Controlling a power assist robot for lifting objects considering human's unimanual, bimanual and cooperative weight perception

S. M.Mizanoor Rahman, Ryojun Ikeura, Masaya Nobe, Hideki Sawai

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

22 Scopus citations

Abstract

We developed a 1 DOF power assist robot for lifting objects. We hypothesized that human's perception of weight due to inertial force might be different from the perceived weight due to gravitational force for lifting an object with a power assist robot. We established psychophysical relationships between the actual weights and the power-assisted weights for the objects lifted with the robot, and also determined the excess in load forces that the subjects applied for three independent lifting schemes or grasp configurations: (i) unimanual lift, (ii) bimanual lift, and (iii) cooperative lift. We also compared the weight perceptual and load force features for the unimanual lifts to that for the bimanual and cooperative lifts. We then modified the power-assist control using a novel control strategy based on the weight perceptual and load force features. The control modification reduced the excessive load forces applied by the subjects in each lifting scheme and thus enhanced maneuverability, naturalness, ease of use, stability, safety etc. of the robot system significantly. Finally, we proposed using the findings to design human-friendly power assist robots for carrying heavy objects in various industries.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Robotics and Automation, ICRA 2010
Pages2356-2362
Number of pages7
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK, United States
Duration: May 3 2010May 7 2010

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other2010 IEEE International Conference on Robotics and Automation, ICRA 2010
Country/TerritoryUnited States
CityAnchorage, AK
Period5/3/105/7/10

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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