Wearable motion capture suit with full-body tactile sensors

Authors:
Yuki Fujimori;Yoshiyuki Ohmura;Tatsuya Harada;Yasuo Kuniyoshi
Affiliations:
Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan;Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan;Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan;Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

Citing 5
Cited 0

Retargetting motion to new characters

Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Motion Tracking: No Silver Bullet, but a Respectable Arsenal

IEEE Computer Graphics and Applications
Unsupervised Analysis of Human Gestures

PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Markerless monocular motion capture using image features and physical constraints

CGI '05 Proceedings of the Computer Graphics International 2005
Practical motion capture in everyday surroundings

ACM SIGGRAPH 2007 papers

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a system for capturing human movement and tactile data and methods for analyzing this data. We cannot fully capture the essence of motion without tactile information, and sometimes the lack of such information causes critical problems. To achieve a better understanding of motion behavior, we developed a wearable motion capture suit with full-body tactile sensors. We also developed a motion sensor which can estimate its orientation with its inner CPU. We also built a tactile sensor module which can fit many kinds of body shapes. With this system, we can measure a user's movement and tactile information simultaneously. By integrating tactile data with motion data, we can achieve many kinds of meaningful insights. We demonstrate the effectiveness of this system with experiments. We captured two motions: stretching after sitting on a chair and laying down on a bed. By recognizing the contact point from the tactile data and fitting it into the environment, we were able to estimate the motion trajectories.