Modeling user's driving-characteristics in a steering task to customize a virtual fixture based on task-performance

Han U. Yoon, Ranxiao F. Wang, Seth A. Hutchinson

Research output: Contribution to journalConference article

Abstract

This paper presents an approach for modeling user's driving-characteristics in a steering task, and determining the parameters of a virtual fixture to assist the user-control on the basis of his/her task-performances. First, we briefly introduce our assistive human-robot interaction (HRI) interface and a virtual fixture as backgrounds related to this research. The designed HRI interface provides assistance by actively constraining the user-control with a virtual fixture. Second, we discuss a way to model a user's driving-characteristics in a steering task. In modeling the driving-characteristics, we use techniques from inverse optimal control (IOC), where known basis functions (speed, steering, and proximities to inner/outer road boundary) are employed to design a cost function. Third, we describe the experimental setup and procedures to obtain user-demonstrated data from human subjects. Utilizing the obtained data sets, we infer the unknown parameter vector by solving inverse optimal control. Afterward, the user's driving-characteristics are expressed in terms of the balances of the inferred parameters, allowing us to find a relationship between the modeled driving-characteristics and task-completion time. Finally, we present a method to set a virtual fixture for a newly given task by predicting the user's task-performances.

Original languageEnglish (US)
Article number6906920
Pages (from-to)625-630
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
DOIs
StatePublished - Sep 22 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: May 31 2014Jun 7 2014

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Human robot interaction
Cost functions

ASJC Scopus subject areas

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

Cite this

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abstract = "This paper presents an approach for modeling user's driving-characteristics in a steering task, and determining the parameters of a virtual fixture to assist the user-control on the basis of his/her task-performances. First, we briefly introduce our assistive human-robot interaction (HRI) interface and a virtual fixture as backgrounds related to this research. The designed HRI interface provides assistance by actively constraining the user-control with a virtual fixture. Second, we discuss a way to model a user's driving-characteristics in a steering task. In modeling the driving-characteristics, we use techniques from inverse optimal control (IOC), where known basis functions (speed, steering, and proximities to inner/outer road boundary) are employed to design a cost function. Third, we describe the experimental setup and procedures to obtain user-demonstrated data from human subjects. Utilizing the obtained data sets, we infer the unknown parameter vector by solving inverse optimal control. Afterward, the user's driving-characteristics are expressed in terms of the balances of the inferred parameters, allowing us to find a relationship between the modeled driving-characteristics and task-completion time. Finally, we present a method to set a virtual fixture for a newly given task by predicting the user's task-performances.",
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