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%
Principais avaliações do ROBOTICS: COMPUTATIONAL MOTION PLANNING
I like this course because they are covering really complicated topics in very less material. And the assignments are amazing. They are worth the learning effect they create.
The course material and videos are very good. Small bugs in the exercise can be a bit of headache. Luckily, digging the community forum there is always a high chance to solve your issue.
The last assignment had no hints. Also was extremely fragile with the grading. Step size cannot be fixed to a value, because otherwise the route count is wrong.
It's nice! I particularly like the programming homework. However, the course is pretty much beginner-level, and the course is too short (for only 4 weeks).
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