Measurement of human body motion has a myriad of applications ranging from gaming, rehabilitation, animation, virtual reality, sports science and surveillance. Existing methods of motion tracking include visual, mechanical, magnetic and inertial tracking. Visual methods require line of sight and suffer from the notorious occlusion problem. For the existing mechanical or inertial tracking methods, they have cumbersome wirings which hinder the natural movements. In this thesis, a wearable wireless sensor network using inertial/ magnetic sensors is developed to overcome the limitations of these existing methods. Using tri-axial accelerometer as the sole sensor will lead to singularity when the heading axis is vertical, restricting measurement of orientation to half a vertical plane. A new factorized quaternion approach is proposed in this research to overcome this deficiency with consideration of anatomical and sensor constraints. Different from the conventional approach based on single angle-axis quaternion, the proposed approach factorizes the quaternion into two principal axis quaternions corresponding to two equivalent arm motions. This allows for the implementation of anatomical arm constraints that match the range of arm motion and reduces the ambiguity in solutions. In addition, the singularities arising from the use of tri-axial accelerometers can be detected and resolved for a transient state. A novel algorithm based on elevation and heading angles is also proposed to determine the orientation of a sensor node equipped with tri-axial accelerometer, gyroscope and magnetometer. Compared to Euler angles, the fixed elevation and heading angles are independent on the temporal order of rotations. In addition, the fixed elevation and heading angles are observable and thus more intuitively visualized.
In many applications, it is desired to monitor the human body motion to provide useful information for applications such as rehabilitation, virtual reality, sports science etc. Most existing inertial/magnetic systems used for body motion tracking today come with wiring which restrains the natural movement. In this paper, a wearable wireless sensor network using accelerometers has been developed for monitoring the human motion. The wireless feature of our system allows for unrestrained movements and improves the usability of the system. Moreover, the use of lightweight sensor nodes makes it easy for attachment to the limbs and poses little hindrance to natural movements. The developed system is also portable and low in cost compared to sophisticated visual tracking systems utilizing multiple cameras. The low power consumption of the sensor nodes also makes it suitable for long term monitoring. A prototype has been developed and experimental results show that the system has reasonable performance.
The objective of the paper is to understand, characterize and enhance the achievable performance of the system of a state-of-the-art marine observation device, the Oceanserver IVER2 Autonomous Underwater Vehicle(AUV), in the Singapore coastal zone and with regard to accurate sampling of oceanographic properties. This paper discusses modifications made to the AUV, in order to make it useful for experiments in this region, which includes shallow water, strong currents, poor visibility, heavy traffic and a poor acoustic environment. These factors strongly influence the choice of navigation method and the system architecture which will enable the AUV to obtain accurate geo-referenced oceanographic properties, and to ensure its safe operation. Our science experiments usually involve sampling at various areas around the coast of Singapore within the same day; this calls for consistent positioning methods that allow ease in deploying and retrieving related equipment.This paper illustrates the use of ultra-short baseline (USBL) tracking system and ranges from an acoustic modem fused by a particle filter to aid the dead reckoning algorithm of the IVER2. The performance of the modified system is shown through simulations and field experiments.
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