Integration of Vision-based Object Detection and Grasping for Articulated Manipulator in Lunar Conditions
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Abstract (arXiv)
The integration of vision-based frameworks to achieve lunar robot applications faces numerous challenges such as terrain configuration or extreme lighting conditions. This paper presents a generic task pipeline using object detection, instance segmentation and grasp detection, that can be used for various applications by using the results of these vision-based systems in a different way. We achieve a rock stacking task on a non-flat surface in difficult lighting conditions with a very good success rate of 92%. Eventually, we present an experiment to assemble 3D printed robot components to initiate more complex tasks in the future.
Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 14 of its 32 references that are in the map. First posted on arXiv 3 Sep 2023.
Builds on
14 of 32 references.
References · 14
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