# Integration of Vision-based Object Detection and Grasping for Articulated Manipulator in Lunar Conditions

Source: [Integration of Vision-based Object Detection and Grasping for Articulated Manipulator in Lunar Conditions](<https://www.sota2.com/research/paper/68fa707f1e209131cea4b842>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:43:00.780Z

Authors: Camille Boucher, Gustavo H. Diaz, Shreya Santra, Kentaro Uno, Kazuya Yoshida

Published: 2023-09-03T02:18:35.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2309.01055>)

[PDF](<https://arxiv.org/pdf/2309.01055.pdf>)