Topic
Inertial measurement unit
About: Inertial measurement unit is a research topic. Over the lifetime, 13326 publications have been published within this topic receiving 189083 citations. The topic is also known as: IMU.
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TL;DR: The next generation of satellites will be able to communicate with each other in real time, and the design of the spacecraft will allow for real-time communications between the spacecraft and the Earth.
Abstract: Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.
75 citations
Patent•
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04 May 2010
TL;DR: In this article, a flash LADAR system and method is presented to enable landing, docking, and navigation functions, such as Guidance, Navigation and Control (GNC), Altimetry, Velocimetry and Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and dust penetration.
Abstract: The present invention pertains in general to a single, integrated flash LADAR system and method. The system includes data processing hardware and software, a passive two-dimensional camera, a three-dimensional camera, a light source, and a common optical path. One or more star trackers can also be included. In addition, auxiliary components, such as an inertial measurement unit and a global positioning system receiver can be included. The system can be closely integrated with a critical algorithm suite that operates in multiple modes, in real-time to enable landing, docking, and navigation functions, such as Guidance, Navigation, and Control (GNC), Altimetry, Velocimetry, Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and dust penetration.
75 citations
TL;DR: To systematically analyze exactly how magnetic disturbances affects the attitude and heading estimation for a magnetic and inertial sensor, four major components dealing with magnetic disturbance are reviewed, namely decoupling attitude estimation from magnetic reading, gyro bias estimation, adaptive strategies of compensating magnetic disturbance and sensor fusion algorithms.
Abstract: With the advancements in micro-electromechanical systems (MEMS) technologies, magnetic and inertial sensors are becoming more and more accurate, lightweight, smaller in size as well as low-cost, which in turn boosts their applications in human movement analysis. However, challenges still exist in the field of sensor orientation estimation, where magnetic disturbance represents one of the obstacles limiting their practical application. The objective of this paper is to systematically analyze exactly how magnetic disturbances affects the attitude and heading estimation for a magnetic and inertial sensor. First, we reviewed four major components dealing with magnetic disturbance, namely decoupling attitude estimation from magnetic reading, gyro bias estimation, adaptive strategies of compensating magnetic disturbance and sensor fusion algorithms. We review and analyze the features of existing methods of each component. Second, to understand each component in magnetic disturbance rejection, four representative sensor fusion methods were implemented, including gradient descent algorithms, improved explicit complementary filter, dual-linear Kalman filter and extended Kalman filter. Finally, a new standardized testing procedure has been developed to objectively assess the performance of each method against magnetic disturbance. Based upon the testing results, the strength and weakness of the existing sensor fusion methods were easily examined, and suggestions were presented for selecting a proper sensor fusion algorithm or developing new sensor fusion method.
74 citations
TL;DR: A modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation to have low cost, easy wearability, and high reliability.
Abstract: Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.
74 citations
TL;DR: The algorithms proposed in this paper are capable of providing precise and robust vehicle localization and the lateral localization error is compensated by the point cloud-based lateral localization method proposed inThis paper.
Abstract: Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.
73 citations