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Sebastian Thrun, Andy Brown, Jake Lussier, Raffaello D'Andrea, Angela Schoellig, Nicholas Roy, and Sergei Lupashin
Flying robots must traverse complex, dynamic environments. Wind, obstacles, unreliable sensor data, and other randomness all present significant challenges. In this course, you will learn the fundamentals of aerial path planning. You will begin with 2D...
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Flying robots must traverse complex, dynamic environments. Wind, obstacles, unreliable sensor data, and other randomness all present significant challenges. In this course, you will learn the fundamentals of aerial path planning. You will begin with 2D problems, optimize your solutions using waypoints, and then scale your solutions to three dimensions. You will apply these skills in your second project—autonomously navigating your drone through a dense urban environment.

What's inside

Syllabus

Solving the planning problem really comes down performing search through a state space to find a path from a start state to a goal state and here you'll get a chance to do just that!
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Your vehicle has a physical size and orientation in the world and here you'll learn how to think about position and orientation as part of your planning solution.
Graphs are really just a way of describing how your search space is connected. Here you'll learn about the tradeoffs between grids and graphs and each can be used in your planning representation.
Here you'll make the leap from two dimensions to three dimensions and discover how you can use different representations of your search space to optimize your planning solution.
In this lesson, you'll dive deep into some advanced concepts that are crucial to motion planning in the real world, where a consideration for physics and preparedness for the unexpected are crucial.
In this project, you'll get a chance to apply what you've learned about 3D motion planning from the last several lessons to plan and execute a mission in a complex urban environment!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Applies these skills in a second project, autonomously navigating your drone through a dense urban environment
Taught by Sebastian Thrun, Andy Brown, Jake Lussier, Raffaello D'Andrea, Angela Schoellig, Nicholas Roy, and Sergei Lupashin, all recognized for their work in robotics
Useful for a career in robotics engineering and relevant for professionals in the industry
Examines advanced concepts crucial to motion planning in the real world
Emphasizes applying these skills in your project to create a mission in a complex urban environment
Requires students to have a background in 2D and 3D motion planning

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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 Planning with these activities:
Review Calculus and Linear Algebra
Solidify your understanding of mathematical concepts that are essential for motion planning.
Browse courses on Calculus
Show steps
  • Review core concepts of calculus, including derivatives, integrals, and differential equations.
  • Brush up on linear algebra concepts, such as vector spaces, matrices, and transformations.
  • Apply these concepts to solve motion planning problems.
Mentor Junior Robotics Enthusiasts
Enhance your communication and leadership skills while making a positive impact by mentoring students interested in robotics.
Browse courses on Mentorship
Show steps
  • Identify opportunities to mentor at schools, clubs, or online forums.
  • Develop a structured mentoring plan to support your mentees' learning.
  • Provide guidance and feedback on their projects and assignments.
  • Encourage your mentees to participate in competitions and outreach events.
Develop a Visual Guide to Motion Planning Algorithms
Enhance your understanding and explain motion planning algorithms effectively by creating visual content.
Show steps
  • Choose one or more motion planning algorithms.
  • Design and create visual representations of the algorithms, such as diagrams, animations, or simulations.
  • Write clear and concise explanations to accompany the visuals.
  • Share your guide with others through a blog post, online forum, or video platform.
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice Aerial Path Planning
Reinforce your understanding of aerial path planning by solving practice problems and simulations.
Show steps
  • Set up a simulation environment for motion planning.
  • Generate a set of waypoints for your drone to navigate.
  • Implement a planning algorithm to compute a path between the waypoints.
  • Simulate the drone's motion along the planned path and analyze the results.
  • Iterate on your algorithm and waypoints to optimize the drone's path.
Explore Advanced Motion Planning Techniques
Expand your understanding of motion planning by exploring advanced techniques that are crucial for real-world applications.
Browse courses on Nonlinear Optimization
Show steps
  • Review the basics of nonlinear optimization.
  • Learn about sampling-based planning algorithms such as RRT and PRM.
  • Apply these algorithms to complex planning scenarios, such as navigating in constrained environments.
  • Compare the performance of different motion planning techniques.
Develop an Aerial Navigation System
Challenge yourself by designing and implementing a complete aerial navigation system for drones, putting your learning into practice.
Show steps
  • Define the requirements and specifications for the navigation system.
  • Design the architecture of the system, including sensors, actuators, and control algorithms.
  • Implement and test the system components individually.
  • Integrate the components into a complete navigation system.
  • Evaluate the system's performance in real-world environments.

Career center

Learners who complete Planning will develop knowledge and skills that may be useful to these careers:
Management Consultant
Management Consultants help businesses improve their performance. They work in a variety of industries, including healthcare, finance, and manufacturing. This course may be useful for Management Consultants who want to learn more about aerial path planning. The course will teach them how to think about position and orientation as part of their planning solution and how to optimize their solutions using waypoints.
Data Scientist
Data Scientists use data to solve problems. They work in a variety of industries, including finance, healthcare, and marketing. This course may be useful for Data Scientists who want to learn more about aerial path planning. The course will teach them how to solve the planning problem and how to optimize their solutions using waypoints.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve problems in a variety of industries, including manufacturing, healthcare, and transportation. This course may be useful for Operations Research Analysts who want to learn more about aerial path planning. The course will teach them how to use graphs to describe their search space and how to consider physics and prepare for the unexpected when planning.
Statistician
Statisticians collect, analyze, and interpret data. They work in a variety of industries, including healthcare, finance, and marketing. This course may be useful for Statisticians who want to learn more about aerial path planning. The course will teach them how to solve the planning problem and how to optimize their solutions using waypoints.
Software Engineer
Software Engineers design, build, and maintain software systems. They work in a variety of industries, including software development, web development, and mobile development. This course may be useful for Software Engineers who want to learn more about aerial path planning. The course will teach them how to think about position and orientation as part of their planning solution and how to use different representations of their search space to optimize their planning solution.
Financial Analyst
Financial Analysts provide financial advice to individuals and businesses. They work in a variety of industries, including banking, investment management, and insurance. This course may be useful for Financial Analysts who want to learn more about aerial path planning. The course will teach them how to solve the planning problem and how to optimize their solutions using waypoints.
Actuary
Actuaries use mathematical and statistical techniques to assess risk. They work in a variety of industries, including insurance, finance, and healthcare. This course may be useful for Actuaries who want to learn more about aerial path planning. The course will teach them how to consider physics and prepare for the unexpected when planning.
Mechanical Engineer
Mechanical Engineers design, build, and maintain machines. They work in a variety of industries, including manufacturing, transportation, and energy. This course may be useful for Mechanical Engineers who want to learn more about aerial path planning. The course will teach them how to use different representations of their search space to optimize their planning solution.
Psychologist
Psychologists study the human mind and behavior. They work in a variety of industries, including healthcare, education, and business. This course may be useful for Psychologists who want to learn more about aerial path planning. The course will teach them how to solve the planning problem and how to consider physics and prepare for the unexpected when planning.
Economist
Economists study the production, distribution, and consumption of goods and services. They work in a variety of industries, including government, academia, and business. This course may be useful for Economists who want to learn more about aerial path planning. The course will teach them how to think about position and orientation as part of their planning solution and how to optimize their solutions using waypoints.
Aerospace Engineer
Aerospace Engineers design, build, and test aircraft, spacecraft, and other related vehicles. They work in a variety of industries, including the military, aviation, and space exploration. This course may be useful for Aerospace Engineers who want to learn more about aerial path planning. The course will teach them how to optimize their solutions using waypoints and scale their solutions to three dimensions.
Electrical Engineer
Electrical Engineers design, build, and maintain electrical systems. They work in a variety of industries, including power generation, telecommunications, and manufacturing. This course may be useful for Electrical Engineers who want to learn more about aerial path planning. The course will teach them how to consider physics and prepare for the unexpected when planning.
Robotics Engineer
Robotics Engineers are responsible for designing, building, and maintaining robots. They work in a variety of industries, including manufacturing, healthcare, and space exploration. This course may be useful for Robotics Engineers who want to learn more about aerial path planning. The course will teach them how to solve the planning problem, think about position and orientation as part of their planning solution, and use graphs to describe how their search space is connected.
Computer Engineer
Computer Engineers design, build, and maintain computer systems. They work in a variety of industries, including software development, hardware manufacturing, and networking. This course may be useful for Computer Engineers who want to learn more about aerial path planning. The course will teach them how to use graphs to describe their search space and how to optimize their solutions using waypoints.
Sociologist
Sociologists study the structure and organization of society. They work in a variety of industries, including government, academia, and business. This course may be useful for Sociologists who want to learn more about aerial path planning. The course will teach them how to think about position and orientation as part of their planning solution and how to optimize their solutions using waypoints.

Reading list

We've selected 18 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 Planning.
Provides a comprehensive overview of planning algorithms, including a detailed discussion of search-based planning, sampling-based planning, and optimization-based planning. It valuable resource for anyone interested in learning more about the theory and practice of planning.
Provides a comprehensive overview of estimation theory, with a focus on applications to tracking and navigation. It would be a valuable resource for students and researchers in this field.
Provides a comprehensive overview of computer vision, with a focus on applications in robotics and artificial intelligence. It would be a valuable resource for students and researchers in this field.
Provides a comprehensive overview of natural language processing, with a focus on applications in robotics and artificial intelligence. It would be a valuable resource for students and researchers in this field.
Provides a comprehensive overview of control of mobile robots, including topics such as kinematics, dynamics, and control. It valuable reference for researchers and practitioners in the field of robotics.
Provides a comprehensive overview of convex optimization, with a focus on applications in machine learning and signal processing. It would be a valuable resource for students and researchers in this field.
Provides a comprehensive overview of probabilistic robotics, including a detailed discussion of motion planning. It valuable resource for anyone interested in learning more about the theory and practice of probabilistic robotics.
Provides a comprehensive overview of autonomous mobile robots, including both theoretical foundations and practical applications. It valuable resource for anyone interested in learning more about autonomous mobile robots, and it can serve as a useful reference for this course.
Provides a comprehensive overview of deep learning for computer vision. It valuable resource for anyone interested in learning more about deep learning for computer vision, and it can serve as a useful reference for this course.
Provides a comprehensive overview of robotics, vision and control. It valuable resource for anyone interested in learning more about robotics, vision and control, and it can serve as a useful reference for this course.
Provides a comprehensive overview of planning with Markov decision processes. It valuable resource for anyone interested in learning more about planning with Markov decision processes, and it can serve as a useful reference for this course.
Provides a comprehensive overview of robotics: modelling, planning and control. It valuable resource for anyone interested in learning more about robotics: modelling, planning and control, and it can serve as a useful reference for this course.
Provides a comprehensive overview of intelligent robotics and autonomous agents. It valuable resource for anyone interested in learning more about intelligent robotics and autonomous agents, and it can serve as a useful reference for this course.
Provides a comprehensive overview of control of robot manipulators. It valuable resource for anyone interested in learning more about control of robot manipulators, and it can serve as a useful reference for this course.
Provides a comprehensive overview of machine learning for robotics. It valuable resource for anyone interested in learning more about machine learning for robotics, and it can serve as a useful reference for this course.
Provides a comprehensive overview of planning with Markov decision processes. It valuable resource for anyone interested in learning more about the theory and practice of planning with Markov decision processes.
Provides a comprehensive overview of probabilistic graphical models: principles and techniques. It valuable resource for anyone interested in learning more about probabilistic graphical models: principles and techniques, and it can serve as a useful reference for this course.
Provides a comprehensive overview of reinforcement learning. It valuable resource for anyone interested in learning more about the theory and practice of reinforcement learning.

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