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.

3-D position estimation from inertial sensing: Minimizing the error from the process of double integration of accelerations

Abstract: This paper introduces a new approach to 3-D position estimation from acceleration data, i.e., a 3-D motion tracking system having a small size and low-cost magnetic and inertial measurement unit (MIMU) composed by both a digital compass and a gyroscope as interaction technology. A major challenge is to minimize the error caused by the process of double integration of accelerations due to motion (these ones have to be separated from the accelerations due to gravity). Owing to drift error, position estimation cannot be performed with adequate accuracy for periods longer than few seconds. For this reason, we propose a method to detect motion stops and only integrate accelerations in moments of effective hand motion during the demonstration process. The proposed system is validated and evaluated with experiments reporting a common daily life pick-and-place task.

Adaptive Kalman filter for MEMS-IMU based attitude estimation under external acceleration and parsimonious use of gyroscopes

Abstract: This paper considers rigid body attitude estimation from a small inertial/magnetic sensor module containing triaxial gyroscopes, accelerometers, and magnetometers. Precisely, two challenges are addressed. The first one concerns attitude estimation during various dynamic conditions, in which external acceleration occurs. Although external acceleration is one of the main source of loss of performance in attitude estimation methods, this problem has not been sufficiently addressed in the literature. An adaptive algorithm compensating external acceleration from the residual in the accelerometer is proposed. At each step, the covariance matrix associated with the external acceleration is estimated to adaptively tune the filter gain. The second challenge is focused on the energy consumption issue of gyroscopes for long-term battery life of Inertial Measurement Units. We study the way to reduce the gyro measurement acquisition while maintaining acceptable attitude estimation. Through numerical simulations, under external acceleration and parsimonious gyroscope's use, the efficiency of the proposed q-AKF is illustrated.

MEMS SoC: observer-based coplanar gyro-free inertial measurement unit

Abstract: This paper presents a novel design of a coplanar gyro-free inertial measurement unit (IMU) that consists of seven to nine single-axis linear accelerometers, and it can be utilized to perform the six DOF measurements for an object in motion. Unlike other gyro-fee IMUs, this design uses redundant accelerometers and state estimation techniques to facilitate the in situ and mass fabrication for the employed accelerometers. The alignment error from positioning accelerometers onto a measurement unit and the fabrication cost of an IMU can greatly be reduced. The outputs of the proposed design are three linear accelerations and three angular velocities. As compared to other gyro-free IMUs, the proposed design uses less integral operation and thus improves its sensing resolution and drifting problem. The sensing resolution of a gyro-free IMU depends on the sensing resolution of the employed accelerometers as well as the size of the measurement unit. Simulation results indicate that the sensing resolution of the proposed design is 2° s−1 for the angular velocity and 10 μg for the linear acceleration when nine single-axis accelerometers, each with 10 μg sensing resolution, are deployed on a 4 inch diameter disc. Also, thanks to the iterative EKF algorithm, the angle estimation error is within 10−3 deg at 2 s.

Design and implementation of sensor data fusion for an autonomous quadrotor

Abstract: This paper describes the design and integration of the instrumentation and sensor fusion that is used to allow the autonomous flight of a quadrotor. A comercial frame is used, a mathematical model for the quadrotor is developed and its parameters determined from the characterization of the unit. A 9 degrees of freedom Inertial Measurement Unit (IMU) equipped with a barometer is calibrated and added to the platform. Sensor fusion is done by two modified Extended Kalman Filters (EKF): one combining data provided by IMU and the other also including the information provided by GPS. A reliable estimation of the state variables is obtained. Three states representing systematic bias in the accelerometer measurements are also added to the EKF, which improves the inertial estimation of the position. A stable autonomous platform is achieved.

Robot, carriage device, and control method using inertia sensor

Abstract: A robot includes: an arm; a driving source that pivots the arm; an angle sensor that detects a pivot angle and outputs pivot angle information; an inertia sensor that is attached to the arm and outputs inertial force information; a control command generating unit that outputs a control command defining rotational operation of the arm; a control conversion determining unit that determines whether the inertial force information is used when the driving source is controlled; and an arm operation control unit that performs a first control based on the control command, the pivot angle information, and the inertial force information, if the control conversion determining unit determines that the inertial force information should be used, and performs a second control based on the control command and the pivot angle information, if the control conversion determining unit determines that the inertial force information should not be used.