About this course: 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.
Taught by: CJ Taylor, Professor of Computer and Information Science
School of Engineering and Applied Science
| Basic Info |
Course 2 of 6 in the
Robotics Specialization.
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| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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It will be better If content of this course could be richer and more detailed.
This brief course is the perfect introduction to motion planning methods. Although the lectures are short, they are clear and focused. This simplifies understanding of the main problems. There are also substantial programming assignments. However, the procedures are explained clearly so that the allotted time is more than sufficient for their completion. There are also suggestions on further improvements if you are interested in the topic.
Very useful introductory course to path planning
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Very good course!