Human-human haptic collaboration in cyclical Fitts' tasks

Sommer Gentry, Eric Feron, Roderick Murray-Smith

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Understanding how humans assist each other in haptic interaction teams could lead to improved robotic aids to solo human dextrous manipulation. Inspired by experiments re- ported in Reed et al. [1], which suggested two-person haptically interacting teams could achieve a lower movement time (MT) than individuals for discrete aiming movements of specified accuracy, we report that two-person teams (dyads) can also achieve lower MT for cyclical, continuous aiming movements. We propose a model, called endpoint compromise, for how the intended endpoints of both subjects' motion combine during haptic interaction; it predicts a ratio of √2 between slopes of MT fits for individuals and dyads. This slope ratio prediction is supported by our data.

Original languageEnglish (US)
Title of host publication2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
PublisherIEEE Computer Society
Number of pages6
ISBN (Print)0780389123, 9780780389120
StatePublished - 2005
Externally publishedYes

Publication series

Name2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS


  • Fitts' law
  • Haptic interaction
  • Human-human collaboration
  • Rhythm
  • Rhythmic interaction

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Systems Engineering


Dive into the research topics of 'Human-human haptic collaboration in cyclical Fitts' tasks'. Together they form a unique fingerprint.

Cite this