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Robots are crucial for exploring distant celestial bodies. The Surface Avatar ISS-to-Earth Telerobotic Technology Demonstration Mission investigates how to command a heterogeneous team of robots from orbit using scalable autonomy. In this experiment series astronauts aboard the International Space Station (ISS) command a team of robots located on Earth. One challenge identified in these experiments is that the robot’s decision-making process is affected by environmental uncertainty especially for the robot’s pose estimation and navigation. Traditional planning algorithms assume perfect knowledge of the robot’s surroundings, neglecting the role of imperfect sensing. This paper addresses this limitation by developing an uncertainty-aware planning method and demonstrating its application to address perception inaccuracies in navigation, paving the way for its broader adoption in other domains. The proposed uncertainty aware planning framework is tested for localization and navigation by the humanoid robot Rollin’ Justin during a space-to-ground telerobotic experiment as part of the Surface Avatar mission.
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Köpken et al. (2025) studied this question.
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