Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency

There is considerable interest in multirobot systems capable of performing spatially distributed, hazardous, and complex tasks as a team leveraging the unique abilities of humans and automated machines working alongside each other. The limitations of human perception and cognition affect operators’...

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Bibliographic Details
Main Authors: Nathan Lucas, Abhilash Pandya
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Robotics
Subjects:
Online Access:https://www.mdpi.com/2218-6581/10/2/71
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spelling doaj-8b75945d349444418edfd91cb5debc292021-06-01T00:14:31ZengMDPI AGRobotics2218-65812021-05-0110717110.3390/robotics10020071Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and EfficiencyNathan Lucas0Abhilash Pandya1Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USADepartment of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USAThere is considerable interest in multirobot systems capable of performing spatially distributed, hazardous, and complex tasks as a team leveraging the unique abilities of humans and automated machines working alongside each other. The limitations of human perception and cognition affect operators’ ability to integrate information from multiple mobile robots, switch between their spatial frames of reference, and divide attention among many sensory inputs and command outputs. Automation is necessary to help the operator manage increasing demands as the number of robots (and humans) scales up. However, more automation does not necessarily equate to better performance. A generalized robot confidence model was developed, which transforms key operator attention indicators to a robot confidence value for each robot to enable the robots’ adaptive behaviors. This model was implemented in a multirobot test platform with the operator commanding robot trajectories using a computer mouse and an eye tracker providing gaze data used to estimate dynamic operator attention. The human-attention-based robot confidence model dynamically adapted the behavior of individual robots in response to operator attention. The model was successfully evaluated to reveal evidence linking average robot confidence to multirobot search task performance and efficiency. The contributions of this work provide essential steps toward effective human operation of multiple unmanned vehicles to perform spatially distributed and hazardous tasks in complex environments for space exploration, defense, homeland security, search and rescue, and other real-world applications.https://www.mdpi.com/2218-6581/10/2/71multirobotteleoperationshuman–robot interfaceseye trackinghuman performance
collection DOAJ
language English
format Article
sources DOAJ
author Nathan Lucas
Abhilash Pandya
spellingShingle Nathan Lucas
Abhilash Pandya
Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency
Robotics
multirobot
teleoperations
human–robot interfaces
eye tracking
human performance
author_facet Nathan Lucas
Abhilash Pandya
author_sort Nathan Lucas
title Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency
title_short Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency
title_full Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency
title_fullStr Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency
title_full_unstemmed Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency
title_sort multirobot confidence and behavior modeling: an evaluation of semiautonomous task performance and efficiency
publisher MDPI AG
series Robotics
issn 2218-6581
publishDate 2021-05-01
description There is considerable interest in multirobot systems capable of performing spatially distributed, hazardous, and complex tasks as a team leveraging the unique abilities of humans and automated machines working alongside each other. The limitations of human perception and cognition affect operators’ ability to integrate information from multiple mobile robots, switch between their spatial frames of reference, and divide attention among many sensory inputs and command outputs. Automation is necessary to help the operator manage increasing demands as the number of robots (and humans) scales up. However, more automation does not necessarily equate to better performance. A generalized robot confidence model was developed, which transforms key operator attention indicators to a robot confidence value for each robot to enable the robots’ adaptive behaviors. This model was implemented in a multirobot test platform with the operator commanding robot trajectories using a computer mouse and an eye tracker providing gaze data used to estimate dynamic operator attention. The human-attention-based robot confidence model dynamically adapted the behavior of individual robots in response to operator attention. The model was successfully evaluated to reveal evidence linking average robot confidence to multirobot search task performance and efficiency. The contributions of this work provide essential steps toward effective human operation of multiple unmanned vehicles to perform spatially distributed and hazardous tasks in complex environments for space exploration, defense, homeland security, search and rescue, and other real-world applications.
topic multirobot
teleoperations
human–robot interfaces
eye tracking
human performance
url https://www.mdpi.com/2218-6581/10/2/71
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AT abhilashpandya multirobotconfidenceandbehaviormodelinganevaluationofsemiautonomoustaskperformanceandefficiency
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