• Anytime
    Application Deadline
  • 1 month
    Duration
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Overview

The programme

Robotic systems typically include three components: a mechanism which is capable of exerting forces and torques on the environment, a perception system for sensing the world and a decision and control system which modulates the robot's behavior to achieve the desired ends.  In this course we will consider the problem of how a robot decides what to do to achieve its goals. This problem is often referred to as Motion Planning and it has been formulated in various ways to model different situations.  You will learn some of the most common approaches to addressing this problem including graph-based methods, randomized planners and artificial potential fields.  

Throughout the Robotics - Computational Motion Planning offered by Coursera in partnership with University of Pennsylvania, we will discuss the aspects of the problem that make planning challenging.

Detailed Programme Facts

Programme Structure

Courses include:

  • Introduction and Graph-based Plan Methods
  • Configuration Space
  • Sampling-based Planning Methods
  • Artificial Potential Field Methods

English Language Requirements

This programme may require students to demonstrate proficiency in English.

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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