Keywords

Human robot interaction, human robot interface, multi robot systems, multi robot manipulation, machine learning

Abstract

Designing an effective human-robot interaction paradigm is particularly important for complex tasks such as multi-robot manipulation that require the human and robot to work together in a tightly coupled fashion. Although increasing the number of robots can expand the area that the robots can cover within a bounded period of time, a poor human-robot interface will ultimately compromise the performance of the team of robots. However, introducing a human operator to the team of robots, does not automatically improve performance due to the difficulty of teleoperating mobile robots with manipulators. The human operator’s concentration is divided not only among multiple robots but also between controlling each robot’s base and arm. This complexity substantially increases the potential neglect time, since the operator’s inability to effectively attend to each robot during a critical phase of the task leads to a significant degradation in task performance. There are several proven paradigms for increasing the efficacy of human-robot interaction: 1) multimodal interfaces in which the user controls the robots using voice and gesture; 2) configurable interfaces which allow the user to create new commands by demonstrating them; 3) adaptive interfaces which reduce the operator’s workload as necessary through increasing robot autonomy. This dissertation presents an evaluation of the relative benefits of different types of user interfaces for multi-robot systems composed of robots with wheeled bases and three degree of freedom arms. It describes a design for constructing low-cost multi-robot manipulation systems from off the shelf parts. User expertise was measured along three axes (navigation, manipulation, and coordination), and participants who performed above threshold on two out of three dimensions on a calibration task were rated as expert. Our experiments reveal that the relative expertise of the user was the key determinant of the best performing interface paradigm for that user, indicating that good user modiii eling is essential for designing a human-robot interaction system that will be used for an extended period of time. The contributions of the dissertation include: 1) a model for detecting operator distraction from robot motion trajectories; 2) adjustable autonomy paradigms for reducing operator workload; 3) a method for creating coordinated multi-robot behaviors from demonstrations with a single robot; 4) a user modeling approach for identifying expert-novice differences from short teleoperation traces.

Notes

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Graduation Date

2014

Semester

Spring

Advisor

Sukthankar, Gita

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computing

Degree Program

Computer Engineering

Format

application/pdf

Identifier

CFE0005198

URL

http://purl.fcla.edu/fcla/etd/CFE0005198

Language

English

Release Date

May 2014

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

Restricted to the UCF community until May 2014; it will then be open access.

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