Welcome back everyone to week 8. I'm still Michael Gurner and we're in for the second
lecture actually this time talking about the actual probabilistic planners. Last time we
introduced all the basic requirements, all the basic terminology, we need to understand
what's going on there. We talked about feasibility of trajectories, about geometry representations
and especially about collision checking. We talked about the difference between Cartesian
state space on the one hand and joint space or configuration space on the other hand.
We already talked about basic planner or classic planner approaches that people came up with
a long time ago. We noticed that all of these have shortcomings and of course no method
I'm going to introduce here is going to be perfect. They have other shortcomings. Now
let's have a look at the field of probabilistic planners especially we'll talk about three
prototypical planners that is PRM, RRT and EST, three pretty prominent acronyms in that
field. Afterwards we will also talk about a bit about how to introduce optimal planning
in this context. And then next week you will get the additional lecture on task and manipulation
planning that builds on top of all of the introduced concepts.