Lizard air-righting trajectories, captured with computer vision and analyzed by multi-objective optimization, are proposed as reference motions for reorienting free-floating space manipulators.
Reinforcement Learning of Space Robotic Manipulation with Multiple Safety Constraints,
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Adapting Biological Reflexes for Dynamic Reorientation in Space Manipulator Systems
Lizard air-righting trajectories, captured with computer vision and analyzed by multi-objective optimization, are proposed as reference motions for reorienting free-floating space manipulators.