Maximum Position Error Research Articles

ROBUST POSITIONING OF DRONES FOR LAND USE MONITORING IN STRONG TERRAIN RELIEF USING VISION-BASED NAVIGATION

For land use monitoring, the main problems are robust positioning in urban canyons and strong terrain reliefs with the use of GPS system only. Indeed, satellite signal reflection and shielding in urban canyons and strong terrain relief results in problems with correct positioning. Using GNSS-RTK does not solve the problem completely because in some complex situations the whole satellite's system works incorrectly. We transform the weakness (urban canyons and strong terrain relief) to an advantage. It is a vision-based navigation using a map of the terrain relief. We investigate and demonstrate the effectiveness of this technology in Chinese region Xiaoshan. The accuracy of the vision-based navigation system corresponds to the expected for these conditions. . It was concluded that the maximum position error based on vision-based navigation is 20 m and the maximum angle Euler error based on vision-based navigation is 0.83 degree. In case of camera movement, the maximum position error based on vision-based navigation is 30m and the maximum Euler angle error based on vision-based navigation is 2.2 degrees.

Two-dimensional laser Doppler velocimeter and its integrated navigation with a strapdown inertial navigation system.

In the field of land navigation, a laser Doppler velocimeter (LDV) can be used to provide the velocity of a vehicle for an integrated navigation system with a strapdown inertial navigation system. In order to suppress the influence of vehicle jolts on a one-dimensional (1D) LDV, this paper designs a split-reuse two-dimensional (2D) LDV. The velocimeter is made up of two 1D velocimeter probes that are mirror-mounted. By the different effects of the vertical vibration on the two probes, the velocimeter can calculate the forward velocity and the vertical velocity of a vehicle. The results of the vehicle-integrated navigation experiments show that the 2D LDV not only can actually suppress the influence of vehicle jolts and greatly improve the navigation positioning accuracy, but also can give high-precision altitude information. The maximum horizontal position errors of the two experiments are 2.6m and 3.2m in 1.9h, and the maximum altitude errors are 0.24m and 0.22m, respectively.

A New Localization System for Indoor Service Robots in Low Luminance and Slippery Indoor Environment Using Afocal Optical Flow Sensor Based Sensor Fusion.

In this paper, a new localization system utilizing afocal optical flow sensor (AOFS) based sensor fusion for indoor service robots in low luminance and slippery environment is proposed, where conventional localization systems do not perform well. To accurately estimate the moving distance of a robot in a slippery environment, the robot was equipped with an AOFS along with two conventional wheel encoders. To estimate the orientation of the robot, we adopted a forward-viewing mono-camera and a gyroscope. In a very low luminance environment, it is hard to conduct conventional feature extraction and matching for localization. Instead, the interior space structure from an image and robot orientation was assessed. To enhance the appearance of image boundary, rolling guidance filter was applied after the histogram equalization. The proposed system was developed to be operable on a low-cost processor and implemented on a consumer robot. Experiments were conducted in low illumination condition of 0.1 lx and carpeted environment. The robot moved for 20 times in a 1.5 × 2.0 m square trajectory. When only wheel encoders and a gyroscope were used for robot localization, the maximum position error was 10.3 m and the maximum orientation error was 15.4°. Using the proposed system, the maximum position error and orientation error were found as 0.8 m and within 1.0°, respectively.

Statics of Continuum Space Manipulators With Nonconstant Curvature via Pseudorigid-Body 3R Model

Continuum space manipulators have wide application prospect in the complex space environment with small space. Efficient and accurate static models are very important for continuum manipulators. However, the existing static models of cable-driven continuum manipulators, which are based on theories of elasticity, are often very complex and not conducive to efficient computing. In this work, the cable-driven continuum manipulator is equivalent to the traditional rigid one by the pseudorigid-body 3R model. We establish the static equation of the continuum manipulator, which takes into account the effects of friction, multi-segment coupling, and external loads. The calculation speed of the static equation obtained by the proposed method is 16.52 times that of obtained by the traditional integration method. Then, the effects of the magnitude and direction of the friction on the curvature and configuration of the manipulator are discussed, respectively. The influences of the configuration and stiffness of the manipulator on the coupling between the segments are also studied. Through the coupling analysis of different stiffness, we give some advice to the design of multi-segment continuum manipulators. Finally, the experiments are made through a two-segment continuum manipulator to validate the proposed static model. The maximum position error between the simulation and experimental results is 5.57%.

Research on the Strategy of Motion Constraint-Aided ZUPT for the SINS Positioning System of a Shearer.

The accurate measurement of position and orientation for shearers is a key technology in realizing an automated, fully-mechanized, coal mining face. Since Global Positioning System (GPS) signal cannot arrive at the coal mine underground, wireless sensor network positioning system cannot operate stably in the coal mine; thus a strap-down inertial navigation system (SINS) is used to measure the position and orientation of the shearer. Aiming at the problem of the SINS accumulative error, this paper proposes a positioning error correction method based on the motion constraint-aided SINS zero velocity updated (ZUPT) model. First of all, a stationary state detection model of the shearer is built with median filter based on the acceleration and angular rate measured by the SINS. Secondly, the motion of the shearer is analyzed using coal mining technology, then the motion constraint model of the shearer is established. In addition, the alternate action between the motion constraint model and the ZUPT model is analyzed at the process of movement and cessation of the shearer, respectively; hence, the motion constraint-aided SINS ZUPT model is built. Finally, by means of the experimental platform of the SINS for the shearer, the experimental results show that the maximum position error with the positioning model proposed in this paper is 1.6 m in 180 s, and increases by 92.0% and 88.1% compared with the single motion constraint model and single ZUPT model, respectively. It can then restrain the accumulative error of the SINS effectively.

Modular injector integrated linear apparatus with motion profile optimization for spatial atomic layer deposition

A spatial atomic layer deposition apparatus integrated with a modular injector and a linear motor has been designed. It consists of four parts: a precursor delivery manifold, a modular injector, a reaction zone, and a driving unit. An injector with multi-layer structured channels is designed to help improve precursor distribution homogeneity. During the back and forth movement of the substrate at high speed, the inertial impact caused by jerk and sudden changes of acceleration will degrade the film deposition quality. Such residual vibration caused by inertial impact will aggravate the fluctuation of the gap distance between the injector and the substrate in the deposition process. Thus, an S-curve motion profile is implemented to reduce the large inertial impact, and the maximum position error could be reduced by 84%. The microstructure of the film under the S-curve motion profile shows smaller root-mean-square and scanning voltage amplitude under an atomic force microscope, which verifies the effectiveness of the S-curve motion profile in reducing the residual vibration and stabilizing the gap distance between the injector and the substrate. The film deposition rate could reach 100 nm/min while maintaining good uniformity without obvious periodic patterns on the surface.

A New Method for Measuring Generalized Geometric Errors for a New Type of Coordinate Measuring Machine Using a Laser Tracker

Geometric errors are the main reason for the inaccuracy of all machines. Measuring these errors and compensating for them will enhance the accuracy of machines themselves. This paper proposes a new systematic methodology to measure generalized geometric errors of a novel coordinate measuring machine based on a laser tracker that can obtain a full pose of measured points. Based on this methodology, a computer program has been developed that can perform error analysis on any serial link. This methodology is applied to the error analysis of a new type of coordinate measuring machine, which has two rotary joints and one linear joint. The obtained results show that generalized geometric errors can be successfully identified, and the accuracy of the experimented machine is considerably improved, thereby reducing maximum position errors from a few millimeters to approximately 50 μm after error compensation.

Double position sensitive detectors (PSDs) based measurement system of trajectory tracking of a moving target

PurposeThe purpose of this paper is to achieve the trajectory tracking measurement of a moving target based on double position sensitive detectors (PSDs).Design/methodology/approachIn this paper, first, a double PSD-based measurement system including hardware system and software system is built up. Then, the working principle is studied to calculate parameters, and calibration experience is conducted. Finally, this double PSD-based measurement system is used to test angular displacement and axial displacement on the tool magazine and automatic tool changer.FindingsIn the experiment, the maximum position error of a space point based on double PSD measurement system is 0.8566 mm, and the average error is 0.4716 mm. These results show that the built double PSD-based measurement system of trajectory tracking of a moving target is reasonable.Originality/valueCombining the characteristics of the PSD and principles of binocular visual measurement, a non-contact three-dimensional measuring system based on double PSDs is developed. The designed double-based measurement system is quite suitable for measurement of a fast-changing illuminant or in the case that the tracking accuracy is not tight.

Influence of mechanical faults on the position error of an axial flux brushless resolver without rotor windings

The axial flux brushless resolver without rotor windings is newly proposed resolver that has the advantages of variable reluctance (VR) resolvers for having no winding on rotor and also, its manufacturing process is much simpler than that of VR resolvers. The influence of different mechanical faults on the position error of the studied resolver is discussed. Different types of eccentricities, inclined rotor and run out error independently and simultaneously are studied using 3D time stepping finite-element method. The results show the maximum position error is related to the resolver under static eccentricity (SE), so an optimised rotor is proposed for the studied resolver to overcome this challenge. Finally, the optimised resolver is built and the experimental tests are done to validate the simulation results.

Kinematic calibration of a 3-P(Pa)S parallel-type spindle head considering the thermal error

Calibration is considered to be the most effective way to improve the accuracy of parallel kinematic machine tools (PKMTs). However, ordinary calibrations only considered the time-invariant errors (manufacturing error), neglecting some time-variant errors, a significant one of which is thermal error. Therefore, in this paper, the influence of thermal error was considered in the calibration of a 3-P(Pa)S parallel-type spindle head. First, a new kinematic model of the spindle head was proposed, which is closer to the real physical model, so the thermal error of the spindle head can be considered in the model. Second, the structural parameters of the spindle head were expressed as the sum of the ideal parameters, the manufacturing errors, and the thermal errors. Third, the pose (position and orientation) of the end effector and the temperature of the spindle head were measured. The positions of the temperature sensors were selected using the global temperature sensitivity index (GTSI), which is derived from the global sensitivity index (GSI). Thus, by setting a standard temperature, the thermal error of the structural parameter can be obtained. Fourth, the influence of the thermal error was inputted into the identification equation for calibration, so the results are the structural parameters at the standard temperature (20 °C). To solve the ill-conditioning problem, a Regularization method was used in the identification. Finally, the calibration was verified on a 3-P(Pa)S-XY machine tool. The RTCP test, performed immediately after the measurement, shows that the maximum position error after the calibration is 0.019mm at the tilt angle of 30° and 0.037mm at 20°. In addition, the RTCP test after a temperature change shows that the calibration considering the thermal error can improve the average position accuracy from 0.025mm to 0.015mm. The calibration method in this paper is expected to be applicable for other machine tools.

Integrity monitoring of vehicle positioning in urban environment using RTK-GNSS, IMU and speedometer

Continuous and trustworthy positioning is a critical capability for advanced driver assistance systems (ADAS). To achieve continuous positioning, methods such as global navigation satellite systems real-time kinematic (RTK), Doppler-based positioning, and positioning using low-cost inertial measurement unit (IMU) with car speedometer data are combined in this study. To ensure reliable positioning, the system should have integrity monitoring above a certain level, such as 99%. Achieving this level when combining different types of measurements that have different characteristics and different types of errors is a challenge. In this study, a novel integrity monitoring approach is presented for the proposed integrated system. A threat model of the measurements of the system components is discussed, which includes both the nominal performance and possible fault modes. A new protection level is presented to bound the maximum directional position error. The proposed approach was evaluated through a kinematic test in an urban area in Japan with a focus on horizontal positioning. Test results show that by integrating RTK, Doppler with IMU/speedometer, 100% positioning availability was achieved. The integrity monitoring availability was assessed and found to meet the target value where the position errors were bounded by the protection level, which was also less than an alert level, indicating the effectiveness of the proposed approach.

NOVEL APPROACH TO IMPROVE GEOCENTRIC TRANSLATION MODEL PERFORMANCE USING ARTIFICIAL NEURAL NETWORK TECHNOLOGY

Abstract: Geocentric translation model (GTM) in recent times has not gained much popularity in coordinate transformation research due to its attainable accuracy. Accurate transformation of coordinate is a major goal and essential procedure for the solution of a number of important geodetic problems. Therefore, motivated by the successful application of Artificial Intelligence techniques in geodesy, this study developed, tested and compared a novel technique capable of improving the accuracy of GTM. First, GTM based on official parameters (OP) and new parameters determined using the arithmetic mean (AM) were applied to transform coordinate from global WGS84 datum to local Accra datum. On the basis of the results, the new parameters (AM) attained a maximum horizontal position error of 1.99 m compared to the 2.75 m attained by OP. In line with this, artificial neural network technology of backpropagation neural network (BPNN), radial basis function neural network (RBFNN) and generalized regression neural network (GRNN) were then used to compensate for the GTM generated errors based on AM parameters to obtain a new coordinate transformation model. The new implemented models offered significant improvement in the horizontal position error from 1.99 m to 0.93 m.

An improved rotation scheme for Tri-axis rotational inertial navigation system

Rotating modulation technique is a mature method which has been widely used in the rotational inertial navigation system (RINS). A proper rotation scheme can greatly improve the position accuracy of the system. However, if the system is in angular motion, the modulation performance of the rotation scheme will be affected and improvements should be made. The modulation mechanism of a conventional rotation scheme based on tri-axis RINS in static base, which is called Scheme A in this paper, is analyzed firstly. Then the bad effects of system’s yaw angular motion upon the modulation performance are discussed and an improvement of the rotation scheme aiming at dynamic base is put forward after that. Simulations based on Matlab are conducted to demonstrate the effectiveness of the improvement. Vehicle experiments based on a real tri-axis RINS demonstrate that the improvement made on rotation scheme can reduce the maximum radical direction position errors by 0.6 n miles in 12 h roughly compared to the original unimproved scheme.

Real-time electromagnetic seed drop detection for permanent implants brachytherapy: Technology overview and performance assessment.

To describe the principles and report on the performance of a novel real-time electromagnetic (EM) seed drop detection technology for permanent implants brachytherapy procedures. A novel EM hollow needle prototype was recently developed by Philips. It possesses standard 3D tracking capability as well as a seed drop detection mechanism, both performed from a single custom built EM sensor. The detection mechanism is based on the magnetic permeability changes in the sensor as the seeds pass through. Drop position estimates are generated by the tracking information at the dropping instants. Three validation experiments were carried out in this study. First, the robustness of the detection mechanism was tested in free air with four different seed types. Detection waveforms were measured and commented. The accuracy of the seed drop position estimates was then evaluated using both 2D and 3D experiments. The procedures consisted of dropping seeds in phantoms, recording the drop position estimates, and finally registering the resulting spatial distributions on reference ones obtained by accurate modalities. Seeds were dropped on a specially designed plastic support adapted to brachytherapy template dimensions for 2D experiments, and true seed positions (reference distribution) were obtained by optical detection. In 3D experiments, seeds were dropped in edible gelatin and reference distributions were obtained by localizing the implants from CT scans of the phantoms. All four seed types were correctly detected by the needle prototype. In total, 250 seeds were dropped on the plastic support, and 96 were dropped in gelatin phantoms. The detection rate was 100% in both cases. The minimum, maximum, and average drop position errors were, respectively, 0.1(+1.6/ - 0.1), 2.9(+1.4/ - 1.5), and 0.9(+1.4/ - 0.7) mm for 2D, and 0.1(+1.0/ - 0.1), 2.1(+1.1/ - 0.8), and 0.6(+1.2/ - 0.5) mm for 3D experiments. The hollow needle prototype combines both EM tracking and automatic seed drop detection in a compact and convenient form. The EM detection mechanism is robust, and the seed drop position estimates appear sufficiently accurate for potential integration of the technology to current brachytherapy treatment planning systems. In that context, it would serve as a valuable tool for rapid dosimetry validation in real-time treatment delivery.

An Online Smoothing Method Based on Reverse Navigation for ZUPT-Aided INSs

Zero velocity update (ZUPT) is widely discussed for error restriction in land vehicle Inertial Navigation Systems (INSs) and wearable pedestrian INSs to overcome the problems of Global Positioning System (GPS) unavailability in urban canyons or indoor scenarios. In this paper, an online smoothing method for ZUPT-aided INSs is presented. By introducing the Rauch–Tung–Striebel (RTS) smoothing method into the ZUPT-aided INS, position errors can be effectively restrained not only at stop points but during the whole trajectory. By integrating reverse navigation with a ZUPT smoother, the method realises forward and real-time processing. Compared with existing approaches, it can improve the position accuracy in real time without any other sensors, which is well suited for applications on high-accuracy navigation in GPS-challenging environments. Accuracy test results with different Inertial Measurement Units (IMUs) show that the developed method can significantly decrease position errors from hundreds or thousands of metres to below ten metres. During the whole trajectory, the online smoothing method ensures the maximum position errors at non-stop points can reach the same level of accuracy at stop points. A delay test result proves that the delay of the reverse online smoothing method proposed in this paper is much shorter than existing online smoothing methods.

Collaborative Tracking Control of Dual Linear Switched Reluctance Machines Over Communication Network With Time Delays.

This paper investigates the collaborative tracking control for dual linear switched reluctance machines (LSRMs) over a communication network with random time delays. Considering the spatio-temporal constraint relationship of the dual LSRMs in complex industrial processes, the collaborative tracking control scheme is proposed based on the networked motion control method. The stability conditions and the controller design method for the networked dual LSRMs are obtained from the two motors relative position error by using Lyapunov theory and delay systems approach. Four different allocation schemes combined with two kinds of external control signals are applied onto the collaborative tracking control experiment platform of the dual LSRMs to validate the effectiveness of the proposed method. The maximum steady-state relative position error within 0.104 mm can be achieved under the constant absolute position reference input signal of 3 mm, and the maximum absolute relative position error within ±0.46 mm can be achieved under the sinusoidal reference of 8 mm amplitude and 0.2 Hz.

Vertical Corner Feature Based Precise Vehicle Localization Using 3D LIDAR in Urban Area.

Tall buildings are concentrated in urban areas. The outer walls of buildings are vertically erected to the ground and almost flat. Therefore, the vertical corners that meet the vertical planes are present everywhere in urban areas. These corners act as convenient landmarks, which can be extracted by using the light detection and ranging (LIDAR) sensor. A vertical corner feature based precise vehicle localization method is proposed in this paper and implemented using 3D LIDAR (Velodyne HDL-32E). The vehicle motion is predicted by accumulating the pose increment output from the iterative closest point (ICP) algorithm based on the geometric relations between the scan data of the 3D LIDAR. The vertical corner is extracted using the proposed corner extraction method. The vehicle position is then corrected by matching the prebuilt corner map with the extracted corner. The experiment was carried out in the Gangnam area of Seoul, South Korea. In the experimental results, the maximum horizontal position error is about 0.46 m and the 2D Root Mean Square (RMS) horizontal error is about 0.138 m.

Positional error similarity analysis for error compensation of industrial robots

The purpose of this paper is to propose an error compensation method with error similarity analysis to improve the absolute positional accuracy of industrial robots. The positional error similarity is proposed with the analysis of the error model established by robot kinematic parameters, and is quantified with semivariogram function. Then an error compensation method is proposed base-on positional error similarity. The ordinary Kriging method is used to calculate the positional errors of the robot TCP. The error compensation is performed by modifying the position coordinates in the robot controlling commands. Experimental verification showed that the maximum positional error of the robot TCP was reduced by 75.36% from 1.2912mm to 0.3182mm.

Capability of Artificial Neural Network for Forward Conversion of Geodetic Coordinates $$(\phi ,\lambda ,h)$$ ( ϕ , λ , h ) to Cartesian Coordinates (X, Y, Z)

The standard forward transformation equation plays a major role in coordinate transformation between global and local datums. Thus, it is a prerequisite step in the forward conversion of geodetic coordinates into cartesian coordinates in coordinate transformation from global to local datum and vice versa. Numerous studies have been carried out on converting cartesian coordinates to geodetic coordinates (reverse procedure) through the application of iterative, approximate, closed form, vector-based and computational intelligence algorithms. However, based on literature covered pertaining to this study, it was realized that the existing researches do not fully address the issue of applying and testing alternative techniques in the case of the forward conversion. Hence, the purpose of this present study was to explore the coordinate conversion performance of two different artificial neural network approaches (backpropagation artificial neural network (BPANN) and radial basis function neural network (RBFNN)) and multiple linear regression (MLR). The statistical findings revealed that the BPANN, RBFNN and MLR offered satisfactory prediction of cartesian coordinates. However, the RBFNN compared to BPANN and MLR showed better stability and more accurate prediction results. Furthermore, in terms of maximum three-dimensional position error, the RBFNN attained 0.004 m while 0.011 and 0.627 m were achieved, respectively, by MLR and BPANN. By virtue of the success achieved in this study, the main conclusion drawn here is that RBFNN provides a promising alternative in the forward conversion of geodetic coordinates into cartesian coordinates. Therefore, the capability of artificial neural network as a powerful tool for solving majority of function approximation problems in geodesy has been demonstrated.

An error-similarity-based robot positional accuracy improvement method for a robotic drilling and riveting system

It is important to improve the absolute positional accuracy of the industrial robots used in the robotic drilling and riveting systems. The purpose of this paper is to propose a method to compensate for the absolute positional errors of the industrial robots. Firstly, the spatial similarity of the positional errors is qualitatively and quantitatively analyzed using semivariogram function and experiments. Secondly, the positional error model is established based on the spatial similarity, and a linear unbiased optimal estimation method of the target positional errors is proposed. Finally, experiments are used to verify the proposed methods with measuring the robot’s positional errors after compensation. The analysis shows that there is a spatial similarity of positional errors in the robot joint space, which can be used to establish error model and to estimate the target’s positional errors. Experimental results show that the proposed method can reduce the maximum absolute positional errors by 84.08 % from 2.01 to 0.32 mm, which can meet the accuracy requirements of the robotic drilling and riveting system.