DEVELOPMENT OF HUMAN INERTIAL MOTION CAPTURE SYSTEM

Abstract

This paper presents the full cycle of development of inertial motion capture system: from the selection of sensors, selection of the orientation estimation algorithm of the received data and system movement visualization. The paper considers the existing methods of motion capture using various physical principles of work. Inertial motion capture systems are used in the field of biomechanics increasingly. It is done the analysis of existing inertial motion capture systems in paper. There are several leading market manufacturers of inertial motion capture systems: Xsense, InertialLab, APDM. Comparative characteristics of these systems are given. It is proposed to use own inertial motion capture system (IMCS) as an alternative for expensive industrial designs.The study gives the concept of the developed system. The presented prototype of IMCS consists of autonomous AHRS-modules, base wireless receiver, subsystem of data collection and animation reproduction program. Each of the autonomous AHRS has its own power supply, sensors (IMU), microcontroller with firmware and radio transmitter. AHRS-module uses the ATmega328p microcontroller as calculation core. IMU (Inertial measurement unit) was created by combining on the same board the following sensors: gyro ITG3205 (InvenSense), accelerometer ADXL345L (AnalogDevices) and magnetometer HMC5883L (Honeywell). The firmware functional phases are described in paper. The first phase of the microcontroller firmware is reading data from sensors. After collecting the necessary information, the microcontroller program passes into the phase of the orientation estimation using the AHRS algorithm. The third firmware phase is the data packet preparation and its transmission to the receiver. In paper sensors’ calibration methods are described, the precision characteristics of AHRS-module are given. The developed IMCS has small dimensions of IMUs. They are autonomous and use wireless communication technology for data transfer.As AHRS algorithm of orientation estimation system uses complementary Bachman filter. It reduces the computational load on the microcontroller. Developed system has own software for object movement visualization. NI LabVIEW programming environment is used to display skeleton kinematics through data collected from AHRS modules. Shown approach uses method proposed by Denavit and Hartenberg to describe kinematic chain movement. It is used so called D-H parameters to get the equation of kinematic chain motion conversion. The developed IMCS can be configured flexibly for various kinds of tasks.