SLAC: 3D localization of human based on kinetic human movement capture

This article introduces a method called SLAC (Simultaneous Localization And Capture) to track the spatial location of a human using wearable inertia sensors without additional external assistive global sensing device (e.g., camera, ultrasound, IR, etc.) The method uses multiple wearable inertia sensors to determine the orientation of the body segments and lower limb joint motions. At the same time, based on human kinematics and locomotion phase detection, the spatial position and trajectory of a reference point on the body can be determined. Preliminary experimental study has shown that the position error of SLAC can be controlled stairs within less than 2% error of the total distance travelled for a person to walk around a rectangle on the floor and climb up and down stairs. A benchmark study on the accuracy of SLAC was carried out using the camera-based Motion Analysis® system. The localization data obtained from SLAC tally well with that from the commercial system. The positioning accuracy obtained from SLAC is at least an order of magnitude better than that of GPS. Since the sensors can be worn on the human at any time and any place, this method has no restriction to indoor and outdoor applications and is complimentary to GPS applications.

[1]  Yasuo Kuniyoshi,et al.  Wearable motion capture suit with full-body tactile sensors , 2009, 2009 IEEE International Conference on Robotics and Automation.

[2]  Eric Foxlin,et al.  Pedestrian tracking with shoe-mounted inertial sensors , 2005, IEEE Computer Graphics and Applications.

[3]  Takeshi Kurata,et al.  Personal positioning based on walking locomotion analysis with self-contained sensors and a wearable camera , 2003, The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, 2003. Proceedings..

[4]  H. Dawes,et al.  IMU: inertial sensing of vertical CoM movement. , 2009, Journal of Biomechanics.

[5]  Robert Harle,et al.  Pedestrian localisation for indoor environments , 2008, UbiComp.

[6]  Wojciech Matusik,et al.  Practical motion capture in everyday surroundings , 2007, ACM Trans. Graph..

[7]  Cornie Scheffer,et al.  Benchmarking of a full-body inertial motion capture system for clinical gait analysis , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  Hendrik Johannes Luinge,et al.  Inertial sensing of human movement , 2002 .

[9]  R.G.J. Damgrave,et al.  The Drift of the Xsens Moven Motion Capturing Suit during Common Movements in a Working Environment , 2009 .

[10]  Atsuo Takanishi,et al.  Human-like walking with knee stretched, heel-contact and toe-off motion by a humanoid robot , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  J. Michael McCarthy,et al.  Introduction to theoretical kinematics , 1990 .

[12]  Daniel Roetenberg,et al.  Inertial and magnetic sensing of human motion , 2006 .