Multirobot Confidence And Behavior Modeling: An Evaluation Of Telerobotic Performance And Efficiency
Access Type
Open Access Embargo
Date of Award
January 2019
Degree Type
Dissertation
Degree Name
Ph.D.
Department
Electrical and Computer Engineering
First Advisor
Abhilash . Pandya
Abstract
There is considerable interest in multirobot systems capable of performing spatially distributed, hazardous, and complex tasks as a team. There is also growing interest in manned-unmanned teams leveraging the unique abilities of humans and automated machines working alongside each other. The limitations of human perception and cognition affect the ability of operators 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 scales up. However, more automation does not necessarily equate to better performance.
This research developed novel techniques applicable to user interface designs for the remote operation of multiple unmanned vehicles. A generalized robot confidence model was introduced which transforms an arbitrary number of indicators of operator attention to a confidence value for each robot in order to enable adaptive behaviors for an arbitrary number of robots. The model was implemented and successfully evaluated to reveal evidence linking average robot confidence to multirobot search task performance and efficiency. The contributions of this work provide important steps toward effective human teleoperation of multiple mobile robots to perform spatially distributed and hazardous tasks in complex environments for space exploration, defense, homeland security, search and rescue, and other real-world applications.
Recommended Citation
Lucas, Nathan, "Multirobot Confidence And Behavior Modeling: An Evaluation Of Telerobotic Performance And Efficiency" (2019). Wayne State University Dissertations. 2363.
https://digitalcommons.wayne.edu/oa_dissertations/2363