Showing papers on "Inertial measurement unit published in 2003"

Vision and inertial sensor cooperation using gravity as a vertical reference

Abstract: This paper explores the combination of inertial sensor data with vision. Visual and inertial sensing are two sensory modalities that can be explored to give robust solutions on image segmentation and recovery of 3D structure from images, increasing the capabilities of autonomous robots and enlarging the application potential of vision systems. In biological systems, the information provided by the vestibular system is fused at a very early processing stage with vision, playing a key role on the execution of visual movements such as gaze holding and tracking, and the visual cues aid the spatial orientation and body equilibrium. In this paper, we set a framework for using inertial sensor data in vision systems, and describe some results obtained. The unit sphere projection camera model is used, providing a simple model for inertial data integration. Using the vertical reference provided by the inertial sensors, the image horizon line can be determined. Using just one vanishing point and the vertical, we can recover the camera's focal distance and provide an external bearing for the system's navigation frame of reference. Knowing the geometry of a stereo rig and its pose from the inertial sensors, the collineations of level planes can be recovered, providing enough restrictions to segment and reconstruct vertical features and leveled planar patches.

Real-time integration of a tactical-grade IMU and GPS for high-accuracy positioning and navigation

Abstract: The integration of the Global Positioning System (GPS) and Inertial Navigation Systems (INSs) is often used to provide accurate positioning and navigation information. For applications requiring the highest accuracy, the quality of the inertial sensors required is usually assumed to be very high. This dissertation investigates the integration of GPS with a tactical-grade Inertial Measurement Unit (IMU) for centimetre-level navigation in real-time. Different GPS/INS integration strategies are investigated to assess their relative performance in terms of position and velocity accuracy during partial and complete data outages, carrier phase ambiguity resolution after such data outages, and the overall statistical reliability of the system. In terms of statistical reliability, the traditional equations used in dynamic systems are redeveloped in light of some practical considerations, including centralized and decentralized filter architectures, and sequential versus simultaneous measurement updating. Results show that the integrated solution outperforms the GPS-only approach in all areas. The difference between loose and tight integration strategies was most significant for ambiguity resolution and system reliability. The integrated solution is capable of providing decimetre-level accuracy or better for durations of about five or ten seconds when a complete or partial GPS outage is simulated. This level of accuracy, extended over longer time intervals, is shown to reduce the time required to resolve the L1 ambiguities by an average of about 50% or more for data outages as long as 30 seconds when using a tight integration strategy. More importantly, the reliability of the ambiguity resolution process is improved with the integrated

Pose estimation using line-based dynamic vision and inertial sensors

Abstract: An observer problem from a computer vision application is studied. Rigid body pose estimation using inertial sensors and a monocular camera is considered and it is shown how rotation estimation can be decoupled from position estimation. Orientation estimation is formulated as an observer problem with implicit output where the states evolve on SO(3). A careful observability study reveals interesting group theoretic structures tied to the underlying system structure. A locally convergent observer where the states evolve on SO (3) is proposed and numerical estimates of the domain of attraction is given. Further, it is shown that, given convergent orientation estimates, position estimation can be formulated as a linear implicit output problem. From an applications perspective, it is outlined how delayed low bandwidth visual observations and high bandwidth rate gyro measurements can provide high bandwidth estimates. This is consistent with real-time constraints due to the complementary characteristics of the sensors which are fused in a multirate way.

Airborne simultaneous localisation and map building

Abstract: This paper presents results of the application of simultaneous localisation and map building (SLAM) for an uninhabited aerial vehicle (UAV). Single vision camera and inertial measurement unit (IMU) are installed in a UAV platform. The data taken from a flight test is used to run the SLAM algorithm. Results show that both the map and the vehicle uncertainty are corrected even though the model of the system and observation are highly non-linear. The results, however, also indicate that further work of observability and the relationship between vehicle model drift and the number and the location of landmarks need to be further analysed given the highly dynamic nature of the system.

Personal position measurement using dead reckoning

Abstract: This paper compares position measurement techniquesusing dead reckoning. We are seeking to find a techniquewhich is suitable for use by pedestrians, and have compareda number of sensors that can be used to achieve a robustand accurate dead reckoning system. All our techniquesare step based. To measure steps we have compared the useof pedometers and accelerometers. To determine headingwe have compared two and three dimensional compassesand a rate gyroscope. Finally we have performed four casestudies based on real applications with standard deviationmeasured at 2.2m for a short test and 19.9m for an extendedtest. These errors can be reduced by using more computationallyexpensive filtering operations.

Real-Time Navigation, Guidance, and Control of a UAV Using Low-Cost Sensors.

Abstract: Applying low-cost sensors for the Guidance, Navigation and Control (GNC) of an autonomous Uninhibited Aerial Vehicle (UAV) is an extremely challenging area. This paper presents the real-time results of applying a low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) receiver for the GNC. The INS/GPS navigation loop provides continuous and reliable navigation solutions to the guidance and flight control loop for autonomous flight. With additional air data and engine thrust data, the guidance loop computes the guidance demands to follow way-point scenarios. The flight control loop generates actuator signals for the control surfaces and thrust vector. The whole GNC algorithm was implemented within an embedded flight control computer. The real-time flight test results show that the vehicle can perform the autonomous flight reliably even under high maneuvering scenarios.

Performance Analysis and Architectures for INS-Aided GPS Tracking Loops

Abstract: GPS and inertial sensors have complementary characteristics, which have been exploited in the design of integrated GPS-inertial navigation and guidance systems. Traditionally, most hybrid GPS-inertial systems have been mechanized by combining the information from GPS and an Inertial Navigation System using either loose integration (i.e., integration at the position, velocity and/or attitude level) or tight integration (integration at the pseudorange, Doppler, or carrier phase level). Such integration schemes provide users with limited immunity against momentary GPS outages and also allow detection of certain classes of GPS signal failures. A third scheme of integration can be used, in which the inertial sensors are used to aid the GPS phase frequency and code tracking loops directly. In this paper, this level of coupling is referred to as ultra-tight integration, and it offers potential improvements to GPS performance, such as higher phase-tracking bandwidth, and more resistance to radio frequency interference or multipath noise. In this paper we propose a simple architecture for GPS-inertial systems with ultra-tight integration and present the results of some trade studies and simulations quantifying the performance of such systems. Performances of the ultra-tight GPS-inertial system are evaluated using a simulation tool developed specifically for this study. The metrics used for the evaluation are allowable reduction in the carrier tracking loop-filter bandwidth for improved signal-to-noise ratio, and robustness against carrier-phase cycle-slips. The sensitivity of these metrics to inertial sensor quality and GPS receiver clock noise is discussed and quantified. These studies show that an ultra-tightly coupled system using low cost/performance inertial sensors and a typical temperature-compensated crystal oscillator can function with a carrier tracking loop-filter bandwidth as low as 3Hz. This structure shows a 14dB improvement in phasenoise suppression when compared to a traditional 15Hz loop filter, and comparable carrier-phase tracking bandwidth to that of the inertial sensors (>30Hz).

Design of all-accelerometer inertial measurement unit for tremor sensing in hand-held microsurgical instrument

Abstract: We present the design of an all-accelerometer inertial measurement unit (IMU). The IMU forms part of an intelligent hand-held microsurgical instrument that senses its own motion, distinguishes between hand tremor and intended motion, and compensates in real-time the erroneous motion. The new IMU design consists of three miniature dual-axis accelerometers, two of which are housed in a sensor suite at the distal end of the instrument handle, and one located at the proximal end close to the instrument tip. By taking the difference between the accelerometer readings, we decouple the inertial and gravitational accelerations from the rotation-induced (centripetal and tangential) accelerations, hence simplifies the kinematic computation of angular motions. We have shown that the error variance of the Euler orientation parameters /spl theta//sub x/, /spl theta//sub y/ and /spl theta//sub z/ is inversely proportional to the square of the distance between the three sensor locations. Comparing with a conventional three gyros and three accelerometers IMU, the proposed design reduces the standard deviation of the estimates of translational displacements by 29.3% in each principal axis and those of the Euler orientation parameters /spl theta//sub x/, /spl theta//sub y/ and /spl theta//sub z/ by 99.1%, 99.1% and 92.8% respectively.

Low-cost flight control system for a small autonomous helicopter

Abstract: In this paper we describe a low-cost flight control system for a small (60 class) helicopter which is part of a larger project to develop an autonomous flying vehicle. Our approach differs from that of others in not using an expensive inertial/GPS sensing system. The primary sensors for vehicle stabilization are a low-cost inertial sensor and a pair of CMOS cameras. We describe the architecture of our flight control system, the inertial and visual sensing subsystems and present some flight control results.

Indoor Positioning System Using Accelerometry and High Accuracy Heading Sensors

Abstract: The current GPS signal structure and signal power levels are barely sufficient for indoor applications. Recent developments in high sensitivity receiver technology are promising for indoor positioning inside light structures such as wooden frame houses but generally not for concrete high rise buildings. Errors due to multipath and noise associated with weak indoor signals limit the accuracy and availability of GNSS in difficult indoor environments. An alternate approach makes use of inertial technologies. However, the use of a strapdown inertial navigation system (INS) system and its traditional mechanization as a personal indoor positioning system is rather unrealistic due to the rapidly growing positioning errors caused by gyro drifts. Even a high performance INS will cause hundreds of metres of positioning error in 30 minutes without GPS updates. The majority of previously proposed personal positioning systems utilize the Pedestrian Dead Reckoning (PDR) approach. These systems use accelerometers for step detection and step length estimation and magnetic compasses or low cost gyros for heading determination. In such systems, the error sources are the step length estimation error and the heading error. Assuming no heading error, the positioning error is directly proportional to the number of steps and, thus, to the distance traveled. However, the critical component of these systems is heading. Indoor, apart from measuring the Earth's magnetic field, magnetic sensors will be subject to other local electromagnetic fields. Over time, low cost gyros will drift in a significant and unpredictable manner which makes them unsuitable for obtaining adequate heading information. In this paper, the heading problem is resolved by using one deg/hour ring laser gyros. A tactical-grade IMU is used to provide accurate heading information, and accelerometers are used only for step occurrence detection. A special study is carried out to examine errors in heading, if only one gyro is used instead of three. In this case, the three-gyro solution is used as a reference. To test the concept, several long period tests were performed, carrying the IMU in a backpack. Both DGPS and stand-alone receivers were included to compare two different level initialization sources. 3D-gyro heading solutions initialized with DGPS are promising. However, if only one gyro is used or DGPS is not available, heading solution accuracy degrades significantly. Size restrictions on current ring laser gyros limit the application of the proposed system. However, as gyro technology evolves, such a system may be beneficial for applications such as the positioning of rescue workers, police squads, and other indoor location and navigation applications.

Fuzzy logic based closed-loop strapdown attitude system for unmanned aerial vehicle (UAV)

Abstract: This paper describes the development of a fuzzy logic based closed-loop strapdown attitude reference system (SARS) algorithm, integrated filtering estimator for determining attitude reference, for unmanned aerial vehicles (UAVs) using low-cost solid-state inertial sensors. The SARS for this research consists of three single-axis rate gyros in conjunction with two single-axis accelerometers. For the solution scheme fuzzy modules (rules and reasoning) are utilized for online scheduling of the parameters for the filtering estimator. Implementation using experimental flight test data of SURV-1 Sejong UAV has been performed in order to verify the estimation. The proposed fuzzy logic aided estimation results demonstrate that more accurate performance can be achieved in comparison with conventional fixed parameter filtering estimators. The estimation results were compared with the on-board vertical gyro used as the reference standard or ‘truth model’ for this analysis.

Enhanced inertial measurement unit/global positioning system mapping and navigation process

Abstract: The present invention relates generally to a geospatial database access and query method, and more particularly to a map and Inertial Measurement Unit/Global Positioning System (IMU/GPS) navigation process. With the location information provided by an IMU/GPS integrated system, the geospatial database operations, such as database access and query, are sped up. With the map data from a geospatial database, the navigation performance and accuracy are enhanced. The present invention also supports real time mapping by using IMU/GPS integrated system as the positioning sensor.

Inertial navigation system for mobile objects with constraints

Abstract: An aided inertial navigation system and method for navigating a mobile object having constraints comprising an inertial measurement unit, a processor, and an error correction device. The inertial measurement unit provides acceleration data and/or angular velocity data of the mobile object. The processor is adapted to receive the acceleration data and/or angular velocity data, and to provide output data with position output indicative of position of the mobile object. The error correction device receives as input, state and dynamics information and auxiliary input data including map information associated with the path, speed data, wheel-angle data and discrete data. The error correction device provides as output, state corrections to the processor that enhance accuracy of the position output. The state corrections are used by the processor to estimate position of the mobile object based on the constraints to the mobile object and the map information associated with the path.

The georgia tech unmanned aerial research vehicle: GTMax

Abstract: This paper describes the design, development, and operation of a research Unmanned Aerial Vehicle (UAV) system that has been developed at the Georgia Institute of Technology, called the GTMax. This description will include the processes put in place to enable the system to be used for UAV-technology research, including effective flight testing. Research UAVs are characterized by the need for continual checkout of experimental software and hardware. Also, flight-testing can be further leveraged by complementing research results with flight-test validated simulation results for the same experimental UAV platform. The chosen helicopter-based UAV platform (a Yamaha R-Max) is well instrumented, including: differential GPS, inertial measurement unit, sonar altimeter, radar altimeter, and a 3-axis magnetometer. One or two flight processors can be utilized.

Method and system for fault detection and exclusion for multi-sensor navigation systems

Abstract: A new Fault Detection and Exclusion (FDE) approach for tightly integrated GPS/inertial sensors that combines a normalized solution separation for fault detection and a residual monitoring scheme for fault exclusion is described. The computation of the detection threshold, the horizontal protection level and the horizontal uncertainty level are also presented. This new FDE algorithm is designed to enable the tightly integrated GPS/inertial sensor to be used as a primary means of navigation sensor for civil aviation.

Self-contained spatial input device for wearable computers

Abstract: In this paper, we present a pen-shaped input device forwearable computers which reproduce and recognizethree-dimensional (3D) hand motions with no externalreferences. The input device is equipped with inertialsensors. The inertial sensors measure accelerations andangular velocities produced by a user's handwritingmotion in 2D/3D spaces. The measurements fromgyroscopes are integrated once to produce the attitude ofthe system and are consequently used to remove theeffects of the gravity and the inclination of the system.The compensated acceleration measurements are doublyintegrated to yield the position of the system. Due to theintegration processes involved in reproducing thehandwriting trajectory, the accuracy of the positionmeasurement significantly deteriorates along with time.To reproduce handwriting trajectory of a stroke on asurface and even in the air, we propose algorithms tosegment a stroke, to compensate the integration errors,and to reconstruct 2D trajectory on the x-y plane from 3Dtrajectory in the air. Real experimental results areincluded to show the effectiveness and feasibility of theproposed algorithms. The proposed methods provide anew approach for implementing a small, user-friendlykeyboard alternative input device for wearable computers.

Foot-to-Foot Range Measurement as an Aid to Personal Navigation

Abstract: Ultimately there will be times when all enhancements to GPS signal reception fail. In these situations a number of approaches to GPS denied navigation have been proposed. These often make use of supplemental radio frequency signals, some of which actually require setting up a local RF infrastructure. The personal navigation aid proposed here, although utilizing a radio frequency signal, is intended to be self contained and of low power. It consists of a micromechanical IMU on each boot combined with a series of foot-to-foot range measurements. A frequency generator at the waist sends a signal down one leg to a transmitting antenna on one boot. The RF signal is received on the other boot and sent to the waist pack thereby closing the loop. A detector at the waist measures phase change and thus measures the changing distance between the two feet. Our analysis shows that this scalar distance change measurement used in conjunction with micro-mechanical inertial instruments on each foot and combined with "zero-velocity updates" at each (or most) foot falls enables quite accurate personal navigation. The performance of an unaided inertial navigation system based on modest quality micromechanical instruments is truly poor. Our analysis shows a 2.5 km error in each horizontal direction after walking in a straight line for 10 minutes (2900 ft). The addition of zero velocity updates reduces this error to 60 m predominantly in the cross range axis. The addition of the foot-to-foot range change measurement reduces this value by another two orders of magnitude, to 0.6 m This measurement concept is a big step toward an accu-rate self-contained personal navigation system It is not dependent on external signals or ambient light. The RF could be very low power (it only has to extend over the foot-to-foot distance). As such it should be relatively covert compared to a Doppler radar or acoustic Doppler device. There is a price to pay in terms of body mounted hardware, but this could be mitigated by the push toward instrumented clothing.

Golf club with embedded inertial measurement unit and processing

Abstract: Golf clubs having an embedded inertial measurement unit and a corresponding microprocessor for determining the motion of the head of the golf club. Briefly described, one of a number of embodiments of a golf club comprises a 6DOF inertial measurement unit disposed within the head of the golf club and a microprocessor in communication with the 6DOF inertial measurement unit. The microprocessor is configured to receive data from the 6DOF inertial measurement unit and determine the motion of the head of the golf club.

A 3-DoF Experimental Test-Bed for Integrated Attitude Dynamics and Control Research

Abstract: This article presents the details of a newly constructed 3-dof experimental spacecraft simulator facility at the School of Aerospace Engineering at the Georgia Institute of Technology. The main component of the facility is a cylindrical platform located on a hemi-spherical air bearing that allows friction-free rotation about three axes. The facility includes a variety of actuators and sensors: gas thrusters, variable-speed controlled momentum gyros (which can operate solely in a reaction wheel (RW) or in a control momentum gyro (CMG) mode), a two-axial sun sensor, a high-precision three-axial rate gyro, a three-axial magnetometer, and a complementary inertial measurement unit. The facility offers a truly integrated attitude control system (IACS) for experimental testing of advanced attitude determination and control algorithms.

Low cost robot manipulator

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.

Inertial Sensors Errors Modeling Using Allan Variance

Abstract: In this paper, the Allan variance technique will be used in noise analysis of MEMS-based inertial sensors, including BEI GyroChipTM II, BEI GyroChipTM Horizon, Silicon Design Inc. Model 2412 Triaxial Accelerometer, and two Inertial Measurement Systems (IMU), BEI MotionPak II-3g and Crossbow AHRS400CC-100. Test results clearly show the Allan variance technique is very effective in inertial sensors performance analysis. In addition, Modified Allan variance is also introduced and performed for inertial sensor noise analysis.

Online Motion Estimation from Image and Inertial Measurements

Abstract: We present two algorithms for estimating sensor motion from image and inertial measurements, which are suitable for use with inexpensive inertial sensors and in environments without known fiducials. The first algorithm is a batch method, which produces optimal estimates of the sensor motion, scene structure, and other parameters using measurements from the entire observation sequence simultaneously. The second algorithm recovers sensor motion, scene structure, and other parameters in an online manner, is suitable for use with long or “infinite” sequences, and handles sequences in which no feature is always visible. We also describe initial results from running each algorithm on a sequence for which ground truth is available. We show that while image measurements alone are not sufficient for accurate motion estimation from this sequence, both batch and online estimation from image and inertial measurements produce accurate estimates of the sensors’ motion.

A Personal Navigation System Using Low-Cost MEMS/GPS/Fluxgate

Abstract: The advances of MEMS technology have led the development of small-sized sensors (inertial sensors, magnetic compass sensors, etc.). Small-sized GPS receivers also have been developed using only one GPS chipset. For the synergistic effect, the integrated system of these systems has been adopted in many navigation systems. In this paper, a new algorithm for pedestrian navigation systems (PNS) using the integrated system is proposed. The key of the PNS is step (stance phase) detection. The step is detected using the accelerometer signals. The point of time for calculating of the inclination of the ground and the azimuth is determined through the step detection. The stride is computed using a neural network. The neural network is learned when the GPS signal is available. And then the walking distance and the position of the user are calculated. The performance of the proposed approach is verified through the actual walking test. With position compensation about every 100 steps, about 160m, the proposed system is able to keep an accuracy of 10m.

Method and system for processing pulse signals within an inertial navigation system

Abstract: A method and system (100) for processing pulse signals within an inertial device is provided. The inertial device may have inertial sensors, such as accelerometers (110, 112, 114) and gyroscopes (104, 106, 108). The inertial sensors may output signals represen tative of a moving body's motion. The signals may require correction due to imperfections and other errors of the inertial sensors. The inertial device may receive signals from the inertial sensors and process the signals on a signal-by-signal basis so that when processing the signals, the inertial device at least recognizes which sensor output a signal and when the signal was output. The inertial device may then correlate signals that were output from the inertial sensors at selected times in order to transform the signals into desired navigational frame of reference.

Sensing and Control for a Small-Size Helicopter

Abstract: This paper details the progress to date, toward developing a small autonomous helicopter. We describe system architecture, avionics, visual state estimation, custom IMU design, aircraft modelling, as well as various linear and neuro/fuzzy control algorithms. Experimental results are presented for state estimation using fused stereo vision and IMU data, heading control, and attitude control. FAM attitude and velocity controllers have been shown to be effective in simulation.

Sensor data fusion for inertial navigation of trains in GPS-dark areas

Abstract: The motivation of the presented work is to develop a robust navigation system for accurate localization of trains on railway tracks in the cases where the GPS-based navigation is not temporally available. As the final solution of the train locator naturally takes into consideration the satellite-based navigation, the satellite signal needs not to be available all along the railway. The presented contribution describes an approach to preprocessing and fusing of additional train onboard sensors - the odometer and accelerometer, all targeted to serve as optional and temporary substitution for GPS navigation. The suggested solution is exploring a rule-based substitutions and mutual calibrations of the used sensors depending on actual conditions. The given approach relies on the GPS system only to provide position calibrations and serves a reference method for evaluation of the presented results. Suggested solutions have been experimentally tested with real-world data gathered with locomotive onboard inertial sensors.

Camera-Inertial Sensor modelling and alignment for Visual Navigation

Abstract: This article presents a technique for modeling and calibrating a camera with integrated low-cost iner- tial sensors, three gyros and three accelerometers for full 3D sensing. Inertial sensors attached to a camera can provide valuable data about camera pose and movement. In biological vision systems, inertial cues provided by the vestibular system, are fused with vision at an early processing stage. Vision systems in autonomous vehi- cles can also benefit by taking inertial cues into account. Camera calibration has been extensively studied, and standard techniques established. Inertial navigation systems, relying on high-end sensors, also have established techniques. Nevertheless, in order to use off-the-shelf inertial sensors attached to a camera, appropriate modeling and calibration techniques are required. For inertial sensor alignment, a pendulum instrumented with an encoded shaft is used to estimate the bias and scale factor of inertial measurements. For camera calibration, a standard and reliable camera calibration technique is used, based on images of a planar grid. Having both the camera and the inertial sensors calibrated and observing the vertical direction at different poses, the rigid rotation between the two frames of reference is estimated, using a mathematical model based on unit quaternions. The technique for this alignment and consequent results with simulated and real data are presented at the end of this article.

Integration of GPS and low cost INS measurements

Abstract: GPS and Inertial Navigation Systems (INS) are increasingly used for positioning and attitude determination in a wide range of applications. Until recently, the very high cost of the INS components limited their use to high accuracy navigation and geo-referencing applications. Over the last few years, a number of low cost inertial sensors have come on the market. Although they exhibit large errors, GPS measurements can be used to correct the INS and sensor errors to provide high accuracy real-time navigation. The integration of GPS and INS is usually achieved using a Kalman filter which is a sophisticated mathematical algorithm used to optimise the balance between the measurements from each sensor. The measurement and process noise matrices used in the Kalman filter represent the stochastic properties of each system. Traditionally they are defined a priori and remain constant throughout a processing run. In reality, they depend on factors such as vehicle dynamics and environmental conditions. In this research, three different algorithms are investigated which are able to adapt the stochastic information on-line. These are termed adaptive Kalman filtering algorithms due to their ability to automatically adapt the filter in real time to correspond to the temporal variation of the errors involved. The algorithms used in this research have been tested with the IESSG's GPS and inertial data simulation software. Field trials using a Crossbow AHRS-DMU-HDX sensor have also been completed in a marine environment and in land based vehicle trials. The use of adaptive Kalman filtering shows a clear improvement in the on-line estimation of the stochastic properties of the inertial system. It significantly enhances the speed of the dynamic alignment and offers an improvement in navigation accuracy. The use of the low cost IMU in a marine environment demonstrates that a low cost sensor can potentially meet the requirements of navigation and multi-beam sonar geo-referencing applications.

A new scheme of non-gyro inertial measurement unit for estimating angular velocity

Abstract: The non-gyro inertial measurement unit (NGIMU) uses only accelerometers replacing gyroscopes to compute the motion of a moving body. To alleviate the accumulation of angular velocity error attributed to accelerometers error, a novel design scheme for a NGIMU is proposed along with its mathematic model. Based on the conventional six-accelerometer cube configuration, this scheme employs a nine-accelerometer configuration scheme and obtains the correct sign by exploiting the redundant information of the accelerometers and integrating the angular acceleration value. The accurate angular velocity can be calculated as square root of the square expression of the angular velocity. Simulation results show that the computational accuracy of angular velocity can be improved and confirm the effectiveness and feasibility of the proposed design scheme.

Sourceless tracking of human posture using small inertial/magnetic sensors

Abstract: Human body posture can be tracked in real-time using small inexpensive inertial/magnetic sensor modules to measure the orientation of individual limb segments. To perform this task inertial/magnetic sensors generally contain: three orthogonally mounted angular rate sensors, three orthogonally mounted accelerometers, and three orthogonally mounted magnetometers. These sensors must be small and light enough to be securely attached to major limb segments and avoid user encumbrance. Sensor data must be processed by an efficient filtering algorithm that is able to produce accurate orientation estimates without singularities in all attitudes and does not require still periods to correct for drift. This paper discusses the design of a sourceless body tracking system with an emphasis on sensor and efficient filter design. Various methods for mitigating small transient orientation errors due to variability in the direction of the local magnetic field vector are also described.