Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: To Go or Not To Go? A Near Unsupervised Learning Approach For Robot
  Navigation   It is important for robots to be able to decide whether they can go through a
space or not, as they navigate through a dynamic environment. This capability
can help them avoid injury or serious damage, e.g., as a result of running into
people and obstacles, getting stuck, or falling off an edge. To this end, we
propose an unsupervised and a near-unsupervised method based on Generative
Adversarial Networks (GAN) to classify scenarios as traversable or not based on
visual data. Our method is inspired by the recent success of data-driven
approaches on computer vision problems and anomaly detection, and reduces the
need for vast amounts of negative examples at training time. Collecting
negative data indicating that a robot should not go through a space is
typically hard and dangerous because of collisions, whereas collecting positive
data can be automated and done safely based on the robot's own traveling
experience. We verify the generality and effectiveness of the proposed approach
on a test dataset collected in a previously unseen environment with a mobile
robot. Furthermore, we show that our method can be used to build costmaps (we
call as "GoNoGo" costmaps) for robot path planning using visual data only.

18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th