CSCA 5342: Robotic Path Planning and Task Execution
Ìý Work you complete in the non-credit experience will transfer to the for-credit experience when you upgrade and pay tuition after this course's for-credit experience launches. See How It Works for details.
- Course Type: Elective
- Specialization:ÌýIntroduction to Robotics with Webots
- Instructor:ÌýDr.ÌýNikolaus Correll, Professor of Computer Science
- Prior knowledge needed: ​Content covered in CSCA 5312:ÌýBasic Robotic Behaviors and Odometry andÌýCSCA 5332: Robotic Mapping and Trajectory Generation
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: 8Ìýhours
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:ÌýCoursesÌýthat 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.
- Page Updates:ÌýThis page is periodically updated. Course information on the Coursera platform supersedes the information on this page. Click theÌýView on CourseraÌýbuttonÌýabove for the most up-to-date information.