Weipeng Dang

dblp:203/4842 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › tactile sensing › contact sensing
contact localization
0.312017
Accurate contact localization and indentation depth prediction with an optics-based tactile sensor · ICRA 2017
Robotics › Robot manipulation
tactile sensing
0.312017
Accurate contact localization and indentation depth prediction with an optics-based tactile sensor · ICRA 2017

Methods — techniques the papers use, named apart from their topics

light intensity measurement · 0.3
YearPublicationVenuePosition
2017 Accurate contact localization and indentation depth prediction with an optics-based tactile sensor
abstract
Traditional methods to achieve high localization accuracy with tactile sensors usually use a matrix of miniaturized individual sensors distributed on the area of interest. This approach usually comes at a price of increased complexity in fabrication and circuitry, and can be hard to adapt for non planar geometries. We propose to use low cost optic components mounted on the edges of the sensing area to measure how light traveling through an elastomer is affected by touch. Multiple light emitters and receivers provide us with a rich signal set that contains the necessary information to pinpoint both the location and depth of an indentation with high accuracy. We demonstrate sub-millimeter accuracy on location and depth on a 20mm by 20mm active sensing area. Our sensor provides high depth sensitivity as a result of two different modalities in how light is guided through our elastomer. This method results in a low cost, easy to manufacture sensor. We believe this approach can be adapted to cover non-planar surfaces, simplifying future integration in robot skin applications.
Pedro Piacenza, Weipeng Dang, Emily Hannigan, Jeremy Espinal, Ikram Hussain, Ioannis Kymissis, Matei T. Ciocarlie
ICRA2