Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On the Feasibility of Learning Finger-gaiting In-hand Manipulation with
  Intrinsic Sensing   Finger-gaiting manipulation is an important skill to achieve large-angle
in-hand re-orientation of objects. However, achieving these gaits with
arbitrary orientations of the hand is challenging due to the unstable nature of
the task. In this work, we use model-free reinforcement learning (RL) to learn
finger-gaiting only via precision grasps and demonstrate finger-gaiting for
rotation about an axis purely using on-board proprioceptive and tactile
feedback. To tackle the inherent instability of precision grasping, we propose
the use of initial state distributions that enable effective exploration of the
state space. Our method can learn finger-gaiting with significantly improved
sample complexity than the state-of-the-art. The policies we obtain are robust
and also transfer to novel objects. Videos can be found at
https://roamlab.github.io/learnfg/

10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex