A practical load detection framework considering uncertainty in hydraulic pressure-based force measurement for construction manipulator

Mitsuhiro Kamezaki*, Hiroyasu Iwata, Shigeki Sugano

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

This paper proposes a practical framework for detecting (identifying the on-off state of) the external force applied to a construction manipulator (front load) by using a hydraulic sensor. Such a detection system requires high accuracy and robustness considering the uncertainty in pressure-based force measurement. Our framework is thus organized into (i) identifying the dominant error force component (self-weight and driving force) using theoretical and experimental estimation and binarizing the analog external cylinder force, (ii) evaluating detection conditions to address indeterminate conditions such as stroke-end, singular posture, and impulsive or oscillatory force and redefining three-valued outputs such as on, off, or not determinate (ND), and (iii) outputting the front load decision by combining all the cylinder decisions to improve robustness through priority analysis. Experiments were conducted using an instrumented hydraulic arm. Results indicate that our framework adequately detects on, off, and ND outputs of the front load in various detection conditions without misidentification.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Robotics and Automation, ICRA 2011
Pages5869-5874
Number of pages6
DOIs
Publication statusPublished - 2011
Event2011 IEEE International Conference on Robotics and Automation, ICRA 2011 - Shanghai, China
Duration: 2011 May 92011 May 13

Publication series

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

Conference

Conference2011 IEEE International Conference on Robotics and Automation, ICRA 2011
Country/TerritoryChina
CityShanghai
Period11/5/911/5/13

ASJC Scopus subject areas

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

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