SIRU development. Volume 1: System development

A complete description of the development and initial evaluation of the Strapdown Inertial Reference Unit (SIRU) system is reported. System development documents the system mechanization with the analytic formulation for fault detection and isolation processing structure; the hardware redundancy design and the individual modularity features; the computational structure and facilities; and the initial subsystem evaluation results

A practical method for implementing an attitude and heading reference system

This paper describes a practical and reliable algorithm for implementing an Attitude and Heading Reference System (AHRS). This kind of system is essential for real time vehicle navigation, guidance and control applications. When low cost sensors are used, efficient and robust algorithms are required for performance to be acceptable. The proposed method is based on an Extended Kalman Filter (EKF) in a direct configuration. In this case, the filter is explicitly derived from both the kinematic and rror models. The selection of this kind of EKF configuration can help in ensuring a tight integration of the method for its use in filter-based localization and mapping systems in autonomous vehicles. Experiments with real data show that the proposed method is able to maintain an accurate and drift-free attitude and heading estimation. An additional result is to show that there is no ostensible reason for preferring that the filter have an indirect configuration over a direct configuration for implementing an AHRS system.Postprint (published version

Robust foot clearance estimation based on the integration of foot-mounted IMU acceleration data

This paper introduces a method for the robust estimation of foot clearance during walking, using a single inertial measurement unit (IMU) placed on the subject's foot. The proposed solution is based on double integration and drift cancellation of foot acceleration signals. The method is insensitive to misalignment of IMU axes with respect to foot axes. Details are provided regarding calibration and signal processing procedures. Experimental validation was performed on 10 healthy subjects under three walking conditions: normal, fast and with obstacles. Foot clearance estimation results were compared to measurements from an optical motion capture system. The mean error between them is significantly less than 15 % under the various walking conditions

Development of a Novel Handheld Device for Active Compensation of Physiological Tremor

In microsurgery, the human hand imposes certain limitations in accurately positioning the tip of a device such as scalpel. Any errors in the motion of the hand make microsurgical procedures difficult and involuntary motions such as hand tremors can make some procedures significantly difficult to perform. This is particularly true in the case of vitreoretinal microsurgery. The most familiar source of involuntary motion is physiological tremor. Real-time compensation of tremor is, therefore, necessary to assist surgeons to precisely position and manipulate the tool-tip to accurately perform a microsurgery. In this thesis, a novel handheld device (AID) is described for compensation of physiological tremor in the hand. MEMS-based accelerometers and gyroscopes have been used for sensing the motion of the hand in six degrees of freedom (DOF). An augmented state complementary Kalman filter is used to calculate 2 DOF orientation. An adaptive filtering algorithm, band-limited Multiple Fourier linear combiner (BMFLC), is used to calculate the tremor component in the hand in real-time. Ionic Polymer Metallic Composites (IPMCs) have been used as actuators for deflecting the tool-tip to compensate for the tremor

Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation

In this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bias errors are modeled and compensated by including them in the filter state vector. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system that describes the process of motion tracking by the IMU is observable, namely it may provide sufficient information for performing the estimation task with bounded estimation errors. The observability conditions are that the magnetic field, perturbed by first-order Gauss-Markov magnetic variations, and the gravity vector are not collinear and that the IMU is subject to some angular motions. Computer simulations and experimental testing are presented to evaluate the algorithm performance, including when the observability conditions are critical