CEC Graduate Student, Martijn IJtsma, Successfully Defends his PhD in Aerospace Engineering

OCT 29, 2018 -- Today, CEC graduate student, Martijn IJtsma, successfully defended his PhD in Aerospace Engineering, titled, “Computational Simulation of Adaptation of Work Strategies in Human-Robot Teams.” His research is advised by Professors Amy Pritchett and Karen Feigh of the CEC with committee members Prof. Eric Feron (GT-AE), Prof. John-Paul Clarke (GT-AE), and Dr. Matthew Johnson (Institute for Human & Machine Cognition). Below is the abstract of his dissertation with his presentation archived here:

Future manned spaceflight missions require human-robot teams that are resilient and can adapt fluently to changing work demands. Most of the existing work on adaptation focuses on the modeling of work strategies and adaptation of a single individual. Insights relate mainly to human-automation pairs, and have not explicitly addressed adaptation in human-robot teams involving multiple humans working with multiple robots. Furthermore, existing work did not consider technology as embodied agents working alongside humans, but as tools, which has important implications for the interaction and type of teamwork that is modeled.

The aim of this thesis is to gain a deeper understanding of adaptation of work strategies in human-robot teams, specifically how human-robot interaction protocols and function allocation can foster and/or limit such adaptation. To analyze these effects, this work will model adaptation to work demands in a team of humans and robots by mapping existing models of individual human adaptation to multi-agent systems. This modeling will be done from a work-perspective, identifying where dynamics of the work and human-robot interaction limit available work strategies and the associated effect on adaptation.

Central to this thesis is the use of computational simulation to model work strategies and adaptation. By taking a simulation approach, the dynamic and emergent nature of the problem can be analyzed directly, which distinguishes the proposed work from existing work that has employed qualitative or static analyses to study adaptation of humans, and teamwork and human-robot interaction in teams.

The presentation can be found here.


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