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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Habilidades que obtendrás
- 5 stars55,26 %
- 4 stars26,93 %
- 3 stars10,53 %
- 2 stars3,87 %
- 1 star3,37 %
Principales reseñas sobre ROBOTICS: COMPUTATIONAL MOTION PLANNING
Good course..but I wish the course was longer and the lectures and quizzes more detailed. Looking to more courses on these topics.
A very good course in motion planning. Here are introduced some basic approach to motion and the Matlab assignments are very helpful to understand the topics of the course. Absolutely suggested.
The assignments had a lot of ambiguity. The course content was wonderful. It would have been nice if 3d computation problems were involved. Week 4 was really interesting !
The course was challenging, but fulfilling. Thank you Coursera and University of Pennsylvania for giving this wonderful experience and opportunity that I might not experience in our local community!
Acerca de Programa especializado: Robótica
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