MOMDP-Based Target Search Mission Taking into Account the Human Operator's Cognitive State

Paulo Eduardo Ubaldino de Souza, Caroline Ponzoni Carvalho Chanel, Frederic Dehais
2015 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)  
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Abstract-This study discusses the application of sequential decision making under uncertainty and mixed observability in a mixed-initiative robotic target search application. In such a robotic mission, two agents, a ground robot and a human operator, must collaborate to reach a common goal using, each in turn, their recognized skills. The originality of
more » ... e originality of the work relies in considering that the human operator is not a providential agent when the robot fails. Using the data from previous experiments, a Mixed Observability Markov Decision Process (MOMDP) model was designed, which allows to consider aleatory failure events and the partial observable human operator's state while planning for a long-term horizon. Results show that the collaborative system was in general able to successfully complete or terminate the mission, even when many simultaneous sensors, devices and operators failures happened. So, the mixed-initiative framework highlighted in this study shows the relevancy of taking into account the cognitive state of the operator, which permits to compute a policy for the sequential decision problem which prevents to re-planning when unexpected (but known) events occurs.
doi:10.1109/ictai.2015.109 dblp:conf/ictai/SouzaCD15 fatcat:vsij47z6jfecxlozqjkpijptg4