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Robots learn event-referential grasping for occluded objects

By PulseAugur Editorial · [1 sources] ·

Researchers have developed BeyondSCe, a novel zero-shot robotic grasping system designed for scenarios where objects are identified by their role in past events rather than direct appearance. This system can locate requested objects even if they are occluded, by using event history and current scene geometry to select optimal camera viewpoints. In real-world experiments, BeyondSCe demonstrated significant improvements in grasp success rates, particularly for occluded targets, and reduced the number of views required to locate objects compared to baseline methods. AI

IMPACT Enhances robot's ability to understand and act on contextual event information, potentially improving human-robot interaction.

RANK_REASON Academic paper detailing a new method for robotic grasping. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Robots learn event-referential grasping for occluded objects

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Academic paper detailing a new method for robotic grasping. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Hyunjoon Lee, Haebeom Jung, Eunsung Cha, Daeun Lee, Yu-Chiang Frank Wang, Jaesung Choe, Jaesik Park ·

    Beyond the Current Scene: Event-Referential Grasping with Active View Selection

    arXiv:2609.39375v1 Announce Type: cross Abstract: A robot that observes people interacting with objects should be able to carry out later requests that refer back to those interactions. Such requests may specify a grasp target by the role it played in a past event rather than by …

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