IMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly

We introduce IMPACT, a synchronized five-view RGB-D dataset for deployment-oriented industrial procedural understanding, built around real assembly and disassembly of a commercial angle grinder with professional-grade tools. To our knowledge, IMPACT is the first real industrial assembly benchmark that jointly provides synchronized ego-exo RGB-D capture, decoupled bimanual annotation, compliance-aware state tracking, and explicit anomaly--recovery supervision within a single real industrial workflow. It comprises 112 trials from 13 participants totaling 39.5 hours, with multi-route execution governed by a partial-order prerequisite graph, a six-category anomaly taxonomy, and operator cognitive load measured via NASA-TLX. The annotation hierarchy links hand-specific atomic actions to coarse procedural steps, component assembly states, and per-hand compliance phases, with synchronized null spans across views to decouple perceptual limitations from algorithmic failure. Systematic baselines reveal fundamental limitations that remain invisible to single-task benchmarks, particularly under realistic deployment conditions that involve incomplete observations, flexible execution paths, and corrective behavior. The full dataset, annotations, and evaluation code are available at https://github.com/Kratos-Wen/IMPACT.

A Multi-View 3D Telepresence System for XR Robot Teleoperation

Robot teleoperation is critical for applications such as remote maintenance, fleet robotics, search and rescue, and data collection for robot learning. Effective teleoperation requires intuitive 3D visualization with reliable depth cues, which conventional screen-based interfaces often fail to provide. We introduce a multi-view VR telepresence system that (1) fuses geometry from three cameras to produce GPU-accelerated point-cloud rendering on standalone VR hardware, and (2) integrates a wrist-mounted RGB stream to provide high-resolution local detail where point-cloud accuracy is limited. Our pipeline supports real-time rendering of approximately 75k points on the Meta Quest 3. A within-subject study was conducted with 31 participants to compare our system to other visualisation modalities, such as RGB streams, a projection of stereo-vision directly in the VR device and point clouds without providing additional RGB information. Across three different teleoperated manipulation tasks, we measured task success, completion time, perceived workload, and usability. Our system achieved the best overall performance, while the Point Cloud modality without RGB also outperforming the RGB streams and OpenTeleVision. These results show that combining global 3D structure with localized high-resolution detail substantially improves telepresence for manipulation and provides a strong foundation for next-generation robot teleoperation systems.