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 stars55.31%
- 4 stars26.91%
- 3 stars10.52%
- 2 stars3.87%
- 1 star3.37%
ROBOTICS: COMPUTATIONAL MOTION PLANNING의 최상위 리뷰
This course is supposed to be easier but somehow it also makes it difficult because implementations of the algorithms in Matlab are bit non-standard as I am used to. Altogether very challenging.
Good course, completely satisfied. Could have used a bit more material though. For example more tie-ins to the first course would not have been difficult.
Fantastic job everyone, the course was great, the content and MATLAB support is just awesome and yes hats off to the discussion forum.
Good Introduction to some of the Algorithms in Computational Planning . More of training in assignment than explanation in video
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