A Mobile Robot Testbed for Prognostics-Enabled Autonomous Decision Making

Shared by Miryam Strautkalns, updated on Apr 26, 2013


Author(s) :
E. Balaban, S. Narasimhan, M. Daigle, J. Celaya, I. Roychoudhury, B. Saha, S. Saha, K. Goebel

The work described in this paper is aimed at providing an inexpensive, safe platform for development, validation, evaluation, and comparison of prognostics-enabled decision making algorithms. Technologies resulting from this research are planned to be transferred for further maturation on unmanned aerial vehicles and other complex systems. At present, the K11 testbed already constitutes a promising platform for PDM research. A list of fault modes of interest has been identified and a number of them have already been implemented in software and/or hardware. A software simulator has been developed that incorporates models of both nominal and off-nominal behavior, with some of the models verified using experimental data. The software architecture for the testbed has been defined in such a way as to allow quick replacement of autonomy elements depending on testing objectives and customers. The first set of reasoning algorithms, developed at NASA Ames, is being deployed.

Plans for the near future include addition of further injectable fault modes, field experiments of greater complexity, simulator model refinement, and extension of PDM methods to handle more complex problems, including constraints adjustment for optimal RUL . Data collected on the testbed is planned for distribution to other researchers in the field.

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