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Model of Mobile Manipulator Performance Measurement using SysML.

Roger Bostelman1,2, Sebti Foufou3,2, Tsai Hong1

  • 1National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.

Journal of Intelligent & Robotic Systems
|May 17, 2019
PubMed
Summary
This summary is machine-generated.

Standardized test methods are needed for mobile manipulators. This study introduces Systems Modeling Language (SysML) to model performance measurement techniques for comparing mobile manipulator systems and tasks.

Keywords:
controlmobile manipulatorperformance measurementstandardssystems modeling language (SysML)test methods

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Area of Science:

  • Robotics
  • Systems Engineering
  • Measurement Science

Background:

  • Standardized test methods for mobile manipulators are currently lacking, hindering system comparison.
  • Users and manufacturers need reliable methods to evaluate and compare different mobile manipulator systems and their performance on specific tasks.

Purpose of the Study:

  • To propose and model test methods for measuring the safety and performance of mobile manipulators.
  • To enable objective comparison between different mobile manipulator configurations and control strategies.

Main Methods:

  • Utilized Systems Modeling Language (SysML) to describe measurement methodologies.
  • Modeled two specific measurement techniques: optical tracking and artifact-based methods.
  • Applied SysML models to performance measurement of mobile manipulators during assembly tasks.

Main Results:

  • Developed SysML models for mobile manipulator performance measurement.
  • Demonstrated the application of these models for assembly tasks.
  • Verified models through systems review and referenced experimentation.

Conclusions:

  • SysML provides a robust framework for defining and comparing mobile manipulator performance.
  • The proposed methods facilitate objective evaluation of mobile manipulator systems and their task execution capabilities.
  • Uncertainty propagation models were integrated to summarize measurement reliability.