Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stein Variational Probabilistic Roadmaps   Efficient and reliable generation of global path plans are necessary for safe
execution and deployment of autonomous systems. In order to generate planning
graphs which adequately resolve the topology of a given environment, many
sampling-based motion planners resort to coarse, heuristically-driven
strategies which often fail to generalize to new and varied surroundings.
Further, many of these approaches are not designed to contend with
partial-observability. We posit that such uncertainty in environment geometry
can, in fact, help \textit{drive} the sampling process in generating feasible,
and probabilistically-safe planning graphs. We propose a method for
Probabilistic Roadmaps which relies on particle-based Variational Inference to
efficiently cover the posterior distribution over feasible regions in
configuration space. Our approach, Stein Variational Probabilistic Roadmap
(SV-PRM), results in sample-efficient generation of planning-graphs and large
improvements over traditional sampling approaches. We demonstrate the approach
on a variety of challenging planning problems, including real-world
probabilistic occupancy maps and high-dof manipulation problems common in
robotics.

29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin