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Everyday robotic action: lessons from human action control

Overview of attention for article published in Frontiers in Neurorobotics, March 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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1 YouTube creator

Citations

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16 Dimensions

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56 Mendeley
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Title
Everyday robotic action: lessons from human action control
Published in
Frontiers in Neurorobotics, March 2014
DOI 10.3389/fnbot.2014.00013
Pubmed ID
Authors

Roy de Kleijn, George Kachergis, Bernhard Hommel

Abstract

Robots are increasingly capable of performing everyday human activities such as cooking, cleaning, and doing the laundry. This requires the real-time planning and execution of complex, temporally extended sequential actions under high degrees of uncertainty, which provides many challenges to traditional approaches to robot action control. We argue that important lessons in this respect can be learned from research on human action control. We provide a brief overview of available psychological insights into this issue and focus on four principles that we think could be particularly beneficial for robot control: the integration of symbolic and subsymbolic planning of action sequences, the integration of feedforward and feedback control, the clustering of complex actions into subcomponents, and the contextualization of action-control structures through goal representations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 2%
Canada 1 2%
Unknown 54 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 14%
Researcher 8 14%
Student > Doctoral Student 7 13%
Student > Bachelor 6 11%
Student > Master 6 11%
Other 14 25%
Unknown 7 13%
Readers by discipline Count As %
Psychology 16 29%
Computer Science 12 21%
Neuroscience 4 7%
Agricultural and Biological Sciences 3 5%
Engineering 3 5%
Other 7 13%
Unknown 11 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 September 2019.
All research outputs
#12,605,103
of 22,751,628 outputs
Outputs from Frontiers in Neurorobotics
#208
of 853 outputs
Outputs of similar age
#111,935
of 243,431 outputs
Outputs of similar age from Frontiers in Neurorobotics
#2
of 7 outputs
Altmetric has tracked 22,751,628 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 853 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 243,431 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.