Abstract This study aimed to develop and deploy a novel motion capture system capable of measuring space suit kinematics in an underwater test environment. The system was built using off-the-shelf, dive-rated hardware and open source software tools. The new system performance was validated by comparing the measurement outcome to a reference motion capture system in a dry-land condition. Measurement errors, defined as the linear distances of the marker position measurements between the developed and reference system, were 1.9 cm root-mean-square error (RMSE) with a 50-percentile error of 1.3 cm and a 95-percentile error of 3.6 cm. Measurement error tended to increase with motion speed. Similarly, the error showed a slight tendency of increasing with the distance from the center of the calibrated capture volume. However, the trend was not clearly identifiable. A second metric of system accuracy performance was calculated by assessing the wand length. The system was deployed underwater and tested for space suit kinematic assessments. Given the speed and range of space suit motions underwater, the measurement error of the developed system underwater was estimated to be approximately 1.39 cm and the wand length estimation error had a RMSE of 0.67 cm with a 50-percentile error of 0.51 cm and a 95-percentile error of 0.92 cm. Overall, the new system showed reliable and acceptably accurate kinematic measurements comparable to a common dry land motion capture system and can provide usable suit performance metrics in a simulated microgravity environment. Relevance to industry An underwater motion capture system was developed using off-the-shelf equipment. The new system was deployed to assess the kinematic mobility of space suits. The system can offer an inexpensive solution where traditional motion capture system may not be applicable.
[1]
Christoph Zinner,et al.
A new approach for identifying phases of the breaststroke wave kick and calculation of feet slip using 3D automatic motion tracking
,
2014
.
[2]
Robert Tibshirani,et al.
An Introduction to the Bootstrap
,
1994
.
[3]
Sudhakar Rajulu,et al.
Comparative Ergonomic Evaluation of Spacesuit and Space Vehicle Design
,
2012
.
[4]
Fabio Bruno,et al.
A Comparative Analysis between Active and Passive Techniques for Underwater 3D Reconstruction of Close-Range Objects
,
2013,
Sensors.
[5]
D. Freedman.
Bootstrapping Regression Models
,
1981
.
[6]
Matthias Wehkamp,et al.
A practical guide to the use of consumer-level digital still cameras for precise stereogrammetric in situ assessments in aquatic environments
,
2014
.
[7]
Robert M. Haralick,et al.
Review and analysis of solutions of the three point perspective pose estimation problem
,
1994,
International Journal of Computer Vision.
[8]
Yohan Dupuis,et al.
A Study of Vicon System Positioning Performance
,
2017,
Sensors.
[9]
Anthony C. Davison,et al.
Bootstrap Methods and Their Application
,
1998
.
[10]
Roger Y. Tsai,et al.
A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses
,
1987,
IEEE J. Robotics Autom..
[11]
Mark Shortis,et al.
Calibration Techniques for Accurate Measurements by Underwater Camera Systems
,
2015,
Sensors.