Augmented Reality Effects in JAUS Subsystem Commander Teleoperation Interfaces Gregory Garcia Center...

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Augmented Reality Effects in JAUS Subsystem Commander Teleoperation Interfaces Gregory Garcia Center for Intelligent Machines and Robotics Dept. of Mechanical and Aerospace Engineering University of Florida Problem areas with AGV teleoperation interfaces: - Communication - High-overhead - Poorly Designed - Outdated technologies

Transcript of Augmented Reality Effects in JAUS Subsystem Commander Teleoperation Interfaces Gregory Garcia Center...

Page 1: Augmented Reality Effects in JAUS Subsystem Commander Teleoperation Interfaces Gregory Garcia Center for Intelligent Machines and Robotics Dept. of Mechanical.

Augmented Reality Effects in JAUS Subsystem Commander Teleoperation Interfaces

Gregory Garcia

Center for Intelligent Machines and RoboticsDept. of Mechanical and Aerospace EngineeringUniversity of Florida

December 2008

Problem areas with AGV teleoperation interfaces:

- Communication - High-overhead - Poorly Designed - Outdated technologies

Page 2: Augmented Reality Effects in JAUS Subsystem Commander Teleoperation Interfaces Gregory Garcia Center for Intelligent Machines and Robotics Dept. of Mechanical.

Center for Intelligent Machines and RoboticsCollege of Engineering

Existing Interface

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Center for Intelligent Machines and RoboticsCollege of Engineering

Functional Demonstration

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Page 4: Augmented Reality Effects in JAUS Subsystem Commander Teleoperation Interfaces Gregory Garcia Center for Intelligent Machines and Robotics Dept. of Mechanical.

Center for Intelligent Machines and RoboticsCollege of Engineering

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User Study ConditionsApparatus: • Quiet Room (2 days)• Laptop Computer (15.4 inch 1280x800 display)• Optical Mouse• Experimental and control InterfacesStudy Protocol:• 5 minute tutorial and Q/A (2x) • Interface Evaluation (2x)• QuestionnaireMetrics:Quantitative

• Error Rate • Decision making time

Qualitative• Situational Awareness• Interaction Style• Eye Gaze

• Ease of use• User Confidence

• Strengths/ Weaknesses

• Random testing order

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Center for Intelligent Machines and RoboticsCollege of Engineering

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Results and AnalysisHo: OERstandard ≤ OERvideo Ha: OER standard > OERvideo

p-value = 0.27996, t’ = 0.58977, tα = 1.69913• Fail to reject the Null Hypothesis

• 28% probability that pattern is due to chance

One sided T-test for independent samples w/ unequal variancesα = .05

Two sided T-test for independent samples w/ unequal variancesα = .05

H0: DMTstandard – DMTvideo = 0 Ha: DMTstandard – DMTvideo ≠ 0

p-value = 0.2203, t’ = 1.26524, tα/2 = 2.08596• Fail to reject the Null Hypothesis

• 22% probability that patter is due to chance

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Center for Intelligent Machines and RoboticsCollege of Engineering

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Results and Analysis (2)

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Decision Time given Standard In-terface First

No Video Time

With Video Time

Tim

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012345678

Decision Time given Video In-terface First

No Video Time

With Video Time

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No Video Time With Video Time6.419411765 5.028823529

No Video With Video0

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User Situational Awareness

Very Aware

Somewhat Aware

Other Observations• Unanimously chose Video interface• Highest marks for ease of learning• Increased User Confidence Level• Color scheme received favorably• Rely heavily on video for initial big-

picture, used sensor fusion for details

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Center for Intelligent Machines and RoboticsCollege of Engineering

Questions?