Research And Design Of Inertia Motion Capture Front-end Device

Generally, human motion capture system makes up of motion parameter raw data capture system, motion parameter analysis system and human posture matching system. Human motion parameter raw data capture system is very important for a human motion capture system. If we cannot get these raw data, it is impossible to do the following up study of motion capture. This thesis introduces and analyses commercial inertia motion capture systems at present, investigates the structure composition, possible implementation of all parts, and the problems may be encountered while using practically. This thesis makes primary study of motion parameter raw data capture system, designs a front-end device of human motion capture system, including both the hardware and software. We introduce wireless sensor network to solve the restrictions of wired connection, also make a proof of real-time performance of the device and validity of the data captured by the system. This front-end device includes three different kinds of nodes:sensor node, cluster node and sink node. Sensor node gathers acceleration, magnetic density and rotational rate simultaneously, and has the capability of power monitor. Sensor node and cluster node together with sink node compose a wireless sensor network, provides real-time motion data for motion capture system with up to 60 Hz update rate. As for MEMS gyroscope suffers serious random drift noising and low precision, this thesis studies de-noising algorithm for MEMS gyro signals, achieves certain effect and provides some reference for future study.