We present a field deployment of a collaborative scientist-robot system that enables improved scientific gain for planetary science missions. In this system, the scientist interacts with the autonomy through a computer interface to specify prior disciplinary knowledge, hypothesis information, and refine the mission objectives using preferences and ratings. The goal of this interaction is to use autonomy where it works best, optimizing robot data collection paths under a set of constraints, while enabling scientists to communicate priors and objectives in a straightforward and efficient manner. The system was deployed with a quadruped during a planetary analog field science mission at White Sands National Park, New Mexico, to support the investigation of the surface and shallow subsurface properties of the Martian analog dunes. The system was used to generate robot paths for three different mission scientists, who had varying priors and objectives. A quadruped robot executed the path providing data on the stiffness of the surface measured through ground-leg interactions. The generated dense stiffness measurements were used by scientists to select refined locations for follow-up data collection. While, we found that more work is needed to fully incorporate human priors, our deployed system enabled scientists to collect mission-critical data more efficiently, and they were able to adapt the system to their science needs.