arXiv:2607. 17754v1 Announce Type: cross Abstract: In logistics automation, precise segmentation of unseen objects is crucial for efficient robotic manipulation in cluttered environments.
By Yesol Park, Hye-Jung Yoon, Juno Kim, Byoung-Tak Zhang
arXiv:2607. 17757v1 Announce Type: cross Abstract: Current bin picking methods that rely heavily on end-to-end learning often falter when confronted with unfamiliar or complex objects in unstructured environments.
By Hye-Jung Yoon, Juno Kim, Yesol Park, Jun-Ki Lee, Byoung-Tak Zhang
AnyBox is a zero‑shot framework that estimates the full 9DoF pose (6D pose plus 3D dimensions) of boxes from a single RGB‑D image, leveraging the geometric regularity of boxes. It alternates between pose and scale estimation, using a binary search guided by the discrepancy between a reprojected template and the observed mask, and employs a depth‑consistency filter and an early‑stopping rule to prune implausible hypotheses. On public benchmarks and a warehouse dataset, AnyBox improves detection AP by up to 36 points and boosts robotic box‑shelving success by 28%.
By Yintao Ma, Sajjad Pakdamansavoji, Charles Eret, Rui Heng Yang, Xuan Zhao, Yingxue Zhang, Tongtong Cao, Amir Rasouli
The paper introduces a modular perception framework that uses vision‑language models (VLMs) to annotate object‑level regions from a single RGB‑D observation, then grounds these annotations with depth data to build an object‑centric representation. Experiments on 151 tabletop scenes demonstrate that this decomposition maintains strong semantic performance while significantly improving localization and depth estimation compared to direct VLM inference. The resulting representation is integrated into a task‑planning system for robotic manipulation.
By Enrico Saccon, Tommaso Faraci, I\~{n}igo De La Ossa Zarzuelo, Luigi Palopoli, Marco Roveri, Matteo Saveriano
arXiv:2607. 17778v1 Announce Type: cross Abstract: Class-agnostic 3D instance segmentation is critical for robotic systems operating in unknown environments, enabling perception of previously unseen objects for reliable manipulation and navigation.
By Juno Kim, Hye-Jung Yoon, Yesol Park, Byoung-Tak Zhang
Robots operating safely in cluttered everyday environments often need to infer scene geometry from partial observations. Methods that detect objects in 2D and reconstruct them independently struggle i...