Ubiquitous Robot Control Through Multimodal Motion Capture Using Smartwatch and Smartphone Data
Abstract
Domain fit: AI-adjacent · Paper appears method- or tooling-adjacent to AI workflows with partial ecosystem coverage.
We present an open-source library for seamless robot control through motion capture using smartphones and smartwatches. Our library features three modes: Watch Only Mode, enabling control with a single smartwatch; Upper Arm Mode, offering heightened accuracy by incorporating the smartphone attached to the upper arm; and Pocket Mode, determining body orientation via the smartphone placed in any pocket. These modes are applied in two real-robot tasks, showcasing placement accuracy within 2 cm compared to a gold-standard motion capture system. WearMoCap stands as a suitable alternative to conventional motion capture systems, particularly in environments where ubiquity is essential. The library is available at: www.github.com/wearable-motion-capture.
Results and benchmarks
We present an open-source library for seamless robot control through motion capture using smartphones and smartwatches.
Benchmark evidence is limited
Evidence graph: 2 refs, 1 links.
Utility signals: depth 65/100, grounding 58/100, status medium.
Implementation
No direct implementation yet
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Time to first repro: a few days
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Reproduction readiness
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Hardware requirements
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Validation caveat
Hugging Face artifacts
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Research context
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Citations
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References
Tasks
Smartwatch, Computer science, Human–computer interaction, Motion capture, Control (management), Robot, Smartphone app, Motion control
Methods
None detected
Domains
Motion (physics), Artificial intelligence
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