IMU based gesture recognition for mobile robot control using Online Lazy Neighborhood Graph search |
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| P. Kulkarni, B. Illing, B. Gaspers, B. Brüggemann, D. Schulz |
- Abstract:
- In this paper, we present and evaluate a framework for gesture recognition using four wearable IMUs to indirectly control a mobile robot. Six gestures involving different hand and arm motions are defined. A novel algorithm based on Online Lazy Neighborhood Graph (OLNG) search is used to recognize the gestures. We use this algorithm to classify the gestures online and trigger predefined behaviors. Experiments show that the framework is able to correctly detect and classify six different gestures in real-time with an average success rate of 81.6%, while keeping the false positive rate low by design and using only 126 training samples.
- Download:
- IMEKO-TC17-2018-010.pdf
- DOI:
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