Heading Estimation Based on Magnetic Markers for Intelligent Vehicles

2016 ◽  
Vol 138 (7) ◽  
Author(s):  
Yeun Sub Byun ◽  
Young Chol Kim
Keyword(s):  
Real Time ◽  
Autonomous Vehicle ◽  
Kinematic Model ◽  
Estimation Method ◽  
Intelligent Vehicles ◽  
Experimental Results ◽  
Main Concept ◽  
Heading Angle ◽  
Magnetic Markers ◽  
Heading Estimation

This paper presents a new real-time heading estimation method for an all-wheel steered single-articulated autonomous vehicle guided by a magnetic marker system. To achieve good guidance control for the vehicle, precise estimation of the position and heading angle during travel is necessary. The main concept of this study is to estimate the heading angle from the relative orientations of the magnetic markers and the vehicle motion. To achieve this, a kinematic model of the all-wheel steered vehicle is derived and combined with the motion of a magnetic ruler mounted near each axle underneath the vehicle. The position coordinates and polarities of the magnetic markers, which are provided a priori, are used to determine the vehicle position at every detection instance. A gyroscope is employed to assist real-time heading estimation at sample times when there are no marker detection data. The proposed method was tested on a real vehicle and evaluated by comparing the experimental results with those of the differential global positioning system (DGPS) in real-time kinematics (RTK) mode. Experimental results show that the proposed method exhibits good performance for heading estimation.

scholarly journals Real-Time Estimation of Glenohumeral Joint Rotation Center With Cable-Driven Arm Exoskeleton (CAREX)—A Cable-Based Arm Exoskeleton

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Ying Mao ◽  
Xin Jin ◽  
Sunil K. Agrawal
Keyword(s):  
Real Time ◽  
Glenohumeral Joint ◽  
Kinematic Model ◽  
Estimation Method ◽  
Time Estimation ◽  
Estimation Algorithm ◽  
Joint Rotation ◽  
Rotation Center ◽  
Arm Rehabilitation ◽  
Novel Approach

In the past few years, the authors have proposed several prototypes of a Cable-driven upper ARm EXoskeleton (CAREX) for arm rehabilitation. One of the assumptions of CAREX was that the glenohumeral joint rotation center (GH-c) remains stationary in the inertial frame during motion, which leads to inaccuracy in the kinematic model and may hamper training performance. In this paper, we propose a novel approach to estimate GH-c using measurements of shoulder joint angles and cable lengths. This helps in locating the GH-c center appropriately within the kinematic model. As a result, more accurate kinematic model can be used to improve the training of human users. An estimation algorithm is presented to compute the GH-c in real-time. The algorithm was implemented on the latest prototype of CAREX. Simulations and preliminary experimental results are presented to validate the proposed GH-c estimation method.

A Method for Real-Time Estimating Pose of Large Aircraft Component in Process of Pose Adjustment Based on the Unscented Kalman Filter

2012 ◽  
Vol 442 ◽  
pp. 251-255
Author(s):  
Zheng Ying
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Unscented Kalman Filter ◽  
Kinematic Model ◽  
Estimation Method ◽  
Time Estimation ◽  
Measuring Point ◽  
Aircraft Component ◽  
Forward Kinematic ◽  
Large Aircraft

To estimate the pose of large aircraft component in pose adjustment quickly and accurately, a real-time estimation method based on Unscented Kalman filter (UKF) is proposed. Firstly, in the process of the aircraft component adjustment, a rough value of aircraft component’s pose is acquired by using forward kinematic model and the displacement of positioners on real time. Then, position of a measuring point fixed on aircraft component is obtained by a laser tracker. At last, UKF is employed to integrate the previous rough value and the measuring point position for evaluating the accurate pose of aircraft component. Numerical simulation results show that the presented method is achieved easily, calculated fast and high accurate.

Real-Time Estimation of Glenohumeral Joint Rotation Center With CAREX: A Cable-Based Arm Exoskeleton

2012 ◽  
Author(s):  
Ying Mao ◽  
Xin Jin ◽  
Sunil K. Agrawal
Keyword(s):  
Real Time ◽  
Healthy Subjects ◽  
Degrees Of Freedom ◽  
Glenohumeral Joint ◽  
Kinematic Model ◽  
Time Estimation ◽  
Estimation Algorithm ◽  
Experimental Results ◽  
Joint Rotation ◽  
Rotation Center

In the past few years, the authors have proposed several prototypes of a Cable-driven upper ARm EXoskeleton (CAREX) for arm rehabilitation. The key advantages of CAREX over conventional exoskeletons are: (i) It is nearly an order of magnitude lighter. (ii) It does not have conventional links and joints, hence does not require joint axes alignment and segment lengths adjustment. (iii) It does not limit the natural degrees-of-freedom of the upper limb. (iv) The structure of the exoskeleton is novel as the cables are routed from the proximal to the distal segments of the arm. Preliminary experimental results with CAREX on a robotic arm and on healthy subjects have demonstrated the effectiveness of the exoskeleton within “assist-as-needed” training paradigm. In this paper, we propose a novel approach to estimate the glenohumeral joint rotation center (GH-c) using measurements of shoulder joint angles and cable lengths. This helps in locating the glenohumeral joint rotation center appropriately within the kinematic model. As a result, more accurate kinematic model can be used to improve the training of human users. An estimation algorithm is presented to compute the GH-c in real-time. The algorithm was implemented on the latest prototype of CAREX which controls four degrees-of-freedom of the shoulder and elbow. Preliminary experiments were performed on two healthy subjects under two different scenarios: (i) GH-c was assumed to be a fixed point and (ii) GH-c was estimated using the proposed algorithm. Experimental results are presented to compare the two scenarios.

scholarly journals A Survey on Novel Estimation Approach of Motion Controllers for Self-Driving Cars

2021 ◽  
Vol 2 (4) ◽  
pp. 211-219
Author(s):  
Vinothkanna R
Keyword(s):  
Motion Planning ◽  
Real Time ◽  
Autonomous Vehicle ◽  
Estimation Method ◽  
Autonomous Driving ◽  
Estimation Methods ◽  
Real Time Traffic ◽  
Traffic Uncertainty ◽  
Research Article ◽  
Uncertainty Control

The motion planning framework is one of the challenging tasks in autonomous driving cars. During motion planning, predicting of trajectory is computed by Gaussian propagation. Recently, the localization uncertainty control will be estimating by Gaussian framework. This estimation suffers from real time constraint distribution for (Global Positioning System) GPS error. In this research article compared novel motion planning methods and concluding the suitable estimating algorithm depends on the two different real time traffic conditions. One is the realistic unusual traffic and complex target is another one. The real time platform is used to measure the several estimation methods for motion planning. Our research article is that comparing novel estimation methods in two different real time environments and an identifying better estimation method for that. Our suggesting idea is that the autonomous vehicle uncertainty control is estimating by modified version of action based coarse trajectory planning. Our suggesting framework permits the planner to avoid complex and unusual traffic (uncertainty condition) efficiently. Our proposed case studies offer to choose effectiveness framework for complex mode of surrounding environment.

scholarly journals A Multi-Mode PDR Perception and Positioning System Assisted by Map Matching and Particle Filtering

2020 ◽  
Vol 9 (2) ◽  
pp. 93 ◽  
Author(s):  
Xuan Wang ◽  
Guoliang Chen ◽  
Mengyi Yang ◽  
Saizhou Jin
Keyword(s):  
Particle Filtering ◽  
Estimation Method ◽  
Dead Reckoning ◽  
Map Matching ◽  
Angle Deviation ◽  
Finite State ◽  
Heading Angle ◽  
Heading Estimation ◽  
Stability And Accuracy ◽  
And Behavior

Currently, pedestrian dead reckoning (PDR) is widely used in indoor positioning. Since there are restrictions on a device’s pose in the procedure of using a smartphone to perform the PDR algorithm, this study proposes a novel heading estimation solution by calculating the integral of acceleration along the direction of the user’s movement. First, a lightweight algorithm, that is, a finite state machine (FSM)-decision tree (DT), is used to monitor and recognize the device mode, and the characteristics of the gyroscope at the corners are used to improve the heading estimate performance during the linear phase. Moreover, to solve the problem of heading angle deviation accumulation on positioning, a map-aided particle filter (PF) and behavior perception techniques are introduced to constrain the heading and correct the trajectory through the wall after filtering. The results indicate that the recognition of phone pose can be 93.25%. The improved heading estimation method can achieve higher stability and accuracy than the traditional step-wise method. The localization error can reduce to approximately 2.2 m when the smartphone is held at certain orientations.

Research on Automatic Magnetic Deviation Compensation of Electronic Compass for Quadrotor

2013 ◽  
Vol 347-350 ◽  
pp. 995-999
Author(s):  
Wen Jian Xiao ◽  
Ping Lu
Keyword(s):  
Measurement Error ◽  
Real Time ◽  
Horizontal Plane ◽  
Magnetic Sensor ◽  
Experimental Results ◽  
Sensor Data ◽  
Automatic Compensation ◽  
Time Performance ◽  
Heading Angle ◽  
Electronic Compass

In magnetic heading measurement of quadrotor, it is necessary to compensate the magnetic deviation of the electronic magnetic compass. For the flight characteristics of quadrotor, a method using sampling data when the aircraft is in the air to achieve automatic compensation of the deviation has been proposed. Using elliptical hypothesis method one can only compensate deviation for quadrotor flying in horizontal plane by collecting the magnetic sensor data in different directions. When the quadrotor flying in any attitudes, using ellipsoid hypothesis method can obtain parameters used by magnetic deviation compensation. Using these parameters, the pitch and roll angles of quadrotor, the magnetic deviation could be compensated. Experimental results show that this method works well and has a good real time performance. The measurement error of heading angle could be less than 1 °.

JOINT ESTIMATION OF THE TRANSMISSIBILITY AND SEVERITY OF EBOLA VIRUS DISEASE IN REAL TIME

2017 ◽  
Vol 25 (04) ◽  
pp. 587-603 ◽  
Author(s):  
YUSUKE ASAI ◽  
HIROSHI NISHIURA
Keyword(s):  
Real Time ◽  
Ebola Virus ◽  
Virus Disease ◽  
Critical Role ◽  
Estimation Method ◽  
Case Fatality ◽  
Ascertainment Bias ◽  
Joint Estimation ◽  
Ebola Virus Disease ◽  
Strong Impact

The effective reproduction number [Formula: see text], the average number of secondary cases that are generated by a single primary case at calendar time [Formula: see text], plays a critical role in interpreting the temporal transmission dynamics of an infectious disease epidemic, while the case fatality risk (CFR) is an indispensable measure of the severity of disease. In many instances, [Formula: see text] is estimated using the reported number of cases (i.e., the incidence data), but such report often does not arrive on time, and moreover, the rate of diagnosis could change as a function of time, especially if we handle diseases that involve substantial number of asymptomatic and mild infections and large outbreaks that go beyond the local capacity of reporting. In addition, CFR is well known to be prone to ascertainment bias, often erroneously overestimated. In this paper, we propose a joint estimation method of [Formula: see text] and CFR of Ebola virus disease (EVD), analyzing the early epidemic data of EVD from March to October 2014 and addressing the ascertainment bias in real time. To assess the reliability of the proposed method, coverage probabilities were computed. When ascertainment effort plays a role in interpreting the epidemiological dynamics, it is useful to analyze not only reported (confirmed or suspected) cases, but also the temporal distribution of deceased individuals to avoid any strong impact of time dependent changes in diagnosis and reporting.

scholarly journals Real-time Array Shape Estimation Method of Horizontal Suspended Linear Array Based on Non-acoustic Auxiliary Sensors

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Zonglun Che ◽  
Jun Wang ◽  
Jing Zhu ◽  
Bingbing Zhang ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Linear Array ◽  
Estimation Method ◽  
Shape Estimation ◽  
Array Shape Estimation

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

Sign in / Sign up

Export Citation Format

Share Document