arXiv:2508. 02425v2 Announce Type: replace-cross Abstract: In physical human-robot collaboration (pHRC) settings, humans and robots collaborate directly in shared environments.
arXiv:2508. 12435v2 Announce Type: replace-cross Abstract: While gesture recognition using vision or robot skins is an active research area in Human-Robot Collaboration (HRC), this paper explores deep learning methods relying solely on a robot's built-in joint sensors, eliminating the need for external sensors.
arXiv:2606. 24450v1 Announce Type: cross Abstract: Perceiving physical contact is fundamental to dexterous manipulation.
arXiv:2510. 25960v2 Announce Type: replace-cross Abstract: In this paper, we present a framework that uses acoustic side-channel analysis (ASCA) to monitor and verify whether a robot correctly executes its intended commands.
arXiv:2609.25351v1 Announce Type: cross Abstract: We focus on human-robot collaborative transport, a challenging task of broad relevance spanning logistics, manufacturing, and the home, in which a us...
arXiv:2510. 01711v4 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in robot manipulation by leveraging rich representations from pre-trained Vision-Language Models (VLMs).
The paper introduces TaMeSo‑bot, a soft‑wrist robotic system that uses tactile memory to perform robust object insertion tasks. It employs a Masked Tactile Trajectory Transformer (MAT³) to jointly model actions, tactile cues, force‑torque data, and proprioception, learning spatiotemporal representations through masked token prediction. Experiments on peg‑in‑hole tasks show that MAT³ outperforms baselines and adapts well to unseen pegs and conditions.
arXiv:2606. 01950v1 Announce Type: cross Abstract: World models enable intelligent agents to predict the consequences of their actions on the environment.
arXiv:2607. 00530v1 Announce Type: cross Abstract: Improvements in the technical performance of human--robot interaction (HRI) systems do not automatically translate into differences that human users can detect during live interaction.
arXiv:2604.15221v3 Announce Type: replace-cross Abstract: Safe human-robot collaboration (HRC) requires accurate human pose estimation and motion prediction to prevent critical collisions. Existing c...
We focus on human-robot collaborative transport, a challenging task of broad relevance spanning logistics, manufacturing, and the home, in which a user and a robot work together to relocate a large or...
arXiv:2604.14944v3 Announce Type: replace-cross Abstract: We present HRDexDB, a real-world 4D dexterous grasping dataset capturing 3D hand-object interaction trajectories over time across five embodi...
arXiv:2609.12155v1 Announce Type: new Abstract: Understanding person-level bi-manual interactions requires not only detecting hands, but also identifying which two hands belong to the same person and...