Pedestrian navigation system using MEMS sensors for heading drift and altitude error correction

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 270-281 ◽  
Author(s):  
Xiaochun Tian ◽  
Jiabin Chen ◽  
Yongqiang Han ◽  
Jianyu Shang ◽  
Nan Li

Purpose This study aims to design an optimized algorithm for low-cost pedestrian navigation system (PNS) to correct the heading drift and altitude error, thus achieving high-precise pedestrian location in both two-dimensional (2-D) and three-dimensional (3-D) space. Design/methodology/approach A novel heading correction algorithm based on smoothing filter at the terminal of zero velocity interval (ZVI) is proposed in the paper. This algorithm adopts the magnetic sensor to calculate all the heading angles in the ZVI and then applies a smoothing filter to obtain the optimal heading angle. Furthermore, heading correction is executed at the terminal moment of ZVI. Meanwhile, an altitude correction algorithm based on step height constraint is proposed to suppress the altitude channel divergence of strapdown inertial navigation system by using the step height as the measurement of the Kalman filter. Findings The verification experiments were carried out in 2-D and 3-D space to evaluate the performance of the proposed pedestrian navigation algorithm. The results show that the heading drift and altitude error were well corrected. Meanwhile, the path calculated by the novel algorithm has a higher match degree with the reference trajectory, and the positioning errors of the 2-D and 3-D trajectories are both less than 0.5 per cent. Originality/value Besides zero velocity update, another two problems, namely, heading drift and altitude error in the PNS, are solved, which ensures the high positioning precision of pedestrian in indoor and outdoor environments.

Sensor Review ◽  
2015 ◽  
Vol 35 (4) ◽  
pp. 389-400 ◽  
Author(s):  
Hongyu Zhao ◽  
Zhelong Wang ◽  
Qin Gao ◽  
Mohammad Mehedi Hassan ◽  
Abdulhameed Alelaiwi

Purpose – The purpose of this paper is to develop an online smoothing zero-velocity-update (ZUPT) method that helps achieve smooth estimation of human foot motion for the ZUPT-aided inertial pedestrian navigation system. Design/methodology/approach – The smoothing ZUPT is based on a Rauch–Tung–Striebel (RTS) smoother, using a six-state Kalman filter (KF) as the forward filter. The KF acts as an indirect filter, which allows the sensor measurement error and position error to be excluded from the error state vector, so as to reduce the modeling error and computational cost. A threshold-based strategy is exploited to verify the detected ZUPT periods, with the threshold parameter determined by a clustering algorithm. A quantitative index is proposed to give a smoothness estimate of the position data. Findings – Experimental results show that the proposed method can improve the smoothness, robustness, efficiency and accuracy of pedestrian navigation. Research limitations/implications – Because of the chosen smoothing algorithm, a delay no longer than one gait cycle is introduced. Therefore, the proposed method is suitable for applications with soft real-time constraints. Practical implications – The paper includes implications for the smooth estimation of most types of pedal locomotion that are achieved by legged motion, by using a sole foot-mounted commercial-grade inertial sensor. Originality/value – This paper helps realize smooth transitions between swing and stance phases, helps enable continuous correction of navigation errors during the whole gait cycle, helps achieve robust detection of gait phases and, more importantly, requires lower computational cost.


Sensor Review ◽  
2015 ◽  
Vol 35 (2) ◽  
pp. 157-167 ◽  
Author(s):  
Shengbo Sang ◽  
Ruiyong Zhai ◽  
Wendong Zhang ◽  
Qirui Sun ◽  
Zhaoying Zhou

Purpose – This study aims to design a new low-cost localization platform for estimating the location and orientation of a pedestrian in a building. The micro-electro-mechanical systems (MEMS) sensor error compensation and the algorithm were improved to realize the localization and altitude accuracy. Design/methodology/approach – The platform hardware was designed with common low-performance and inexpensive MEMS sensors, and with a barometric altimeter employed to augment altitude measurement. The inertial navigation system (INS) – extended Kalman filter (EKF) – zero-velocity updating (ZUPT) (INS-EKF-ZUPT [IEZ])-extended methods and pedestrian dead reckoning (PDR) (IEZ + PDR) algorithm were modified and improved with altitude determined by acceleration integration height and pressure altitude. The “AND” logic with acceleration and angular rate data were presented to update the stance phases. Findings – The new platform was tested in real three-dimensional (3D) in-building scenarios, achieved with position errors below 0.5 m for 50-m-long route in corridor and below 0.1 m on stairs. The algorithm is robust enough for both the walking motion and the fast dynamic motion. Originality/value – The paper presents a new self-developed, integrated platform. The IEZ-extended methods, the modified PDR (IEZ + PDR) algorithm and “AND” logic with acceleration and angular rate data can improve the high localization and altitude accuracy. It is a great support for the increasing 3D location demand in indoor cases for universal application with ordinary sensors.


Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 364 ◽  
Author(s):  
Ming Xia ◽  
Chundi Xiu ◽  
Dongkai Yang ◽  
Li Wang

The pedestrian navigation system (PNS) based on inertial navigation system-extended Kalman filter-zero velocity update (INS-EKF-ZUPT or IEZ) is widely used in complex environments without external infrastructure owing to its characteristics of autonomy and continuity. IEZ, however, suffers from performance degradation caused by the dynamic change of process noise statistics and heading estimation errors. The main goal of this study is to effectively improve the accuracy and robustness of pedestrian localization based on the integration of the low-cost foot-mounted microelectromechanical system inertial measurement unit (MEMS-IMU) and ultrasonic sensor. The proposed solution has two main components: (1) the fuzzy inference system (FIS) is exploited to generate the adaptive factor for extended Kalman filter (EKF) after addressing the mismatch between statistical sample covariance of innovation and the theoretical one, and the fuzzy adaptive EKF (FAEKF) based on the MEMS-IMU/ultrasonic sensor for pedestrians was proposed. Accordingly, the adaptive factor is applied to correct process noise covariance that accurately reflects previous state estimations. (2) A straight motion heading update (SMHU) algorithm is developed to detect whether a straight walk happens and to revise errors in heading if the ultrasonic sensor detects the distance between the foot and reflection point of the wall. The experimental results show that horizontal positioning error is less than 2% of the total travelled distance (TTD) in different environments, which is the same order of positioning error compared with other works using high-end MEMS-IMU. It is concluded that the proposed approach can achieve high performance for PNS in terms of accuracy and robustness.


2017 ◽  
Vol 23 (6) ◽  
pp. 1020-1031 ◽  
Author(s):  
Miguel Fernandez-Vicente ◽  
Ana Escario Chust ◽  
Andres Conejero

Purpose The purpose of this paper is to describe a novel design workflow for the digital fabrication of custom-made orthoses (CMIO). It is intended to provide an easier process for clinical practitioners and orthotic technicians alike. It further functions to reduce the dependency of the operators’ abilities and skills. Design/methodology/approach The technical assessment covers low-cost three-dimensional (3D) scanning, free computer-aided design (CAD) software, and desktop 3D printing and acetone vapour finishing. To analyse its viability, a cost comparison was carried out between the proposed workflow and the traditional CMIO manufacture method. Findings The results show that the proposed workflow is a technically feasible and cost-effective solution to improve upon the traditional process of design and manufacture of custom-made static trapeziometacarpal (TMC) orthoses. Further studies are needed for ensuring a clinically feasible approach and for estimating the efficacy of the method for the recovery process in patients. Social implications The feasibility of the process increases the impact of the study, as the great accessibility to this type of 3D printers makes the digital fabrication method easier to be adopted by operators. Originality/value Although some research has been conducted on digital fabrication of CMIO, few studies have investigated the use of desktop 3D printing in any systematic way. This study provides a first step in the exploration of a new design workflow using low-cost digital fabrication tools combined with non-manual finishing.


2017 ◽  
Vol 29 (6) ◽  
pp. 857-867 ◽  
Author(s):  
Miyeon Lee ◽  
Dong Il Yoo ◽  
Sungmin Kim

Purpose The purpose of this paper is to develop a relatively inexpensive and easily movable three-dimensional (3D) body scanner. Design/methodology/approach Multiple depth perception cameras and a turntable were used to form the hardware and a client-server computer network was used to control the hardware. Findings A portable and inexpensive yet quite accurate body scanner system has been developed. Research limitations/implications The turntable mechanism and semi-automatic model alignment caused some error. Practical implications This scanner is expected to facilitate the acquisition of 3D human body or garment data easily for various research projects. Social implications Many researchers might have an easy access to 3D data of large object such as body or whole garment. Originality/value Inexpensive yet expandable scanning system has been developed using readily available components.


Author(s):  
Ding-jian Huang ◽  
Li-gang Yao ◽  
Wen-jian Li ◽  
Jun Zhang

Purpose The purpose of this research is to achieve a novel magnetic nutation drive for an industry robotic wrist reducer. Design/methodology/approach A novel magnetic nutation drive is proposed, and the structure and principle of the designed magnetic nutation drive are described in this study. Three-dimensional finite element analysis is used to compute the magnetic and torque of the magnetic nutation drive. Furthermore, a prototype of this novel magnetic nutation drive device is developed with 3D printing technology and tested to verify the feasibility of the proposed structure and principle. Findings The simulation and experimental results indicated that the proposed magnetic nutation drive device could meet the desired specifications, and that this novel magnetic nutation drive device successfully realized the non-contact transmission ratio of 105:1 required for a robotic wrist reducer. Practical implications This novel magnetic nutation drive is low-cost and easy to make and use, and which provides the non-contact transmission ratio of 105:1 required for a robotic wrist reducer. Originality/value For the first time, this research applies the permanent magnet drive technology to nutation drive and puts forward a new non-contact nutation drive mode. The novel drive mode can solve some problems of the traditional mechanical contact nutation drive, such as vibration, friction loss, mechanical fatigue and necessity of lubrication. The proposed non-contact nutation drive device can achieve a high reduction ratio with compact structure and can be suitable for industry application.


2011 ◽  
Vol 65 (1) ◽  
pp. 15-28 ◽  
Author(s):  
Khairi Abdulrahim ◽  
Chris Hide ◽  
Terry Moore ◽  
Chris Hill

Shoe mounted Inertial Measurement Units (IMU) are often used for indoor pedestrian navigation systems. The presence of a zero velocity condition during the stance phase enables Zero Velocity Updates (ZUPT) to be applied regularly every time the user takes a step. Most of the velocity and attitude errors can be estimated using ZUPTs. However, good heading estimation for such a system remains a challenge. This is due to the poor observability of heading error for a low cost Micro-Electro-Mechanical (MEMS) IMU, even with the use of ZUPTs in a Kalman filter. In this paper, the same approach is adopted where a MEMS IMU is mounted on a shoe, but with additional constraints applied. The three constraints proposed herein are used to generate measurement updates for a Kalman filter, known as ‘Heading Update’, ‘Zero Integrated Heading Rate Update’ and ‘Height Update’.The first constraint involves restricting heading drift in a typical building where the user is walking. Due to the fact that typical buildings are rectangular in shape, an assumption is made that most walking in this environment is constrained to only follow one of the four main headings of the building. A second constraint is further used to restrict heading drift during a non-walking situation. This is carried out because the first constraint cannot be applied when the user is stationary. Finally, the third constraint is applied to limit the error growth in height. An assumption is made that the height changes in indoor buildings are only caused when the user walks up and down a staircase. Several trials were shown to demonstrate the effectiveness of integrating these constraints for indoor pedestrian navigation. The results show that an average return position error of 4·62 meters is obtained for an average distance of 1557 meters using only a low cost MEMS IMU.


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