Mission planning and navigation support for lunar and planetary exploration

Abstract

When mankind returns to the moon and eventually voyages to Mars, the ability to effectively carry out surface extra-vehicular activities (EVAs) ill be critical to overall mission success. This thesis investigates improving planetary EVAs via a support system to enable optimized mission operations. In order to develop a robustly effective aid capable of performing under the high time pressure, risk, and uncertainty inherent in space exploration, key surface operation factors are examined to understand to best fit role of automated support within complex, changing exploration situations. A detailed characterization of the makeup and challenges of planetary surface EVAs was used to establish a specific framework for maximizing the productivity of these missions. Recognizing the need for automated support in achieving such optimal performance, the presentation of methods by which all pertinent mission factors may be quantitatively modeled led to creation of a comprehensive automated mission support architecture. Based on this analysis and motivated by ongoing field testing, a prototype mission support system was developed with twofold intent: both for pre-mission planning and simulation as well as for real-time explorer navigation and re-planning. The prototype presents an intuitive interface where controllers may quickly represent a broad range of mission parameters and scenarios in order to determine a best course of action for immediate execution. Specifically, this system optimizes explorer traverses with respect to given cost functions via a novel implementation of the A* search algorithm. Developed plans may further be linked to a global positioning system to empower real-time team navigation.

(cont.) Through the completion of experimental EVA simulations involving physical explorers on a remote terrain jointly controlled by a multi-university team, the developed system was shown to robustly respond to situational updates and contingencies to maintain optimal mission performance in near real-time, offering enhanced functionality where preceding systems fell short. The analysis closes with a discussion on the opportunities for such a system as well as potential areas for further improvement.