Abstract
Motivated by the impact of superresolution methods for imaging, we
undertake a detailed and systematic analysis of localization acuity for a
biomimetic fingertip and a flat region of tactile skin. We identify
three key factors underlying superresolution that enable the perceptual
acuity to surpass the sensor resolution: 1) the sensor is constructed
with multiple overlapping, broad but sensitive receptive fields; 2) the
tactile perception method interpolates between receptors (taxels) to
attain subtaxel acuity; and 3) active perception ensures robustness to
unknown initial contact location. All factors follow from active
Bayesian perception applied to biomimetic tactile sensors with an
elastomeric covering that spreads the contact over multiple taxels. In
consequence, we attain extreme superresolution with a 35-fold
improvement of localization acuity (0.12 mm) over sensor resolution (4
mm). We envisage that these principles will enable cheap high-acuity
tactile sensors that are highly customizable to suit their robotic use.
Practical applications encompass any scenario where an end-effector must
be placed accurately via the sense of touch.
Original language | English |
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Pages (from-to) | 605-618 |
Number of pages | 14 |
Journal | IEEE Transactions on Robotics |
Volume | 31 |
Issue number | 3 |
Early online date | 2 Apr 2015 |
DOIs | |
Publication status | Published - 3 Jun 2015 |
Keywords
- Bayes methods
- biomimetics
- image resolution
- skin
- tactile sensors
- force and tactile sensing
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Professor Nathan F Lepora
- School of Engineering Mathematics and Technology - Professor of Robotics and AI
Person: Academic , Member