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: This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers and suggests a method which considers both the navigation and FDI performance.
Abstract: This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers. We suggest a method to determine the optimal sensor configuration which considers both the navigation and FDI performance. Monte Carlo simulations are performed to show the performance of the suggested optimal sensor configuration method.
56 citations
05 Nov 2012
TL;DR: Robustness in feature tracking and hence in visual measurement generation is achieved by IMU aided feature matching and a two-point relative pose estimation method, to remove outliers from the raw feature point matches.
Abstract: Camera tracking system for augmented reality applications that can operate both indoors and outdoors is described. The system uses a monocular camera, a MEMS-type inertial measurement unit (IMU) with 3-axis gyroscopes and accelerometers, and GPS unit to accurately and robustly track the camera motion in 6 degrees of freedom (with correct scale) in arbitrary indoor or outdoor scenes. IMU and camera fusion is performed in a tightly coupled manner by an error-state extended Kalman filter (EKF) such that each visually tracked feature contributes as an individual measurement as opposed to the more traditional approaches where camera pose estimates are first extracted by means of feature tracking and then used as measurement updates in a filter framework. Robustness in feature tracking and hence in visual measurement generation is achieved by IMU aided feature matching and a two-point relative pose estimation method, to remove outliers from the raw feature point matches. Landmark matching to contain long-term drift in orientation via on the fly user generated geo-tiepoint mechanism is described.
56 citations
23 Jun 2013
TL;DR: This paper proposes a novel automatic method to calibrate a smartphone on board a vehicle using its embedded IMU and GPS, based on longitudinal vehicle acceleration, and is the first attempt to estimate the yaw angle of a smartphone relative to a vehicle in every case, even on non-zero slope roads.
Abstract: Nowadays, smartphones are widely used in the world, and generally, they are equipped with many sensors. In this paper we study how powerful the low-cost embedded IMU and GPS could become for Intelligent Vehicles. The information given by accelerometer and gyroscope is useful if the relations between the smartphone reference system, the vehicle reference system and the world reference system are known. Commonly, the magnetometer sensor is used to determine the orientation of the smartphone, but its main drawback is the high influence of electromagnetic interference. In view of this, we propose a novel automatic method to calibrate a smartphone on board a vehicle using its embedded IMU and GPS, based on longitudinal vehicle acceleration. To the best of our knowledge, this is the first attempt to estimate the yaw angle of a smartphone relative to a vehicle in every case, even on non-zero slope roads. Furthermore, in order to decrease the impact of IMU noise, an algorithm based on Kalman Filter and fitting a mixture of Gaussians is introduced. The results show that the system achieves high accuracy, the typical error is 1%, and is immune to electromagnetic interference.
56 citations
Patent•
07 Apr 2003
TL;DR: In this article, a robotic manipulator consisting of at least one joint, each joint having a drive axis, and a microelectromechanical system (MEMS) inertial sensor aligned with the drive axis providing sensing of the relative position of the drive axes is described.
Abstract: The present invention discloses a robotic manipulator, comprising at least one joint, each joint having a drive axis and at least one microelectromechanical system (MEMS) inertial sensor aligned with at least one drive axis providing sensing of a relative position of the drive axis. The robotic manipulator can include an inertial measurement unit (IMU) coupled to the robotic manipulator for determining the end effector position and orientation. A controller can be used, receiving a signal from at least one MEMS inertial sensor and controlling at least one joint drive axis in response to the signal to change the relative position of the joint drive axis. Rate information from MEMS sensors can be integrated to determine the position of their respective drive axes.
56 citations
01 Jan 2010
TL;DR: Using multiple kilometers of data from a lunar rover prototype, it is demonstrated that, in conjunction with a moderate-grade inertial measurement unit, such a sensor can provide an integrated pose stream that is at times more accurate than that achievable by wheel odometry and visibly more desirable for perception purposes than that provided by a high-end GPS-INS system.
Abstract: Positioning is a key task in most field robotics applications but can be very challenging in GPS-denied or high-slip environments. A common tactic in such cases is to position visually, and we present a visual odometry implementa- tion with the unusual reliance on optical mouse sensors to report vehicle velocity. Using multiple kilometers of data from a lunar rover prototype, we demonstrate that, in conjunction with a moderate-grade inertial measurement unit, such a sensor can provide an integrated pose stream that is at times more accurate than that achievable by wheel odometry and visibly more desirable for perception purposes than that provided by a high-end GPS-INS system. A discussion of the sensor's limitations and several drift mitigating strategies attempted are presented.
56 citations