Ubiquitous Robot Control Through Multimodal Motion Capture Using Smartwatch and Smartphone Data
Fabian C Weigend, Neelesh Kumar, Oya Aran, Heni Ben Amor

TL;DR
This paper introduces WearMoCap, an open-source library enabling robot control through multimodal motion capture using smartphones and smartwatches, achieving high accuracy in real-robot tasks and offering a portable alternative to traditional systems.
Contribution
The paper presents a novel open-source library that combines smartwatch and smartphone data for seamless robot control in various modes, enhancing accessibility and accuracy.
Findings
Placement accuracy within 2 cm of standard motion capture
Effective in three different control modes
Suitable for environments requiring ubiquitous motion capture
Abstract
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobotics and Automated Systems · Human Motion and Animation · Social Robot Interaction and HRI
