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One of the key issues in space exploration is that of deciding what space tasks are best done with humans, with robots, or a suitable combination of each. In general, human and robot skills are complementary. Humans provide as yet unmatched capabilities to perceive, think, and act when faced with anomalies and unforeseen events, but there can be huge potential risks to human safety in getting these benefits. Robots provide complementary skills in being able to work in extremely risky environments, but their ability to perceive, think, and act by themselves is currently not error-free, although these capabilities are continually improving with the emergence of new technologies. Substantial past experience validates these generally qualitative notions. However, there is a need for more rigorously systematic evaluation of human and robot roles, in order to optimize the design and performance of human-robot system architectures using well-defined performance evaluation metrics. This article summarizes a new analytical method to conduct such quantitative evaluations. While the article focuses on evaluating human-robot systems, the method is generally applicable to a much broader class of systems whose performance needs to be evaluated.

The Telerobotics Program of the National Aeronautics and Space Administration (NASA) Office of Space Science is developing innovative telerobotics technologies to enable or support a wide range of space missions over the next decade and beyond. These technologies fall into four core application areas: landers, surface vehicles (rovers), and aerovehicles for solar system exploration and science; rovers for commercially supported lunar activities; free-flying and platform-attached robots for in-orbit servicing and assembly; and robots supporting in-orbit biotechnology and microgravity experiments. Such advanced robots will enable missions to explore Mars, Venus, and Saturn‘s moon Titan, as well as probes to sample comets and asteroids. They may also play an important role in commercially funded exploration of large regions on Earth‘s Moon, as well as the eventual development of a human-supporting Lunar Outpost. In addition, in-orbit servicing of satellites and maintenance of large platforms like the International Space Station will require extensive robotics capabilities.

One of the key issues in space exploration is that of deciding what space tasks are best done with humans, with robots, or a suitable combination of each. In general, human and robot skills are complementary. Humans provide as yet unmatched capabilities to perceive, think, and act when faced with anomalies and unforeseen events, but there can be huge potential risks to human safety in getting these benefits. Robots provide complementary skills in being able to work in extremely risky environments, but their ability to perceive, think, and act by themselves is currently not error-free, although these capabilities are continually improving with the emergence of new technologies. Substantial past experience validates these generally qualitative notions. However, there is a need for more rigorously systematic evaluation of human and robot roles, in order to optimize the design and performance of human-robot system architectures using well-defined performance evaluation metrics. This article summarizes a new analytical method to conduct such quantitative evaluations. While the article focuses on evaluating human-robot systems, the method is generally applicable to a much broader class of systems whose performance needs to be evaluated.