Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning-based Optoelectronically Innervated Tactile Finger for
  Rigid-Soft Interactive Grasping   This paper presents a novel design of a soft tactile finger with
omni-directional adaptation using multi-channel optical fibers for rigid-soft
interactive grasping. Machine learning methods are used to train a model for
real-time prediction of force, torque, and contact using the tactile data
collected. We further integrated such fingers in a reconfigurable gripper
design with three fingers so that the finger arrangement can be actively
adjusted in real-time based on the tactile data collected during grasping,
achieving the process of rigid-soft interactive grasping. Detailed sensor
calibration and experimental results are also included to further validate the
proposed design for enhanced grasping robustness.

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The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
25
The categories of this paper are: patt-sol
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The categories of this paper are: nucl-th
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con