# CLARO: Open-vocabulary grasping in cluttered scenes with a VLM agent

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/txoxyusga3m0bza7qkeypoutb
- Original: https://arxiv.org/abs/2610.24016

## Summary

CLARO is a VLM agent that orchestrates skills such as open-vocabulary object detection, segmentation, 6-DoF grasping, and non-prehensile pushing to locate and retrieve a language-specified target in cluttered environments. It records past actions to support long-horizon execution and outputs grasp poses or 3D waypoints, enabling transfer to different robot arms without task-specific training. In a dynamic simulation environment, CLARO achieved an average success rate of 89.1%, a relative improvement of over 16% on the strongest competing method in highly cluttered scenes; on a real robot arm, its success rate was 88.8%.