
Open access
Date
2015-01Type
- Journal Article
Abstract
We present 3D ActionSLAM, a stand-alone wearable system that can track people in previously unknown multi-floor environments with sub-room accuracy. ActionSLAM stands for action-based simultaneous localization and mapping: It fuses dead reckoning data from a foot-mounted inertial measurement unit with the recognition of location-related actions to build and update a local landmark map. Simultaneously, this map compensates for position drift errors that accumulate in open-loop tracking by means of a particle filter. To evaluate the system performance, we analyzed 23 tracks with a total walked distance of 6,489 m in buildings with up to three floors. The algorithm robustly (93 % of runs converged) mapped the areas with a mean landmark positioning error of 0.59 m. As ActionSLAM is fully stand-alone and not dependent on external infrastructure, it is well suited for patient tracking in remote health care applications. The algorithm is computationally light-weight and runs in real-time on a Samsung Galaxy S4, enabling immediate location-aware feedback. Finally, we propose visualization techniques to facilitate the interpretation of tracking data acquired with 3D ActionSLAM. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000091534Publication status
publishedExternal links
Journal / series
Personal and Ubiquitous ComputingVolume
Pages / Article No.
Publisher
SpringerSubject
Simultaneous localization and mapping; Indoor tracking; Pedestrian dead reckoning; Location- aware computing; Wearable systemsOrganisational unit
03388 - Tröster, Gerhard (emeritus)
Notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.More
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