Collecting Human Motion Data in Large and Occlusion-Prone Environments using Ultra-Wideband Localization

TL;DR

This paper explores using Ultra-Wideband (UWB) localization as a scalable, less intrusive method for collecting human motion data in crowded, occlusion-prone environments, supplementing traditional sensors.

Contribution

It demonstrates the feasibility of UWB technology for human motion capture in complex environments, providing a new scalable alternative to traditional systems.

Findings

UWB can accurately track human motion in occlusion-rich environments.

Multi-modal data collection including UWB, eye-tracking, LiDAR, and radar is feasible.

Over 130 minutes of multi-modal data were recorded in a simulated museum setting.

Abstract

With robots increasingly integrating into human environments, understanding and predicting human motion is essential for safe and efficient interactions. Modern human motion and activity prediction approaches require high quality and quantity of data for training and evaluation, usually collected from motion capture systems, onboard or stationary sensors. Setting up these systems is challenging due to the intricate setup of hardware components, extensive calibration procedures, occlusions, and substantial costs. These constraints make deploying such systems in new and large environments difficult and limit their usability for in-the-wild measurements. In this paper we investigate the possibility to apply the novel Ultra-Wideband (UWB) localization technology as a scalable alternative for human motion capture in crowded and occlusion-prone environments. We include additional sensing modalities such as eye-tracking, onboard robot LiDAR and radar sensors, and record motion capture data as ground truth for evaluation and comparison. The environment imitates a museum setup, with up to four active participants navigating toward random goals in a natural way, and offers more than 130 minutes of multi-modal data. Our investigation provides a step toward scalable and accurate motion data collection beyond vision-based systems, laying a foundation for evaluating sensing modalities like UWB in larger and complex environments like warehouses, airports, or convention centers.