This paper will present a model for collaborative space exploration through effective and efficient cooperation of humans and robots — an extension to the Cooperation of Humans and Robots Model (CHARM) developed by the Human-Robotic Cooperation (HRC) team at the International Space University’s 2011 Space Studies Program held in Graz, Austria. The HRC team integrated international, intercultural, and interdisciplinary perspectives to develop a decision-making model (the CHARM model) capable of selecting a mission scenario which best utilizes humans and robotics in order to accomplish a given objective. Human and robotic capabilities differ, with each offering their own benefits and drawbacks. Robots are reliable and accurate, and can operate in hostile environments — all attributes well-suited for space exploration. However, when faced with new scenarios and unexpected events, robots pale in comparison with the intuition and creativity of humans. Future space exploration will have to intelligently balance the flexibility and ingenuity of humans with robust and sophisticated robotic systems. Based on various space agency goals and the 2011 International Space Exploration Coordination Group (ISECG) Roadmap, this paper selects an exploration objective for the timeframe between 2015 and 2030, and drafts different scenarios to accomplish this objective. Each scenario uses different degrees of human-robot interaction. CHARM is applied to select an optimal mix of human and robotics in order to accomplish the selected objective. CHARM uses an interdisciplinary approach, scoring attributes including technical, scientific, life sciences, political, social, financial, and legal perspectives. In this iteration of CHARM, an Analytical Hierarchy Process is used to assign weighting values to each attribute and the respective categories. The weights are complemented with those collected by survey of a panel of international experts in space exploration mission planning. The results demonstrate that CHARM can be used to select missions efficiently and rationally, thereby reducing both mission costs and risks, making space exploration more feasible and long-term space exploration sustainable. To quantify output confidence in the CHARM scenario selection, a Monte Carlo probabilistic simulation is used to analyze the uncertainty in attribute weighting, introduced by the inclusion of numerous weight value input sources
