MA-Res U-Net:Design of Soybean Navigation System with Improved U-Net Model

Traditional machine vision algorithms have difficulty handling the interference of light and shadow changes,broken rows,and weeds in the complex growth circumstances of soybean fields,which leads to erroneous navigation route segmentation.There are additional shortcomings in the feature extractFion capabilities of the conventional U-Net network.Our suggestion is to utilize an improved U-Net-based method to tackle these difficulties.First,we use ResNet’s powerful feature extraction capabilities to replace the original U-Net encoder.To enhance the concentration on characteristics unique to soybeans,we integrate a multi-scale high-performance attention mechanism.Furthermore,to do multi-scale feature extraction and capture a wider variety of contextual information,we employ atrous spatial pyramid pooling.The segmented image generated by our upgraded U-Net model is then analyzed using the CenterNet method to extract key spots.The RANSAC algorithm then uses these important spots to delineate the soybean seedling belt line.Finally,the navigation line is determined using the angle tangency theory.The experimental findings illustrate the superiority of our method.Our improved model significantly outperforms the original U-Net regarding mean Pixel Accuracy(mPA)and mean Intersection over Union(mIOU)indices,showing a more accurate segmentation of soybean routes.Furthermore,our soybean route navigation system’s outstanding accuracy is demonstrated by the deviation angle,which is only 3°between the actual deviation and the navigation line.This technology makes a substantial contribution to the sustainable growth of agriculture and shows potential for real-world applications.

A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system

In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.

Single-center experience with Knee+^(TM) augmented reality navigation system in primary total knee arthroplasty

BACKGROUND Computer-assisted systems obtained an increased interest in orthopaedic surgery over the last years,as they enhance precision compared to conventional hardware.The expansion of computer assistance is evolving with the employment of augmented reality.Yet,the accuracy of augmented reality navigation systems has not been determined.AIM To examine the accuracy of component alignment and restoration of the affected limb’s mechanical axis in primary total knee arthroplasty(TKA),utilizing an augmented reality navigation system and to assess whether such systems are conspicuously fruitful for an accomplished knee surgeon.METHODS From May 2021 to December 2021,30 patients,25 women and five men,under-went a primary unilateral TKA.Revision cases were excluded.A preoperative radiographic procedure was performed to evaluate the limb’s axial alignment.All patients were operated on by the same team,without a tourniquet,utilizing three distinct prostheses with the assistance of the Knee+™augmented reality navigation system in every operation.Postoperatively,the same radiographic exam protocol was executed to evaluate the implants’position,orientation and coronal plane alignment.We recorded measurements in 3 stages regarding femoral varus and flexion,tibial varus and posterior slope.Firstly,the expected values from the Augmented Reality system were documented.Then we calculated the same values after each cut and finally,the same measurements were recorded radiolo-gically after the operations.Concerning statistical analysis,Lin’s concordance correlation coefficient was estimated,while Wilcoxon Signed Rank Test was performed when needed.RESULTS A statistically significant difference was observed regarding mean expected values and radiographic mea-surements for femoral flexion measurements only(Z score=2.67,P value=0.01).Nonetheless,this difference was statistically significantly lower than 1 degree(Z score=-4.21,P value<0.01).In terms of discrepancies in the calculations of expected values and controlled measurements,a statistically significant difference between tibial varus values was detected(Z score=-2.33,P value=0.02),which was also statistically significantly lower than 1 degree(Z score=-4.99,P value<0.01).CONCLUSION The results indicate satisfactory postoperative coronal alignment without outliers across all three different implants utilized.Augmented reality navigation systems can bolster orthopaedic surgeons’accuracy in achieving precise axial alignment.However,further research is required to further evaluate their efficacy and potential.

Application of unscented Kalman filter to novel terrain passive integrated navigation system

To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environment and AUV navigation requirements of low cost and high accuracy, a novel TPINS is designed with a configuration of the strapdown inertial navigation system （SINS）, the terrain reference navigation system （TRNS）, the Doppler velocity sonar （DVS）, the magnetic compass and the navigation computer utilizing the unscented Kalman filter （UKF） to fuse the navigation information from various navigation sensors. Linear filter equations for the extended Kalman filter （EKF）, nonlinear filter equations for the UKF and measurement equations of navigation sensors are addressed. It is indicated from the comparable simulation experiments of the EKF and the UKF that AUV navigation precision is improved substantially with the proposed sensors and the UKF when compared to the EKF. The TPINS designed with the proposed sensors and the UKF is effective in reducing AUV navigation position errors and improving the stability and precision of the AUV underwater integrated navigation.

Study on rate azimuth platform inertial navigation system

The cost of the gravity passive inertial navigation system will be lower witha rate azimuth platform and gravity sensor constituting a gravity measurement and navigationsystem. According to the system performance characteristics, we study the rate azimuth platforminertial navigation system (RAPINS), give the system navigation algorithm, error equations of theattitude, velocity and position of the rate azimuth platform, and random error models of theaccelerometer and gyro. Using the MATLAB/Simulink tools, we study the RAPINS and RAPINS withvelocity damping. Simulation results demonstrate that the RAPINS with velocity damping has smallerrors in platform attitude and position and satisfies gravity measurement and navigationrequirement.

Error Analysis and Compensation of Strapdown Inertial Navigation System

Based on error analysis, the influence of error sources on strapdown inertial navigation systems is discussed. And the maximum permissible component tolerances are established. In order to achieve the desired accuracy (defined by circular error probability), the types of appropriate sensors are chosen. The inertial measurement unit (IMU) is composed of those sensors. It is necessary to calibrate the sensors to obtain their error model coefficients of IMU. After calibration tests, the accuracy is calculated by uniform design method and it is proved that the accuracy of IMU is satisfied for the desired goal.

ROTATING FIBER OPTIC GYRO STRAP-DOWN INERTIAL NAVIGATION SYSTEM WITH THREE ROTATING AXES

The principle of the inertial navigation system（INS） with rotating inertial measurement unit （IMU） is analyzed. A new IMU is established to rotate round each axis in three directions. Then, the related error models for the designed system during rotating are deduced and the improved system is built. Finally, the performance simulation of the proposed system is provided. The simulation result indicates that the designed system can improve the accuracy of the roll and the pitch as well as heading by rotating three axes, thus guaranting the heading accuracy. Moreover, based on the principle of rotation at six different positions, such structure can carry out real-time calibration, and improve the system performance.

DESIGN AND REALIZATION OF SINS/TWO-ANTENNA GPS INTEGRATED NAVIGATION SYSTEM

The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.

ANTI-ROTATION AND ANTI-SCALE IMAGE MATCHING ALGORITHM FOR NAVIGATION SYSTEM

Based on the inertial navigation system, the influences of the excursion of the inertial navigation system and the measurement error of the wireless pressure altimeter on the rotation and scale of the real image are quantitatively analyzed in scene matching. The log-polar transform （LPT） is utilized and an anti-rotation and anti- scale image matching algorithm is proposed based on the image edge feature point extraction. In the algorithm, the center point is combined with its four-neighbor points, and the corresponding computing process is put forward. Simulation results show that in the image rotation and scale variation range resulted from the navigation system error and the measurement error of the wireless pressure altimeter, the proposed image matching algo- rithm can satisfy the accuracy demands of the scene aided navigation system and provide the location error-correcting information of the system.

Novel gravity passive navigation system

According to the characteristics of gravity passive navigation, this paper presents a novel gravity passive navigation system （GPNS）, which consists of the rate azimuth platform （RAP）, gravity sensor, digitally stored gravity maps, depth sensor and relative log. The algorithm of rate azimuth platform inertial navigation system, error state-space equations, measurement equations and GPNS optimal filter are described. In view of the measurements made by an onboard gravity sensor the Eotvos effect is introduced in the gravity measurement equation of a GPNS optimal filter. A GPNS is studied with the Matlab/Simulink tools; simulation results demonstrate that a GPNS has small errors in platform attitude and position. Because the inertial navigation platform is the rate azimuth platform in the GPNS and gravity sensor is mounted on the rate azimuth platform, the cost of the GPNS is lower than existing GPNS＇s and according to the above results the GPNS meets the need to maintain accuracy navigation for underwater vehicles over long intervals.

Research of Strapdown Integrated Navigation System Based on Rota­tion Control Technology

To realize high-precision Single-axial Rotating FOG-SINS,a low-power,low-cost,middle-precision rotating control mechanism design for single-axial rotating navigation system is put forward.Through theory analysis,design and experimental verification,the rotating control mechanism has good control precision and high reliability,which meets the demands for developing middle&high-precision FOG-SINS.

IAE-adaptive Kalman filter for INS/GPS integrated navigation system

A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.

Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation

To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.

A fast and accurate initial alignment method for strapdown inertial navigation system on stationary base

In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system （SINS） is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing the multiposition technique,but the alignment time of the azimuth error is relatively longer. Over here, the two-position alignment principle is presented. On the basis of this SINS error model, a fast estimation algorithm of the azimuth error for the initial alignment of SINS on stationary base is derived fully from the horizontal velocity outputs and the output rates, and the novel azimuth error estimation algorithm is used for the two-position alignment. Consequently, the speed and accuracy of the SINS＇ s initial alignment is enhanced greatly. The computer simulation results illustrate the efficiency of this alignment method.

An improved computation scheme of strapdown inertial navigation system using rotation technique

To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles.

Comparison of robust H_∞ filter and Kalman filter for initial alignment of inertial navigation system

There are many filtering methods that can be used for the initial alignment of an integrated inertial navigation system. This paper discussed the use of GPS, but focused on two kinds of filters for the initial alignment of an integrated strapdown inertial navigation system (SINS). One method is based on the Kalman filter (KF), and the other is based on the robust filter. Simulation results showed that the filter provides a quick transient response and a little more accurate estimate than KF, given substantial process noise or unknown noise statistics. So the robust filter is an effective and useful method for initial alignment of SINS. This research should make the use of SINS more popular, and is also a step for further research.

Suppression of the G-sensitive drift of laser gyro in dual-axis rotational inertial navigation system

The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer can be averaged out,but the G-sensitive drifts of laser gyro cannot be averaged out by indexing.A 16-position rotational simulation experiment proves the G-sensitive drift will affect the long-term navigation error for the rotational INS quantitatively.The vibration coupling and asymmetric structure of the DRLG are the main errors.A new dithered mechanism and optimized DRLG is designed.The validity and efficiency of the optimized design are conformed by 1 g sinusoidal vibration experiments.An optimized inertial measurement unit(IMU)is formulated and measured experimentally.Laboratory and vehicle experimental results show that the divergence speed of longitude errors can be effectively slowed down in the optimized IMU.In long term independent navigation,the position accuracy of dual-axis rotational INS is improved close to 50%,and the G-sensitive drifts of laser gyro in the optimized IMU are less than 0.0002°/h.These results have important theoretical significance and practical value for improving the structural dynamic characteristics of DRLG INS,especially the highprecision inertial system.

Dynamic navigation system-guided trans-inferior alveolar nerve implant placement in the atrophic posterior mandible: A case report

BACKGROUND In atrophic posterior mandibular areas,where the bone height superior to the inferior alveolar nerve(IAN)is less than 6 mm,short implants are not applicable.Conventional alternatives such as IAN transposition and various alveolar bone augmentation approaches are technically demanding and prone to complications.CASE SUMMARY Computer-guided dynamic navigation implantation improves the accuracy,predictability,and safety of implant placement.This case report presents a dynamic navigation system-guided trans-IAN implant placement technique,which can successfully treat a posterior mandibular dentition defect when the bone height is only 4.5 mm.The implant was inserted into the buccal side of the IAN and was 1.7 mm away from the IAN.The implantation deviations were controlled within a satisfying range,and the long-term restoration outcome was stable.CONCLUSION Dynamic navigation system-guided trans-IAN implant placement might be a recommended technique for patients with extremely insufficient residual bone height and sufficient bone width in the posterior mandibular area.

Hybrid Navigation System Based Autonomous Positioning and Path Planning for Mobile Robots

Positioning and navigation technology is a new trend of research in mobile robot area.Existing researches focus on the indoor industrial problems,while many application fields are in the outdoor environment,which put forward higher requirements for sensor selection and navigation scheme.In this paper,a complete hybrid navigation system for a class of mobile robots with load tasks and docking tasks is presented.The work can realize large-range autonomous positioning and path planning for mobile robots in unstructured scenarios.The autonomous positioning is achieved by adopting suitable guidance methods to meet different application requirements and accuracy requirements in conditions of different distances.Based on the Bezier curve,a path planning scheme is proposed and a motion controller is designed to make the mobile robot follow the target path.The Kalman filter is established to process the guidance signals and control outputs of the motion controller.Finally,the autonomous positioning and docking experiment are carried out.The results of the research verify the effectiveness of the hybrid navigation,which can be used in autonomous warehousing logistics and multi-mobile robot system.

Error Model of Rotary Ring Laser Gyro Inertial Navigation System

To improve the precision of inertial navigation system（INS） during long time operation,the rotation modulated technique（RMT） was employed to modulate the errorr of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of INS errors.The principle of the RMT was introduced and the error propagating functions were derived from the rotary navigation equation.Effects of the measurement error for the rotation angle of the platform on the system precision were analyzed.The simulation and experimental results show that the precision of INS was ① dramatically improved with the use of the RMT,and ② hardly reduced when the measurement error for the rotation angle was in arc-second level.The study results offer a theoretical basis for engineering design of rotary INS.