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Learning Outcomes

  • Use discrete planning techniques such as Dijkstra and A* to compute optimal robot trajectories.
  • Implement complex sequences of behaviors using behavior trees.
  • Plan and implement a complex robotic controller for autonomous mobile manipulation behavior.​

Course Content

Duration: 8 hours

The first week in this course provides an introduction to path planning and presents a series of optimal algorithms for finding the shortest path on a graph that increase in complexity and efficiency. You will be introduced to various algorithms, including Bread-First Search to Dijkstra's and A*.

Duration: 7 hours

In this week, you will learn how to efficiently plan in non-grid worlds and in high-dimensional spaces.

Duration: 8 hours

This week introduces you to a new programming abstraction known as "Behavior Trees", which offers solutions to shortcomings of Finite State Machines and simple reactive controllers.

Duration: 7 hours

This week you will learn how to extend a mobile base with a robotic arm and trigger the ability to grasp objects.

Duration: 10 hours

In this last week, you will complete a final project to demonstrate your knowledge of both this course and the entire specialization. It consists of implementing a complete mobile manipulation solution.

Duration: 1 hour

If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the introductory module and anywhere else they may be found.

Notes

  • Cross-listed Courses: Courses that are offered under two or more programs. Considered equivalent when evaluating progress toward degree requirements. You may not earn credit for more than one version of a cross-listed course.
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