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Sensory prediction on a whiskered robot: a tactile analogy to “optical flow”

Overview of attention for article published in Frontiers in Neurorobotics, January 2012
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Title
Sensory prediction on a whiskered robot: a tactile analogy to “optical flow”
Published in
Frontiers in Neurorobotics, January 2012
DOI 10.3389/fnbot.2012.00009
Pubmed ID
Authors

Christopher L. Schroeder, Mitra J. Z. Hartmann

Abstract

When an animal moves an array of sensors (e.g., the hand, the eye) through the environment, spatial and temporal gradients of sensory data are related by the velocity of the moving sensory array. In vision, the relationship between spatial and temporal brightness gradients is quantified in the "optical flow" equation. In the present work, we suggest an analog to optical flow for the rodent vibrissal (whisker) array, in which the perceptual intensity that "flows" over the array is bending moment. Changes in bending moment are directly related to radial object distance, defined as the distance between the base of a whisker and the point of contact with the object. Using both simulations and a 1×5 array (row) of artificial whiskers, we demonstrate that local object curvature can be estimated based on differences in radial distance across the array. We then develop two algorithms, both based on tactile flow, to predict the future contact points that will be obtained as the whisker array translates along the object. The translation of the robotic whisker array represents the rat's head velocity. The first algorithm uses a calculation of the local object slope, while the second uses a calculation of the local object curvature. Both algorithms successfully predict future contact points for simple surfaces. The algorithm based on curvature was found to more accurately predict future contact points as surfaces became more irregular. We quantify the inter-related effects of whisker spacing and the object's spatial frequencies, and examine the issues that arise in the presence of real-world noise, friction, and slip.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
United States 1 3%
Australia 1 3%
Unknown 36 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 18%
Professor 6 15%
Student > Master 6 15%
Student > Ph. D. Student 6 15%
Student > Bachelor 3 8%
Other 6 15%
Unknown 5 13%
Readers by discipline Count As %
Engineering 13 33%
Computer Science 7 18%
Agricultural and Biological Sciences 3 8%
Neuroscience 3 8%
Philosophy 1 3%
Other 7 18%
Unknown 5 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 October 2012.
All research outputs
#20,171,868
of 22,684,168 outputs
Outputs from Frontiers in Neurorobotics
#682
of 844 outputs
Outputs of similar age
#221,189
of 244,115 outputs
Outputs of similar age from Frontiers in Neurorobotics
#8
of 9 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 844 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one.