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Fraunhofer IPK

Academic institutioneurope · de
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Research library4linked papers
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Selected work

Representative Papers

GraspIT: A Dataset Bridging the Sim-to-Real gap and back for Validated Grasping SE(3) Pose Generation

Jul 07, 2026

This work addresses the limitations of existing grasp datasets, which lack physically validated continuous quality annotations and simulation-to-reality alignment, thereby hindering robust grasping on novel objects. The authors construct tabletop scenes in NVIDIA Isaac Sim and generate grasps for the Franka Panda manipulator, evaluating each with trajectory feasibility and a continuous quality score derived from a four-stage physical slip test and force-closure analysis. A Real↔Sim closed-loop framework enables bidirectional domain alignment. The resulting dataset is the first to jointly provide physically validated continuous grasp quality labels, hard negative samples with difficulty tiers, and high-fidelity 6-DoF pose annotations. It comprises 316,000 RGB-D frames spanning 1,035 simulated and 100 real-world scenes, along with 2.3 million candidate grasps—83% high-quality and 17% hard negatives—and includes a fully open-sourced toolchain.

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A Vision Based System for Guided and Collaborative Reconstruction of Fragmented Documents

Jul 03, 2026

This study addresses the challenge of high-precision, non-invasive reconstruction of fragile paper fragments in cultural heritage by proposing a human–robot collaborative real-time reconstruction system. The system integrates a vacuum-based collaborative robot with the detector-free feature matching algorithm SE2-LoFTR, enabling vision-guided fragment alignment and assembly in either manual or fully automatic modes. It innovatively combines AI-driven analysis—leveraging image segmentation and local feature matching—with a safe vacuum gripper mechanism and high-accuracy robotic control. Experimental results demonstrate a repeatability positioning accuracy of 0.57 mm on fragments as small as 8 cm² and confirm the superior robustness of SE2-LoFTR under conditions involving rotation, scaling, and partial damage.

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Recent publications

Latest Papers

GraspIT: A Dataset Bridging the Sim-to-Real gap and back for Validated Grasping SE(3) Pose Generation

Jul 07, 2026

This work addresses the limitations of existing grasp datasets, which lack physically validated continuous quality annotations and simulation-to-reality alignment, thereby hindering robust grasping on novel objects. The authors construct tabletop scenes in NVIDIA Isaac Sim and generate grasps for the Franka Panda manipulator, evaluating each with trajectory feasibility and a continuous quality score derived from a four-stage physical slip test and force-closure analysis. A Real↔Sim closed-loop framework enables bidirectional domain alignment. The resulting dataset is the first to jointly provide physically validated continuous grasp quality labels, hard negative samples with difficulty tiers, and high-fidelity 6-DoF pose annotations. It comprises 316,000 RGB-D frames spanning 1,035 simulated and 100 real-world scenes, along with 2.3 million candidate grasps—83% high-quality and 17% hard negatives—and includes a fully open-sourced toolchain.

0 citationsRead paper

A Vision Based System for Guided and Collaborative Reconstruction of Fragmented Documents

Jul 03, 2026

This study addresses the challenge of high-precision, non-invasive reconstruction of fragile paper fragments in cultural heritage by proposing a human–robot collaborative real-time reconstruction system. The system integrates a vacuum-based collaborative robot with the detector-free feature matching algorithm SE2-LoFTR, enabling vision-guided fragment alignment and assembly in either manual or fully automatic modes. It innovatively combines AI-driven analysis—leveraging image segmentation and local feature matching—with a safe vacuum gripper mechanism and high-accuracy robotic control. Experimental results demonstrate a repeatability positioning accuracy of 0.57 mm on fragments as small as 8 cm² and confirm the superior robustness of SE2-LoFTR under conditions involving rotation, scaling, and partial damage.

0 citationsRead paper