Probabilistic inference methods in robotics-filling the gap between high-level reasoning and low-level motion control

author: Marc Toussaint, TU Berlin

Categories

Top: Computer Science: Robotics
Top: Computer Science: Machine Learning: Statistical Learning
Top: Computer Science: Machine Learning: Bayesian Learning

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*Slides*
0:00	Probabilistic inference methods in robotics
0:18	Robotics - 1
0:57	Robotics - 2
1:30	Robotics - 3
2:20	Robotics - 4
3:16	Outline - 1
3:47	Background: Probabilistic Inference & Planning
5:20	Planning as Likelihood Maximization - 1
6:05	Planning as Likelihood Maximization - 2
6:49	Planning as Likelihood Maximization - 3
7:35	Planning as Likelihood Maximization - 4
8:35	Extensions to POMDPs - 1
9:04	Extensions to POMDPs - 2
9:26	Outline - 2
10:18	Bayesian view on classical control
11:45	Bayesian view - 1
12:47	Bayesian view - 2
13:33	Same also works for dynamic control...
13:55	Bayesian view - 3
14:05	Motion control - 1
14:22	Motion control - 2
14:40	Example 1 - 1
15:04	Example 1 - 2
15:18	Example 1 - 3
16:23	Example 1 - 4
16:25	Example 1 - 5
16:47	Example 1 - 6
17:38	Example 2 - 1
17:44	Example 2 - 2
18:16	Example 2 - 3
18:54	Example 2 - 4
19:17	Example 2 - 5
21:59	Example 2 - 6
24:10	Summary - 1
24:37	Summary - 2
25:53	ML approaches for all subproblems?
27:00	Thanks
27:14	- Questions

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