Inertial reference unit

About: Inertial reference unit is a research topic. Over the lifetime, 1306 publications have been published within this topic receiving 22068 citations. The topic is also known as: IRU.

Vision and IMU Data Fusion: Closed-Form Determination of the Absolute Scale, Speed and Attitude

Abstract: This chapter describes an algorithm for determining the speed and the attitude of a sensor assembling constituted by a monocular camera and inertial sensors (three orthogonal accelerometers and three orthogonal gyroscopes). The system moves in a 3D unknown environment. The algorithm inputs are the visual and inertial measurements during a very short time interval. The outputs are: the speed and attitude, the absolute scale and the bias affecting the inertial measurements. The determination of these outputs is obtained by a simple closed form solution which analytically expresses the previous physical quantities in terms of the sensor measurements. This closed form determination allows performing the overall estimation in a very short time interval and without the need of any initialization or prior knowledge. This is a key advantage since allows eliminating the drift on the absolute scale and on the orientation. The performance of the proposed algorithm is evaluated with real experiments.

Toward a free inertial pedestrian navigation reference system

Abstract: As free inertial pedestrian navigation systems with foot mounted inertial mobile unit mature, it becomes feasible to conceive a sufficiently accurate derived solution for assessing other indoor navigation systems and assisting research activities. The design of this reference solution and the remaining challenges are at the heart of this paper. A new filter with a quaternion based state vector exploits signals (acceleration and magnetic field) and motions of opportunity for estimating the navigation solution. Quasi Static Field (QSF) updates, Magnetic Angular Rate Updates (MARU) and Angular Gradient Update (AGU) are frequently applied for mitigating the low-cost inertial sensors errors. Experimental tests performed using a post-processed GPS differential solution as reference show an average accuracy of 1.2 m over 500 m walking path: 0.5 %. Discussions about the data acquisition protocol for meeting a 1 meter horizontal accuracy within two standard deviations of the mean (95.45%) is conducted.

Micro-IMU based Wireless Body Sensor Network

Abstract: This paper introduces the new design of a Micro Inertial Measurement Unit (μ-IMU)-based sensor mote for wireless body sensor network (BSN). The μ-IMU unit consists of a three-axis accelerometer, a three-axis gyroscope MPU6050, and a three-axis electronic compass AK8975. The MCU uses a CC2530 which integrates an 8051 core and 2.4GHz RF. The hardware design and Z-Stack-based software architecture of the sensor mote are discussed in details. A MATLAB program is used to collect experimental data for verification. This system shows several advantages in high integration, compact volume, and accurate sensing capability, which is critical for wearable inertial measurement and body capture.

Kinematic inertial sensor

Abstract: A kinematic inertial sensor is provided for measuring angular velocity and position relative to inertial space about one or more measurement axes. The kinematic inertial sensor includes an angular rate sensor having a ring of conducting fluid contained in a housing, a set of gimbals for supporting the angular rate sensor, signal generating means, torque applying means, angle measuring means, resolver means, component processing means, and signal applying means.

6 DOF Motion Analysis Using Inertial Sensors

Abstract: The use of miniature inertial sensors has become a common practice in ambulatory motion analysis. For accurate and drift free orientation estimation several methods have been reported combining the signals from 3D gyroscopes, accelerometers and magnetometers. Accelerometers are used to determine the direction of the local vertical by sensing acceleration due to gravity. Magnetic sensors provide stability in the horizontal plane by sensing the direction of the earth magnetic field like a compass. Data from these complementary sensors can be used to eliminate drift by continuous correction of the orientation obtained by integrating rate sensor data [1].