Showing papers on "Inertial reference unit published in 2016"

A measure system of zero moment point using wearable inertial sensors

Abstract: Keeping balance is the premise of human walking. ZMP(zero moment point) is a point where total torque achieves balance. It is an important evaluation parameter of balance ability in walking, since it can be used to better reflect the dynamic balance during walking. ZMP can be used in many applications, such as medical rehabilitation, disease diagnosis, treatment and etc. In this paper, wearable inertial sensors system based on MEMS is used to measure ZMP (zero moment point) during walking, which is cheap, convenient, and free from the restriction of lab. Our wearable ZMP measurement system consists of inertial measurement subsystem and PC real-time monitoring station. Inertial measurement subsystem includes 9-axis inertial sensing nodes, the body communication network and the central node. Inertial sensing nodes are mounted on different parts of the body to collect body posture information in real-time, and then the best estimation of current posture are obtained by Kalman filter. The data from sensors is aggregated to the central node through the CAN bus, and then ZMP is calculated. Finally, it can be showed in the PC monitoring station. Experiments prove the system can achieve real-time ZMP detection during walking.

Step Detection for ZUPT-Aided Inertial Pedestrian Navigation System Using Foot-Mounted Permanent Magnet

Abstract: A foot-mounted pedestrian dead reckoning system is a self-contained technique for indoor localization. An inertial pedestrian navigation system includes wearable MEMS inertial sensors, such as an accelerometer, gyroscope, or digital compass, which enable the measurement of the step length and the heading direction. Therefore, the use of zero velocity updates is necessary to minimize the inertial drift accumulation of the sensors. The aim of this paper is to develop a foot-mounted pedestrian dead reckoning system based on an inertial measurement unit and a permanent magnet. Our approach enables the stance phase and the step duration detection based on the measurements of the permanent magnet field during each gait cycle. The proposed system involves several parts: inertial state estimation, stance phase detection, altitude measurement, and error state Kalman Filter with zero velocity update and altitude measurement update. Real indoor experiments demonstrate that the proposed algorithm is capable of estimating the trajectory accurately with low estimation error.

Pedestrian Dead Reckoning with Particle Filter for handheld smartphone

Abstract: Commonly used Global Navigation Satellite Systems (GNSS) are inappropriate as Location Based Services (LBS) in indoor environment. Therefore research teams are developing different systems, which can be used as a suitable alternative. One of options is to use Inertial Navigation System (INS) which consists of inertial sensors and mathematic procedures. This concept has been known for a long time, but with arrival of Microelectro Mechanical System (MEMS) INS found wide use. Smartphones with inertial sensors, such as accelerometers and gyroscopes, allow us to use them as input devices for Pedestrian Dead Reckoning (PDR). In this paper we present PDR by using smartphone sensors. They can be classified as low-cost Inertial Measurement Unit (IMU), and have been compared with more precise and expensive Xsens IMU. Accuracy of inertial sensors has increased in the past few years, but they still cannot alone provide proper accuracy because of many negative effects, such as heading drift due to gyroscope bias. Particle Filter (PF) has been successfully used with map constraints to increase the accuracy of proposed location system. Presented results show that low-cost smartphone IMU combined with PF can be applicable as proper navigation system.

A Novel Approach for Attitude Estimation Based on MEMS Inertial Sensors Using Nonlinear Complementary Filters

Abstract: In this paper, a new method for attitude estimation using low-cost micro-electro-mechanical system (MEMS) inertial sensors is developed, in order to obtain accurate attitude parameters when other external sensors, such as the magnetometer and GPS, are limited in operation. The method is based on specific rotation of the inertial measurement unit, which is independent from rigid body motion. The problem of heading angles estimation using just inertial sensors without incorporating additional sensors is studied. An algorithm is developed by incorporating a nonlinear observer in order to fuse measurements from both the gyroscope and the accelerometers. The algorithm provides bias estimation of the gyroscope and better estimation results. Both numerical simulations and real experiments validate the effectiveness of the proposed method.

A Wearable and Modular Inertial Unit for Measuring Limb Movements and Balance Control Abilities

Abstract: Measuring human movement has many useful applications ranging from fall risk assessment, quantifying sports exercise, studying people habits, and monitoring the elderly. Here, we present a versatile, wearable device based on a 9-degrees-of-freedom inertial measurement unit conceived for providing objective measurements of trunk or limb movements for the assessment of motor and balance control abilities. The proposed device measures linear accelerations, angular velocities, and heading and can be configured to either wirelessly transmit the raw or preprocessed data to a computer for online use, e.g., visualization or further processing, or to store the acquired data locally for long-term monitoring during free movement. Furthermore, the device can work in either single sensor or multiple sensors configuration, to simultaneously record several body parts for monitoring full body kinematics. Here, we compare body sway and trunk kinematic data computed based on our sensor with those based on the data from a force platform and a marker-based motion tracker, respectively, during the evaluation of both static and dynamic exercises drawn from clinical balance scales. Results from these experiments on two populations of healthy subjects are encouraging and suggest that the proposed device can effectively be used for measuring limb movements and to assess balance control abilities.

Analytic Coarse Transfer Alignment Based on Inertial Measurement Vector Matching and Real-Time Precision Evaluation

Abstract: This paper presents an analytic coarse transfer alignment method based on inertial measurement vector matching for the inertial navigation system (INS) on vertically launched missiles from the ground. The alignment problem is transformed into the estimation of the relative attitude between the master INS (MINS) and slave INS (SINS) by decomposing the attitude matrix of SINS. As inspired by the ideology of the traditional analytic alignment method, the measurements from the accelerometers and gyroscopes of MINS and SINS are utilized to construct matching vectors to estimate the relative attitude between them without any initial information. Furthermore, the sensitivity of Euler angles with respect to the inertial sensor errors is analyzed according to the presented coarse transfer alignment principle. An algebraic expression for alignment error estimation is given, and thus the real-time precision evaluation for the presented coarse alignment method is achieved. It allows the system to switch to fine alignment in a timely and accurate manner. The simulation and flight test demonstrate that, compared with the quaternion-optimization-based alignment method proposed by Kang et al. , the presented method has a smaller calculation cost and satisfactory convergence. The corresponding precision evaluation algorithm can describe the trend of true alignment error accurately, and is good enough to judge the moment for switching to the fine alignment.

Inertial Sensing, GPS and Odometry

Abstract: This chapter examines how certain properties of the world can be exploited in order for a robot or other device to develop a model of its own motion or pose (position and orientation) relative to an external frame of reference. Although this is a critical problem for many autonomous robotic systems, the problem of establishing and maintaining an orientation or position estimate of a mobile agent has a long history in terrestrial navigation.

In Situ Measurement of the Dynamic Penetration of Free-Fall Projectiles in Soft Soils Using a Low-Cost Inertial Measurement Unit

Abstract: Six degree-of-freedom motion data from projectiles free-falling through water and embedding in soft soil are measured using a low-cost inertial measurement unit, consisting of a tri-axis accelerometer and a three-component gyroscope. A comprehensive framework for interpreting the measured data is described and the merit of this framework is demonstrated by considering sample test data for free-falling projectiles that gain velocity as they fall through water and self-embed in the underlying soft clay. The paper shows the importance of considering such motion data from an appropriate reference frame by showing good agreement in embedment depth data derived from the motion data with independent direct measurements. Motion data derived from the inertial measurement unit are used to calibrate a predictive model for calculating the final embedment depth of a dynamically installed anchor.

Fusion of inertial and depth sensors for movement measurements and recognition

Abstract: A movement recognition system includes an inertial sensor, a depth sensor, and a processor. The inertial sensor is coupled to an object and configured to measure a first unit of inertia of the object. The depth sensor is configured to measure a three dimensional shape of the object using projected light patterns and a camera. The processor is configured to receive a signal representative of the measured first unit of inertia from the inertial sensor and a signal representative of the measured shape from the depth sensor and to determine a type of movement of the object based on the measured first unit of inertia and the measured shape utilizing a classification model.

Modeling and experiment of the suspended seismometer concept for attenuating the contribution of tilt motion in horizontal measurements.

Abstract: Tilt-horizontal coupling in inertial sensors limits the performance of active isolation systems such as those used in gravitational wave detectors. Inertial rotation sensors can be used to subtract the tilt component from the signal produced by horizontal inertial sensors, but such techniques are often limited by the sensor noise of the tilt measurement. A different approach is to mechanically filter the tilt transmitted to the horizontal inertial sensor, as discussed in this article. This technique does not require an auxiliary rotation sensor and can produce a lower noise measurement. The concept investigated uses a mechanical suspension to isolate the inertial sensor from input tilt. Modeling and simulations show that such a configuration can be used to adequately attenuate the tilt transmitted to the instrument, while maintaining translation sensitivity in the frequency band of interest. The analysis is supported by experimental results showing that this approach is a viable solution to overcome the tilt problem in the field of active inertial isolation.

Joints Position Estimation of a Redundant Scara Robot by Means of the Unscented Kalman Filter and Inertial Sensors

Abstract: A method is presented for estimating the position of rotational and prismatic joints of a novel SCARA-type fault-tolerant redundant manipulator using inertial sensors accelerometers and gyroscopes. The estimation is based on the integration of the different sensors by means of the modified AUKF algorithm. The results of the evaluation of this integration scheme are compared with the CMRGD and DCMR methods, which are used for the estimation of the positions of rotational joints based on inertial sensors, showing a clear advantage of the proposed integration method over existing methods for estimating the joint angles, in addition to allowing the calculation of the position of prismatic joints.

Compensation for Stochastic Error of Gyros in a Dual-axis Rotational Inertial Navigation System

Abstract: A dual-axis rotational Inertial Navigation System (INS) has received wide attention in recent years because of high performance and low cost. However, some errors of inertial sensors such as stochastic errors are not averaged out automatically during navigation. Therefore a Twice Position-fix Reset (TPR) method is provided to enhance accuracy of a dual-axis rotational INS by compensating stochastic errors. According to characteristics of an azimuth error introduced by stochastic errors of an inertial sensor in the dual-axis rotational INS, both an azimuth error and a radial-position error are much better corrected by the TPR method based on an optimised error propagation equation. As a result, accuracy of the dual-axis rotational INS is prominently enhanced by the TPR method, as is verified by simulations and field tests.

Inertial navigation unit enhaced with atomic clock

Abstract: An atomic clock is used in conjunction with the GNSS receiver and the inertial sensors, creating a more capable inertial navigation system (INS). The system is composed of a GNSS receiver, an accurate clock, and a mechanism for measuring relative pose changes. The system being presented utilizes an inertial measurement unit (IMU) to provide the relative pose changes, but other mechanisms can be used—like visual and ladar odometry. The GNSS receiver measures the pseudo-ranges to the GNSS satellites in the field of view. These measurements are “time tagged” with the accuracy of the atomic clock. The relative motion between the pseudo-ranges is measured using the IMU. Finally, the lock is achieved by filtering these measurements. The filtering mechanism can vary, from the traditional Kalman Filters to other mechanisms that attempt to minimize the mean square error.

Validation of inertial measurement units for tracking 100m sprint data

Abstract: Wearable micro sensor measurement devices are a promising development in sports technology. This paper presents preliminary data evaluating the accuracy of an inertial measurement unit during 100m sprints against a criterion measure from a tripod-mounted Laveg laser. The inertial measurement units were found to be a valid tool for the analysis of peak velocity (r = 0.92) and average split velocities for splits after the first 10m (r = 0.85 - 0.95). Validation data suggests some caution should be taken in interpretation of the first lorn split (r = 0.32). Whilst data from the two devices for this split were correlated, the inertial measurement unit showed an overestimation for this parameter in comparison to the athlete velocity as measured by the laser. Further in-depth analysis should investigate this period.

Relative Translation and Rotation Calibration Between Optical Target and Inertial Measurement Unit

Abstract: Cameras and Inertial Measurement Units are widely used for motion tracking and general activity recognition. Sensor fusion techniques, which employ both Vision- and IMU-based tracking, rely on their precise synchronization in time and relative pose calibration. In this work, we propose a novel technique for solving both time and relative pose calibration between an optical target (OT) and an inertial measurement unit (IMU). The optical tracking system gathers 6DoF position and rotation data of the OT and the proposed approach uses them to simulate accelerometer and gyroscope readings to compare them against real ones recorded from the IMU. Convergence into the desired result of relative pose calibration is achieved using the adaptive genetic algorithm.

Use of MEMS Inertial Sensors for Performance Improvement of Low-cost Motion Control Systems

Abstract: The performance of a motion control system depends on hardware capabilities, such as sensor resolution and actuator technology. For a certain plant, an amelioration in performance can often be achieved by using better sensors. This however may require a redesign of the system, as the new sensor may not fit into the existing plant. As for the actuators, many motion control systems using stepper motors exist; these stepper motors known for their high torque ripple and limited dynamic performance, especially in the presence of mechanical resonances of the driven load. A possible solution is to replace the actuator with a better one; however, this again may require a costly redesign of the plant. To improve the performance of existing plants with minimal invasive modifications, our group has developed a set of solutions, based on the use of low-cost MEMS inertial sensors, which can be easily placed on the system to be controlled. We will show the manner in which we used such sensors to develop new control strategies, to enhance the performance of existing sensors and actuators, without major modifications to the plant. This will be demonstrated through some examples taken from both laboratory and industrial applications.

Fault detection in lever-arm-compensated position reference systems based on nonlinear attitude observers and inertial measurements in dynamic positioning

Abstract: Marine craft employing a dynamic positioning system rely on measurements from numerous position reference systems in order to maintain the craft's desired position during operation. Faults in such systems pose a serious risk. In particular, slowly emerging faults are difficult to detect and can result in vessel drive-offs, that may in turn have dire consequences. An inertial measurement unit may provide independent position and orientation information, provided that the attitude estimates of the observer are sufficiently accurate. In this paper a three-stage nonlinear observer, based on strapdown inertial measurement units aided by a position reference system with uniform semiglobal exponential stability properties, is posed. The design includes lever arm compensation of position references. Fault detection is achieved with established methodology. Simulations show that this design has the potential to detect slowly emerging position reference faults.

Influence of Inertial Sensor Errors on GNSS/INS Integrated Navigation Performance

Abstract: In GNSS/INS navigation integrated systems, the selection of inertial sensors is a factor which can impact their system performances implicitly. Unfortunately, the research of the relationship between the inertial sensor errors and the navigation performances is not sufficient yet. In this case, the mathematical relationship between the sensor quality and the INS (Inertial Navigation System) performance is firstly derived in details based on a 6 DOF (Degree of Freedom) model. Since the INS is a part of the GNSS/INS system, the influence of the sensor errors on the total performance is further analyzed. By simulating an integrated system using three different grade IMUs (Inertial Measurement Units), the influence mechanism is proved.

Orientation model for inertial devices

Abstract: There is described a computationally efficient quaternion-based orientation estimation model for a moving object using a specialized gradient descent correction step.

Emergency landing using inertial sensors

Abstract: An emergency landing procedure that includes a sequence of control settings is continuously generated. An aircraft is landed, including by using the sequence of control settings and a set of one or more inertial sensors to control an actuator.

Analysis and experiment of error restraint principle in an inertial navigation system with inertial sensors rotation

Abstract: This research developed a new inertial navigation system INS with two inertial measurement units IMU rotating bi-directionally around the vertical and longitudinal body axis respectively. Theoretical analysis and simulation of the proposed rotation INS RINS were presented, which demonstrated that RINS could attenuate positioning errors caused by random constant and time-related components of sensor errors, whereas it did not perform better in modulating white noise component. It also showed that in RINS, utilising inertial sensors with longer relation time and increasing rotation rate are more beneficial. In addition, bi-directional rotation could acquire better result than that unidirectional rotation. Moreover, an experimental RINS prototype with gyroscope drifts of 0.05°/h and accelerometer biases of 50 ug was built. The vehicle tests showed that RINS can achieve positioning accuracy of less than 3 n miles during 8 h 0.3 n mile/h, CEP, more than 10 times improvement than strapdown INS with the same inertial sensors.

On single sensor-based inertial navigation

Abstract: In this paper, we compare two novel algorithms for pedestrian navigation based on signals collected by a single wearable Magnetic, Angular Rate, and Gravity (MARG) sensor. The two navigation algorithms, denoted as Enhanced Pedestrian Dead Reckoning (EPDR) and De-Drifted Propagation (DDP), require the placement of the MARG sensor on the foot or on the chest of the test subject, respectively. Different methods for gait characterization are compared, evaluating navigation dynamics by using data collected through an extensive experimental campaign. The main goal of this research is to investigate the peculiarities of different inertial navigation algorithms, in order to highlight the impact of the sensor's placement, together with inertial sensor issues. Considering a closed path (i.e., ending at the starting point), the relative distance error between the starting point and the final estimated position is about 2% of the total travelled distance for both DDP and EPDR navigation algorithms. On the other hand, the error between the initial heading angle and the final estimated one is approximately 10° for EPDR and 7° for DDP, respectively.

Research of indoor localization based on inertial navigation technology

Abstract: This paper presents the inertial navigation technology applied to three dimensional firefighters indoor positioning system research. The basic principle is through the inertial measurement unit to obtain three-dimensional acceleration and position information in the process of firefighter's movement. In order to improve the positioning accuracy, this paper proposes a zero velocity correction method based on Kalman filtering to suppress the accumulated error in the process of equipment movement. Finally, the method of graph theory to extract building interior network, matching inertial navigation trajectory and location information with building road network.

Accelerometer calibration optimal design based on high-precision three-axis turntable

Abstract: The calibration of inertial navigation system is a prerequisite for inertial navigation, calibration results have a direct impact on the quality of inertial navigation accuracy. It is a widely studied and applied technology with high technology maturation that calibrating inertia devices with high-precision rotary. The commonly used method is to estimate gyro parameters based on the rotational angular rate test, and estimating accelerometer parameters according to the multiple posited static test. There is a complete scheme of calibrating inertial navigation system now in the laboratory. However, in airborne gravity measurements, it demands smooth aircraft flight in practical application, while there are only accelerators in the direction to the sky that work. And the measured value of accelerators are oscillated in the vicinity of g as the aircraft swings in small angle. This paper studied the application conditions of the gravity meter, and optimized the design of the original calibration program form laboratory, then modeled and analysis the turntable error in simulation, and then completed the calibration of the accelerometer in [0.5g, g], which further improved the accuracy of accelerometer calibration, especially the accuracy of the scale factor.

Pedestrian detection with high resolution inertial measurement unit

Abstract: Inertial sensors are used widely for detecting different contexts. However, noise components at high frequencies can disturb the recognition. In this paper, the measurements are made with multi IMU (MIMU) which combines the results of 32 inertial sensors. Averaging of individual sensor outputs reduce the noise level significantly and enables higher resolution. As an example case, we present application for passenger detection in two environments; hallway corridor and public city bus. The results show that accuracy can be increased when MIMU is used compared to single IMU.

A self-calibration method based on one-time electrification before launching for Inertial Navigation System

Abstract: The measuring error of Inertial Navigation System (INS) is the main fact that affects the hitting accuracy of inertial-guided missile. Error parameters compensation could get high-precision. First of all, this article builds an error model of gyro and accelerometer, and then in order to achieve these error parameters' value as closely as possible to their true value in application, a quick self-calibration method based on one-time electrification before launching for inertial platform is proposed. Via this method, INS rotates to 9 particular positions, outputs of inertial sensors are collected in drift state and each error parameter can be separated. The self-calibration method requires no additional devices, improving the maneuverability of the whole system. Finally, experiments are carried out using both the self-calibration method and unit calibration method, the two methods' results show that the largest compared accuracy is 9.40%, which demonstrates the practicability and validity of the suggested method.

Initial alignment of the MEMS inertial measurement system assisted by magnetometers

Abstract: The MEMS inertial measurement system can not perform the initial self-alignment due to the low measurement precision of MEMS gyro. To solve this problem, an initial alignment method assisted by magnetometers is proposed in this paper. Measurement values of MEMS inertial devices and the heading angle are fused to estimate state variables by using unscented Kalman filtering. Error equations of the MEMS inertial measurement system are modified to satisfy the unscented Kalman filtering model in this paper. Simulation results show that the initial alignment method proposed in this paper satisfies the requirement of the MEMS inertial measurement system which is used in low and medium precision field.

Compensation of synchronization error of SIMU and experimental validation

Abstract: Strap-down inertial measurement unit (SIMU) is composed of three gyroscopes and three accelerometers, however there often exists space synchronization error and time synchronization error caused by the limitation of installation and the phase frequency characteristics of its inertial device. Space synchronization error, called lever-arm error or size effect error, is navigation error which is caused by the misalignment of three accelerometers measurement points. Time synchronization error (also called time delay error) is caused by difference between phase frequency characteristics of gyroscope and accelerometer. Under the condition of the non-orthogonal installation of the accelerometer, it establishes mathematical model of the lever-arm error and it can get parameters of the lever-arm by designing a simple experiment method. Aiming at the phase frequency characteristic difference of inertial components, time delay parameters are calculated through establishing the relationship between the accelerometer time delay and navigation accelerometer speed error, and the compensation are directly achieved with the inertial velocity updating algorithm. Then, verify the rationality of theoretical analysis by means of the turntable experiment. At last, the final conclusion is provided.