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In this report, we present a robotic sample introduction/ionization system for mass spectrometry (MS) for spot analysis and imaging of non-planar surfaces. The system operates by probing the sample surface with an acupuncture needle, followed by direct plasma chemical ionization time-of-flight MS. Fil: Bennet, Rachel V.. Georgia Institute of Technology. School of Chemistry and Biochemistry; Estados Unidos Fil: Morzan, Ezequiel Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Georgia Institute of Technology. School of Chemistry and Biochemistry; Estados Unidos Fil: Huckaby, Jacob O.. Georgia Institute of Technology. Institute for Robotics and Intelligent Machines; Estados Unidos Fil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentina. Georgia Institute of Technology. School of Chemistry and Biochemistry; Estados Unidos Fil: Christensen, Henrick I.. Georgia Institute of Technology. Institute for Robotics and Intelligent Machines; Estados Unidos Fil: Fernández, Facundo M.. Georgia Institute of Technology. School of Chemistry and Biochemistry; Estados Unidos

In this paper we present the idea that by using AI planning in concert with formal task modeling, the overhead associated with plan creation for complex tasks can be reduced. The proposed approach uses a SysML taxonomy to model the system capabilities and the process specification, and the PDDL planning language to determine acceptable objective solutions. This idea is applied to the manufacturing domain, and examples are shown modeling a multi-robot system in an automobile manufacturing environment. A discussion is given regarding the merits of the demonstrated approach.