Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: InsertionNet 2.0: Minimal Contact Multi-Step Insertion Using Multimodal
  Multiview Sensory Input   We address the problem of devising the means for a robot to rapidly and
safely learn insertion skills with just a few human interventions and without
hand-crafted rewards or demonstrations. Our InsertionNet version 2.0 provides
an improved technique to robustly cope with a wide range of use-cases featuring
different shapes, colors, initial poses, etc. In particular, we present a
regression-based method based on multimodal input from stereo perception and
force, augmented with contrastive learning for the efficient learning of
valuable features. In addition, we introduce a one-shot learning technique for
insertion, which relies on a relation network scheme to better exploit the
collected data and to support multi-step insertion tasks. Our method improves
on the results obtained with the original InsertionNet, achieving an almost
perfect score (above 97.5$\%$ on 200 trials) in 16 real-life insertion tasks
while minimizing the execution time and contact during insertion. We further
demonstrate our method's ability to tackle a real-life 3-step insertion task
and perfectly solve an unseen insertion task without learning.

23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat