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This paper introduces OHRID Retail, a new multimodal dataset capturing human kinematics and muscle activity during shelf-picking tasks with varying levels of robot guidance. By providing raw recordings and reproducible analysis tools, it directly supports research in human-aware robot navigation, sensor fusion, and ergonomic optimization for shared retail environments. The resource addresses a critical gap in open data regarding human-robot interaction dynamics in commercial settings.
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OHRID-Retail: An Open Multimodal Dataset of Human Activity in Retail Environments

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arXiv:2609.19302v1 Announce Type: new Abstract: Open datasets describing human behavior in environments shared with mobile robots remain limited, particularly for retail activities that combine locomotion, reaching, object handling, and robot guided movement. This paper introduces OHRID Retail, an open, human centered multimodal dataset collected from 16 healthy adults performing a simulated shelf picking task under three within participant conditions: no robot, low speed robot guidance, and high speed robot guidance. Each participant completed two trials per condition. Whole body kinematics were recorded using 17 Xsens Awinda inertial sensors and muscle activity was measured at 10 locations using Delsys Trigno surface electromyography sensors. Descriptive analyses demonstrate variation in whole body movement intensity and muscle activation across robot interaction conditions and body locations. OHRID Retail provides openly available raw recordings, processed measures, documentation, and reproducible analysis resources. The dataset can support research in human activity recognition, multimodal sensor fusion, occupational biomechanics, ergonomics, human aware robot navigation, and human robot interaction in retail and related shared environments.

Abstract:Open datasets describing human behavior in environments shared with mobile robots remain limited, particularly for retail activities that combine locomotion, reaching, object handling, and robot guided movement. This paper introduces OHRID Retail, an open, human centered multimodal dataset collected from 16 healthy adults performing a simulated shelf picking task under three within participant conditions: no robot, low speed robot guidance, and high speed robot guidance. Each participant completed two trials per condition. Whole body kinematics were recorded using 17 Xsens Awinda inertial sensors and muscle activity was measured at 10 locations using Delsys Trigno surface electromyography sensors. Descriptive analyses demonstrate variation in whole body movement intensity and muscle activation across robot interaction conditions and body locations. OHRID Retail provides openly available raw recordings, processed measures, documentation, and reproducible analysis resources. The dataset can support research in human activity recognition, multimodal sensor fusion, occupational biomechanics, ergonomics, human aware robot navigation, and human robot interaction in retail and related shared environments.

Robotics (cs.RO); Human-Computer Interaction (cs.HC)

arXiv:2609.19302 [cs.RO]

(or arXiv:2609.19302v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.19302 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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