Primitive static states for intelligent operated-work machines

Mitsuhiro Kamezaki*, Hiroyasu Iwata, Shigeki Sugano

*Corresponding author for this work

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

23 Citations (Scopus)


Advanced operated-work machines, which have been designed for complicated tasks and which have complicated operating systems, requires intelligent systems that can provide the quantitative work analysis needed to determine effective work procedures and that can provide operational and cognitive support for operators. Construction work environments are extremely complicated, however, and this makes state identification, which is a key technology for an intelligent system, difficult. We therefore defined primitive static states (PSS) that are determined using on-off information for the lever inputs and manipulator loads for each part of the grapple and front and that are completely independent of the various environmental conditions and variation in operator skill level that can cause an incorrect work state identification. To confirm the usefulness of PSS, we performed experiments with a demolition task by using our virtual reality simulator. We confirmed that PSS could robustly and accurately identify the work states and that untrained skills could be easily inferred from the results of PSS-based work analysis. We also confirmed in skill-training experiments that advice information based on PSS-based skill analysis greatly improved operator's work performance. We thus confirmed that PSS can adequately identify work states and are useful for work analysis and skill improvement.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Robotics and Automation, ICRA '09
Number of pages6
Publication statusPublished - 2009
Event2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe, Japan
Duration: 2009 May 122009 May 17

Publication series

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


Conference2009 IEEE International Conference on Robotics and Automation, ICRA '09

ASJC Scopus subject areas

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


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