course/gilrth/autonomous
Reading list
We've selected eight 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
Autonomous Mobile Robots.
The textbook used for the course; provides a comprehensive overview of the field.
Provides in-depth coverage of probabilistic robotics that is foundational to the field of autonomous mobile robots.
Save
Covers motion planning algorithms in depth, which is essential for autonomous mobile robots to navigate complex environments.
Save
An open-access journal that publishes high-quality research in robotics, providing up-to-date information on the latest developments in the field.
Save
Provides a comprehensive overview of computer vision techniques used in environment perception for autonomous robots.
Provides a comprehensive overview of autonomous robot vehicles, including design, navigation, and control.
Provides practical examples and exercises using MATLAB® for implementing robotics algorithms, including those used in autonomous mobile robots.
Save
Provides a strong foundation in robotics fundamentals, including kinematics, dynamics, and control, which are essential for understanding autonomous mobile robots.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/gilrth/autonomous
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Effort
4 to 8 hours per week for 15 weeks
Level
Intermediate
Via
edX
Institution
ETH Zurich
Instructors
Roland Siegwart
Marco Hutter
Margarita Chli
Davide Scaramuzza
Martin Rufli
Nicholas Lawrance
Language
English
Transcript
English
Good to know
Builds a strong foundation for beginners wanting to create mobile robots that act autonomously in complex environments
Applies concepts for the design and implementation of autonomous mobile robots acting in complex environments
Taught by five instructors who are well-known for their work in robotics
Closely follows the textbook 'Introduction to Autonomous Mobile Robots' by Roland Siegwart and others
Describes the basic concepts and algorithms required for mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning
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