AdHocProx: Sensing Mobile, Ad-Hoc Collaborative Device Formations using Dual Ultra-Wideband Radios

要旨

We present AdHocProx, a system that uses device-relative, inside-out sensing to augment co-located collaboration across multiple devices, without recourse to externally-anchored beacons -- or even reliance on WiFi connectivity. AdHocProx achives this via sensors including dual ultra-wideband (UWB) radios for sensing distance and angle to other devices in dynamic, ad-hoc arrangements; plus capacitive grip to determine where the user's hands hold the device, and to partially correct for the resulting UWB signal attenuation. All spatial sensing and communication takes place via the side-channel capability of the UWB radios, suitable for small-group collaboration across up to four devices (eight UWB radios). Together, these sensors detect proximity and natural, socially meaningful device movements to enable contextual interaction techniques. We find that AdHocProx can obtain 95% accuracy recognizing various ad-hoc device arrangements in an offline evaluation, with participants particularly appreciative of interaction techniques that automatically leverage proximity-awareness and relative orientation amongst multiple devices.

著者
Richard Li
University of Washington, Seattle, Washington, United States
Teddy Seyed
Microsoft Research, Redmond, Washington, United States
Nicolai Marquardt
University College London, London, United Kingdom
Eyal Ofek
Microsoft Research, Redmond, Washington, United States
Steve Hodges
Microsoft Research, Cambridge, United Kingdom
Mike Sinclair
Microsoft, Redmond, Washington, United States
Hugo Romat
Microsoft, Seattle, Washington, United States
Michel Pahud
Microsoft Research, Redmond, Washington, United States
Jatin Sharma
Microsoft Research, Redmond, Washington, United States
William A.S.. Buxton
Microsoft Research, Redmond, Washington, United States
Ken Hinckley
Microsoft Research, Redmond, Washington, United States
Nathalie Riche
Microsoft Research, Redmond, Washington, United States
論文URL

https://doi.org/10.1145/3544548.3581300

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Sensor Integration

Hall G1
6 件の発表
2023-04-27 18:00:00
2023-04-27 19:30:00