Inertial and Magnetic Tracking of Limb Segment Orientation For Inserting Humans Into Synthetic Environments
- Тип контента: Научная статья
- Номер документа: 8029
- Название документа: Inertial and Magnetic Tracking of Limb Segment Orientation For Inserting Humans Into Synthetic Environments
- Номер (DOI, IBSN, Патент): Не заполнено
- Изобретатель/автор: Eric Robert Bachmann
- Правопреемник/учебное заведение: NAVAL POSTGRADUATE SCHOOL Monterey, California
- Дата публикации документа: 2000-12-29
- Страна опубликовавшая документ: США
- Язык документа: Английский
- Наименование изделия: Не заполнено
- Источник: Не заполнено
- Вложения: Да
- Аналитик: Глаголева Елена
Current motion tracking technologies fail to provide accurate wide area tracking of multiple users without interference and occlusion problems. These limitations make difficult the construction of a practical and intuitive interface, which allows humans to be inserted into networked virtual environments in a fully immersive manner. Advances in the field of miniature sensors make possible inertial/magnetic tracking of human body limb segment orientation without the limitations of current systems. Due to implementation challenges, inertial/magnetic sensors have not previously been used successfully for full bodymotion capture. This research proposes to overcome these challenges using multi-axis sensors combined with a quaternion-based complementary filter algorithm capable of continuously correcting for drift and following motion through all orientations without singularities. Primarily, this research involves the development of a prototype tracking system to demonstrate the feasibility of hybrid RF/magnetic/inertial motion tracking. Construction of inertial/magnetic (MARG) sensors is completed using off-the-shelf components. Mathematical analysis and computer simulation are used to validate the correctness of the complementary filter algorithm. The implemented human body model utilizes the worldcoordinate reference frame orientation data provided in quaternion form by the complementary filter and orients each limb segment independently. Calibration of the model and the inertial sensors is accomplished using simple but effective algorithms. Physical experiments demonstrate the utility of the proposed system. These experiments involve the tracking of human limbs in real-time using multiple inertial sensors. The motion tracking system produced has an accuracy which is comparable and a latency which is superior to active electro-magnetic sensors. The system is “sourceless” and does not suffer from range restrictions and interference problems. With additional MARG sensor packages, the architecture produced will easily scale to full body tracking. This new technology overcomes the limitations of motion tracking technologies currently vi in use. It will provide wide area tracking of multiple users in virtual environment and augmented reality applications.
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