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 course, we will discuss the aspects of the problem that make planning challenging.
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- 5 stars55,27 %
- 4 stars26,89 %
- 3 stars10,55 %
- 2 stars3,88 %
- 1 star3,38 %
Meilleurs avis pour ROBOTICS: COMPUTATIONAL MOTION PLANNING
Great Introductory Course. It is a bit short on course content, but teaches you enough to be able to learn from other sources such as research papers, etc.
Good Introduction to some of the Algorithms in Computational Planning . More of training in assignment than explanation in video
A beautiful course for robotics beginners. Videos are mostly conceptual yet superficial while programming assignments give a feel for the technicalities involved.
I would say beginners will struggle with the contents of this course because it is heavily conceptual and requires you to read other resources to understand fully, In all, it was a splendid course.
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