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arXiv · 2601.11535

Augmented Assembly: Object Recognition and Hand Tracking for Adaptive Assembly Instructions in Augmented Reality

Alexander Htet Kyaw·Haotian Ma·Sasa Zivkovic·Jenny Sabin
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Abstract

Recent advances in augmented reality (AR) have enabled interactive systems that assist users in physical assembly tasks. In this paper, we present an AR-assisted assembly workflow that leverages object recognition and hand tracking to (1) identify custom components, (2) display step-by-step instructions, (3) detect assembly deviations, and (4) dynamically update the instructions based on users' hands-on interactions with physical parts. Using object recognition, the system detects and localizes components in real time to create a digital twin of the workspace. For each assembly step, it overlays bounding boxes in AR to indicate both the current position and the target placement of relevant components, while hand-tracking data verifies whether the user interacts with the correct part. Rather than enforcing a fixed sequence, the system highlights potential assembly errors and interprets user deviations as opportunities for iteration and creative exploration. A case study with LEGO blocks and custom 3D-printed components demonstrates how the system links digital instructions to physical assembly, eliminating the need for manual searching, sorting, or labeling of parts.

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Alexander Htet Kyaw, Haotian Ma, Sasa Zivkovic, Jenny Sabin. 2025-11-22. Augmented Assembly: Object Recognition and Hand Tracking for Adaptive Assembly Instructions in Augmented Reality. https://arxiv.org/abs/2601.11535

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