About: Gyroscope is a(n) research topic. Over the lifetime, 17467 publication(s) have been published within this topic receiving 159884 citation(s). The topic is also known as: gyroscopes.
01 Dec 1998-
TL;DR: Inertial sensors have seen a steady improvement in their performance, and today, microaccelerometers can resolve accelerations in the micro-g range, while the performance of gyroscopes has improved by a factor of 10/spl times/ every two years during the past eight years.
Abstract: This paper presents a review of silicon micromachined accelerometers and gyroscopes. Following a brief introduction to their operating principles and specifications, various device structures, fabrication, technologies, device designs, packaging, and interface electronics issues, along with the present status in the commercialization of micromachined inertial sensors, are discussed. Inertial sensors have seen a steady improvement in their performance, and today, microaccelerometers can resolve accelerations in the micro-g range, while the performance of gyroscopes has improved by a factor of 10/spl times/ every two years during the past eight years. This impressive drive to higher performance, lower cost, greater functionality, higher levels of integration, and higher volume will continue as new fabrication, circuit, and packaging techniques are developed to meet the ever increasing demand for inertial sensors.
12 Aug 2011-
TL;DR: This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications, applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity sensor arrays that also include tri- axis magnetometers.
Abstract: This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications. It is applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity (MARG) sensor arrays that also include tri-axis magnetometers. The MARG implementation incorporates magnetic distortion compensation. The algorithm uses a quaternion representation, allowing accelerometer and magnetometer data to be used in an analytically derived and optimised gradient descent algorithm to compute the direction of the gyroscope measurement error as a quaternion derivative. Performance has been evaluated empirically using a commercially available orientation sensor and reference measurements of orientation obtained using an optical measurement system. Performance was also benchmarked against the propriety Kalman-based algorithm of orientation sensor. Results indicate the algorithm achieves levels of accuracy matching that of the Kalman based algorithm; < 0.8° static RMS error, < 1.7° dynamic RMS error. The implications of the low computational load and ability to operate at small sampling rates significantly reduces the hardware and power necessary for wearable inertial movement tracking, enabling the creation of lightweight, inexpensive systems capable of functioning for extended periods of time.
01 Jan 2007-
TL;DR: This work introduces inertial navigation, focusing on strapdown systems based on MEMS devices, and concludes that whilst MEMS IMU technology is rapidly improving, it is not yet possible to build a MEMS based INS which gives sub-meter position accuracy for more than one minute of operation.
Abstract: Until recently the weight and size of inertial sensors has prohibited their use in domains such as human motion capture. Recent improvements in the performance of small and lightweight micromachined electromechanical systems (MEMS) inertial sensors have made the application of inertial techniques to such problems possible. This has resulted in an increased interest in the topic of inertial navigation, however current introductions to the subject fail to sufficiently describe the error characteristics of inertial systems. We introduce inertial navigation, focusing on strapdown systems based on MEMS devices. A combination of measurement and simulation is used to explore the error characteristics of such systems. For a simple inertial navigation system (INS) based on the Xsens Mtx inertial measurement unit (IMU), we show that the average error in position grows to over 150 m after 60 seconds of operation. The propagation of orientation errors caused by noise perturbing gyroscope signals is identified as the critical cause of such drift. By simulation we examine the significance of individual noise processes perturbing the gyroscope signals, identifying white noise as the process which contributes most to the overall drift of the system. Sensor fusion and domain specific constraints can be used to reduce drift in INSs. For an example INS we show that sensor fusion using magnetometers can reduce the average error in position obtained by the system after 60 seconds from over 150 m to around 5 m. We conclude that whilst MEMS IMU technology is rapidly improving, it is not yet possible to build a MEMS based INS which gives sub-meter position accuracy for more than one minute of operation.
01 Jun 1995-
TL;DR: A low-cost solid-state inertial navigation system for mobile robotics applications is described and error models for the inertial sensors are generated and included in an extended Kalman filter for estimating the position and orientation of a moving robot vehicle.
Abstract: A low-cost solid-state inertial navigation system (INS) for mobile robotics applications is described. Error models for the inertial sensors are generated and included in an extended Kalman filter (EKF) for estimating the position and orientation of a moving robot vehicle. Two different solid-state gyroscopes have been evaluated for estimating the orientation of the robot. Performance of the gyroscopes with error models is compared to the performance when the error models are excluded from the system. Similar error models have been developed for each axis of a solid-state triaxial accelerometer and for a conducting-bubble tilt sensor which may also be used as a low-cost accelerometer. An integrated inertial platform consisting of three gyroscopes, a triaxial accelerometer and two tilt sensors is described. >
01 Apr 2002-Journal of Biomechanics
Abstract: A general-purpose system to obtain the kinematics of gait in the sagittal plane based on body-mounted sensors was developed. It consisted of four uniaxial seismic accelerometers and one rate gyroscope per body segment. Tests were done with 10 young healthy volunteers, walking at five different speeds on a treadmill. In order to study the system's accuracy, measurements were made with an optic, passive-marker system and the body-mounted system, simultaneously. In all the comparison cases, the curves obtained from the two systems were very close, showing root mean square errors representing <7% full range in 75% of the cases (overall mean 6.64%, standard deviation 4.13%) and high coefficients of multiple correlation in 100% of cases (overall mean 0.9812, standard deviation 0.02). Calibration of the body-mounted system is done against gravity. The body-mounted sensors do not hinder natural movement. The calculation algorithms are computationally demanding and only are applicable off-line. The body-mounted sensors are accurate, inexpensive and portable and allow long-term recordings in clinical, sport and ergonomics settings