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.
- 5 stars55.14%
- 4 stars26.97%
- 3 stars10.58%
- 2 stars3.89%
- 1 star3.39%
来自ROBOTICS: COMPUTATIONAL MOTION PLANNING的热门评论
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 !
Good Introduction to some of the Algorithms in Computational Planning . More of training in assignment than explanation in video
Everything was so relevant and finely explained, but It clearly wasn't a beginner's course, it's more an Intermediate Course.
A good course to get started with robotic motion planning. It starts from shortest path algorithm, configuration space to probabilistic roadmap and potential filed.