Speed-Accuracy Characteristics of Human-Machine Cooperative Manipulation Using Virtual Fixtures with Variable Admittance

By Marayong, Panadda; Okamura, Allison M. | Human Factors, Fall 2004 | Go to article overview

Speed-Accuracy Characteristics of Human-Machine Cooperative Manipulation Using Virtual Fixtures with Variable Admittance


Marayong, Panadda, Okamura, Allison M., Human Factors


INTRODUCTION

A goal of human-machine cooperative systems is to enhance user performance of tasks at the limits of human motor control. For example, microsurgical procedures such as retinal vein cannulation require operation at scales that exceed the capabilities of all but the most skilled surgeons (Weiss, 2001). Even macro-scale tasks, such as tracking a tool along a curve, can be mentally and physically demanding. Tremor and fatigue greatly affect accuracy and completion time during tracking tasks (Riviere, Rader, & Thakor, 1998). Robots can be more precise and untiring than humans, but the complexity of tasks they can perform in unstructured environments is restricted, given the limitations of artificial intelligence. Human-machine cooperative systems are designed to integrate the intelligence and experience of humans, as well as the precision and accuracy of robots, by allowing shared control between the human operator and the robot. Cooperative systems are especially useful in small-scale tasks such as microassembly and microsurgery, in which visual and haptic feedback to the user is limited. Our research extends the assistance provided by cooperative systems through the application of virtual fixtures.

Virtual fixtures are a means of providing assistance to a human operator in a cooperative or teleoperated manipulation system. Using an admittance-controlled robot, we have developed "guidance" virtual fixtures that assist human operators in the execution of tasks related to microsurgery (Bettini, Lang, Okamura, & Hager, 2001). In our admittance controller, the velocity output is proportional to the input force through an admittance gain. A human user operates the robot by pushing on a handle, as shown in Figure 1. Computer vision is used to detect a planar path to be followed, and an admittance control law with a configuration-dependent anisotropic gain matrix provides the user with physical assistance to stay on that path. The virtual fixtures can provide differing levels of guidance; complete guidance strictly prevents the user from deviating from the reference path, whereas no guidance allows the user to move with equal ease in any direction. The system was created as a human-centered design (Sheridan, 2000), even though it is possible for the robot to run autonomously The details of this system, as configured for our experiments, are provided in the Method section.

[FIGURE 1 OMITTED]

In this study, two experiments were performed to investigate the relationship between virtual fixture admittance and performance. Experiment 1 was designed to determine this relationship for a path-following task. Experiment 2 compared the effect of different levels of virtual fixture guidance on user performance in three general tasks: path following, off-path targeting, and avoidance. We hypothesize that the complete guidance virtual fixture will result in the lowest error and execution time for the path-following task and that a high level of guidance will increase error and execution time for the off-path targeting and the avoidance tasks. Based on the experimental results, we created models that can be used to select the appropriate level of guidance to maximize speed and accuracy, based on the nature of the task.

Related Work

Virtual fixtures have been previously applied to telemanipulation systems. Rosenberg (1993) provided an implementation of virtual fixtures for a peg-in-hole task in a teleoperated environment. The virtual fixtures were implemented using auditory feedback and impedance planes (virtual walls with stiffness and damping properties) on a haptic device master. Experimental results showed that the virtual fixtures improve task performance by as much as 70% as compared with when no fixtures are present.

Park, Howe, and Torchiana (2001) applied a virtual wall to the slave robot of a teleoperated surgical system, defining the position of the virtual fixture as the location of the internal mammary artery obtained from a preoperative CT scan. …

The rest of this article is only available to active members of Questia

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
One moment ...
Default project is now your active project.
Project items
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Buy instant access to cite pages or passages in MLA 8, MLA 7, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

(Einhorn 25)

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Note: primary sources have slightly different requirements for citation. Please see these guidelines for more information.

Cited article

Speed-Accuracy Characteristics of Human-Machine Cooperative Manipulation Using Virtual Fixtures with Variable Admittance
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

Help
Full screen
Items saved from this article
  • Highlights & Notes
  • Citations
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

matching results for page

    Questia reader help

    How to highlight and cite specific passages

    1. Click or tap the first word you want to select.
    2. Click or tap the last word you want to select, and you’ll see everything in between get selected.
    3. You’ll then get a menu of options like creating a highlight or a citation from that passage of text.

    OK, got it!

    Cited passage

    Style
    Citations are available only to our active members.
    Buy instant access to cite pages or passages in MLA 8, MLA 7, APA and Chicago citation styles.

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

    1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

    Cited passage

    Thanks for trying Questia!

    Please continue trying out our research tools, but please note, full functionality is available only to our active members.

    Your work will be lost once you leave this Web page.

    Buy instant access to save your work.

    Already a member? Log in now.

    Search by... Author
    Show... All Results Primary Sources Peer-reviewed

    Oops!

    An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.