↓ Skip to main content

To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task

Overview of attention for article published in Frontiers in Psychology, June 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
6 X users

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
51 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task
Published in
Frontiers in Psychology, June 2017
DOI 10.3389/fpsyg.2017.01061
Pubmed ID
Authors

Maurice Lamb, Rachel W. Kallen, Steven J. Harrison, Mario Di Bernardo, Ali Minai, Michael J. Richardson

Abstract

Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the affordance related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of what, when, where and how to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 31%
Researcher 5 10%
Student > Bachelor 4 8%
Student > Master 4 8%
Student > Doctoral Student 3 6%
Other 9 18%
Unknown 10 20%
Readers by discipline Count As %
Psychology 15 29%
Engineering 8 16%
Computer Science 5 10%
Mathematics 2 4%
Medicine and Dentistry 2 4%
Other 7 14%
Unknown 12 24%
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 14 July 2023.
All research outputs
#14,849,289
of 25,761,363 outputs
Outputs from Frontiers in Psychology
#13,711
of 34,783 outputs
Outputs of similar age
#163,030
of 329,425 outputs
Outputs of similar age from Frontiers in Psychology
#322
of 612 outputs
Altmetric has tracked 25,761,363 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 34,783 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one has gotten more attention than average, scoring higher than 59% 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 329,425 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 612 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.