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.
About this Course
Skills you will gain
- 5 stars55.31%
- 4 stars26.91%
- 3 stars10.52%
- 2 stars3.87%
- 1 star3.37%
TOP REVIEWS FROM ROBOTICS: COMPUTATIONAL MOTION PLANNING
Good Introduction to some of the Algorithms in Computational Planning . More of training in assignment than explanation in video
Good course..but I wish the course was longer and the lectures and quizzes more detailed. Looking to more courses on these topics.
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.
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