AI RESEARCH
Viewpoint-Agnostic Grasp Pipeline using VLM and Partial Observations
arXiv CS.LG
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ArXi:2603.07866v1 Announce Type: cross Robust grasping in cluttered, unstructured environments remains challenging for mobile legged manipulators due to occlusions that lead to partial observations, unreliable depth estimates, and the need for collision-free, execution-feasible approaches. In this paper we present an end-to-end pipeline for language-guided grasping that bridges open-vocabulary target selection to safe grasp execution on a real robot.