Most view articles
2017, 38(10):2351-2363.
Abstract:
Robot teleoperation is the key technology to implement tasks in space, telesurgery, deep ocean areas. Robot teleoperation based on virtual reality is an efficient way to overcome the time delay problem, which can provide with a teleoperation with hightransparency and strongstability performance, and it is currently the main way to realize robot teleoperation. Firstly, the key components of the robot teleoperation system based on virtual reality are analyzed, and the function of each module is introduced. Secondly, methods to realize virtual reality environment modelling are reviewed, including the geometric modelling and the dynamic modelling methods. The performance of each modelling method is analyzed. Besides, the construction methods and application areas of virtual fixtures are discussed. Furthermore, current problems in this area are summarized and analyzed, and some research directions are proposed.
Robot teleoperation is the key technology to implement tasks in space, telesurgery, deep ocean areas. Robot teleoperation based on virtual reality is an efficient way to overcome the time delay problem, which can provide with a teleoperation with hightransparency and strongstability performance, and it is currently the main way to realize robot teleoperation. Firstly, the key components of the robot teleoperation system based on virtual reality are analyzed, and the function of each module is introduced. Secondly, methods to realize virtual reality environment modelling are reviewed, including the geometric modelling and the dynamic modelling methods. The performance of each modelling method is analyzed. Besides, the construction methods and application areas of virtual fixtures are discussed. Furthermore, current problems in this area are summarized and analyzed, and some research directions are proposed.
2 Application of humanmachine intelligence synergy in the field of medical and rehabilitation robot
2017, 38(10):2373-2380.
Abstract:
Biological intelligence (human intelligence) and artificial intelligence (machine intelligence) have their good points, respectively and they also have strong advantage complementarity. With the aid of all kinds of humanmachine interface technologies and methods, human intelligence and artificial intelligence are combined to form a new powerful hybrid intelligence, which will provide a significant theory innovation and breakthrough in technology. This paper firstly introduces the main research directions, key technology problems and major research contents of humanmachine intelligence. Then, further introduction is made to illustrate the applications and promoting actions of humanmachine intelligence synergy technology in the fields of service, medical and rehabilitation robot. Finally, the possible problems and challenges existing in the applications are analyzed, and conclusion is made.
Biological intelligence (human intelligence) and artificial intelligence (machine intelligence) have their good points, respectively and they also have strong advantage complementarity. With the aid of all kinds of humanmachine interface technologies and methods, human intelligence and artificial intelligence are combined to form a new powerful hybrid intelligence, which will provide a significant theory innovation and breakthrough in technology. This paper firstly introduces the main research directions, key technology problems and major research contents of humanmachine intelligence. Then, further introduction is made to illustrate the applications and promoting actions of humanmachine intelligence synergy technology in the fields of service, medical and rehabilitation robot. Finally, the possible problems and challenges existing in the applications are analyzed, and conclusion is made.
2017, 38(10):2430-2436.
Abstract:
In order to improve the accuracy of the scanning wavelength of the portable grating scanning near infrared spectrometer, on the basis of the dispersion formula of plane diffraction grating and the position & mechanical transmission relationship among the grating, swing rod and screw in the scanning mechanism, a mathematical model of spectrometer wavelength correction is built, and a wavelength correction method is proposed. The method includes three processes. First, the parameters of the wavelength correction model are determined based on particle swarm optimization algorithm. Second, the swing rod length and the correction value of the wavelength are determined based on the swing rod length ratio of the wavelength correction model and full spectrum comparison optimization. Third, the hardware structure adjustment and soft parameter compensation are conducted on the spectrometer. The characteristic wavelength of a standard light source was used to perform wavelength correction experiment on the selfdeveloped portable nearinfrared spectrometer. The experiment results indicate that after wavelength correction the wavelength accuracy of the spectrometer is better than ±1 nm, which satisfies the spectrometer wavelength accuracy requirement, and the results verify the correctness of the spectrometer wavelength error analysis and the effectiveness of the wavelength correction method.
In order to improve the accuracy of the scanning wavelength of the portable grating scanning near infrared spectrometer, on the basis of the dispersion formula of plane diffraction grating and the position & mechanical transmission relationship among the grating, swing rod and screw in the scanning mechanism, a mathematical model of spectrometer wavelength correction is built, and a wavelength correction method is proposed. The method includes three processes. First, the parameters of the wavelength correction model are determined based on particle swarm optimization algorithm. Second, the swing rod length and the correction value of the wavelength are determined based on the swing rod length ratio of the wavelength correction model and full spectrum comparison optimization. Third, the hardware structure adjustment and soft parameter compensation are conducted on the spectrometer. The characteristic wavelength of a standard light source was used to perform wavelength correction experiment on the selfdeveloped portable nearinfrared spectrometer. The experiment results indicate that after wavelength correction the wavelength accuracy of the spectrometer is better than ±1 nm, which satisfies the spectrometer wavelength accuracy requirement, and the results verify the correctness of the spectrometer wavelength error analysis and the effectiveness of the wavelength correction method.
2017, 38(10):2391-2399.
Abstract:
The haptic rendering technique provides the haptic interaction between the operator and virtual environment by means of a haptic humanmachine interface device, which enables the operator to touch, perceive and manipulate the virtual objects actively. The haptic rendering method enhances the realism and immersion of the virtual reality system, and further expands the application field of virtual reality technology. Traditional wearable haptic rendering devices and force feedback joystick haptic rendering devices have some limitations in portability, operating space and other aspects. As the rapid development of computer technology and consumer electronics, the haptic rendering methods for natural humancomputer interaction gain wide concern. Firstly, this paper introduces the traditional haptic rendering devices, such as wearable device and force feedback joystick device. Then, the haptic rendering methods for natural humancomputer interaction, including the ungrounded method and untethered method, are elaborated. After comparing and analyzing the differences of different haptic rendering methods, the future development direction of the haptic rendering methods for natural interaction is discussed.
The haptic rendering technique provides the haptic interaction between the operator and virtual environment by means of a haptic humanmachine interface device, which enables the operator to touch, perceive and manipulate the virtual objects actively. The haptic rendering method enhances the realism and immersion of the virtual reality system, and further expands the application field of virtual reality technology. Traditional wearable haptic rendering devices and force feedback joystick haptic rendering devices have some limitations in portability, operating space and other aspects. As the rapid development of computer technology and consumer electronics, the haptic rendering methods for natural humancomputer interaction gain wide concern. Firstly, this paper introduces the traditional haptic rendering devices, such as wearable device and force feedback joystick device. Then, the haptic rendering methods for natural humancomputer interaction, including the ungrounded method and untethered method, are elaborated. After comparing and analyzing the differences of different haptic rendering methods, the future development direction of the haptic rendering methods for natural interaction is discussed.
2017, 38(10):2364-2372.
Abstract:
In the current robot aided rehabilitation training methods based on patient’s active participation, the perception of the patients’ active participation are mostly from the viewpoint of “motor” while neglecting the “psychological” involvement. Moreover, the interactive control methods do not incorporate robotic continuous variable motion control and therapist discrete event decision control into a unified framework. To solve this problem, a robotassisted clinical rehabilitation training method is proposed based on anxiety emotion recognition and hybrid theory. Firstly, the significance and difference of anxiety with different arousal are analyzed; Secondly, an anxiety emotion classifier using radial basis function based support vector machine is developed. Besides, humanrobot interactive controller coinciding with the arousal of the patient’s anxiety is developed by using hybrid control theory. Finally, the proposed method is verified with three recruited stroke patients on a constructed clinical experimental platform featuring a Barrett WAMTM manipulator.
In the current robot aided rehabilitation training methods based on patient’s active participation, the perception of the patients’ active participation are mostly from the viewpoint of “motor” while neglecting the “psychological” involvement. Moreover, the interactive control methods do not incorporate robotic continuous variable motion control and therapist discrete event decision control into a unified framework. To solve this problem, a robotassisted clinical rehabilitation training method is proposed based on anxiety emotion recognition and hybrid theory. Firstly, the significance and difference of anxiety with different arousal are analyzed; Secondly, an anxiety emotion classifier using radial basis function based support vector machine is developed. Besides, humanrobot interactive controller coinciding with the arousal of the patient’s anxiety is developed by using hybrid control theory. Finally, the proposed method is verified with three recruited stroke patients on a constructed clinical experimental platform featuring a Barrett WAMTM manipulator.
2017, 38(10):2400-2406.
Abstract:
In order to make the arm rehabilitation patients accurately feel the endofarm force, a soft measurement method of endofarm force is proposed based on random forest regression. The data from the electromyography (EMG) sensors and the arm gesture sensors are integrated to describe the comprehensive feature information of the arm. The comprehensive feature information is used as the input of Random Forest Regression with the endofarm force as the output. According to the basic actions of arm rehabilitation, two groups of experiments ‘pushpull’ and ‘liftdrop’ are specifically designed. The Random Forest Regression is trained offline with the comprehensive feature information and the endofarm force measured with a force sensor, then prediction of endofarm force is conducted and compared with the real force. The method is verified by the experimental results and the effectiveness of the method is proved.
In order to make the arm rehabilitation patients accurately feel the endofarm force, a soft measurement method of endofarm force is proposed based on random forest regression. The data from the electromyography (EMG) sensors and the arm gesture sensors are integrated to describe the comprehensive feature information of the arm. The comprehensive feature information is used as the input of Random Forest Regression with the endofarm force as the output. According to the basic actions of arm rehabilitation, two groups of experiments ‘pushpull’ and ‘liftdrop’ are specifically designed. The Random Forest Regression is trained offline with the comprehensive feature information and the endofarm force measured with a force sensor, then prediction of endofarm force is conducted and compared with the real force. The method is verified by the experimental results and the effectiveness of the method is proved.
2017, 38(10):2589-2596.
Abstract:
Binocular stereo vision and 3D laser scanning techniques are the common sensor measurement methods in environment detection and modeling for mobile robots. In order to realize the data fusion application of the two systems, it is necessary to establish the mathematic relationship between the two local measurement coordinate systems, which is the position and pose joint calibration between the sensors. This paper proposes a new method for the joint calibration based on the distance matching among 3D feature points. A calibration board is designed, which is basically a blackwhite chess board with hollow holes. The binocular stereo vision cameras are used to extract the 3D coordinate information of the corner points of the chess board, and a laser ranging radar is used to scan and acquire the 3D coordinates of the centers of the hollow area. Through minimizing the squared difference of the theoretical and measured distances of two groups of the feature points, the rotation matrix and translation vector of the two sensor coordinate systems are obtained. The joint measurement experiment results show the accuracy and reliability of the proposed method.
Binocular stereo vision and 3D laser scanning techniques are the common sensor measurement methods in environment detection and modeling for mobile robots. In order to realize the data fusion application of the two systems, it is necessary to establish the mathematic relationship between the two local measurement coordinate systems, which is the position and pose joint calibration between the sensors. This paper proposes a new method for the joint calibration based on the distance matching among 3D feature points. A calibration board is designed, which is basically a blackwhite chess board with hollow holes. The binocular stereo vision cameras are used to extract the 3D coordinate information of the corner points of the chess board, and a laser ranging radar is used to scan and acquire the 3D coordinates of the centers of the hollow area. Through minimizing the squared difference of the theoretical and measured distances of two groups of the feature points, the rotation matrix and translation vector of the two sensor coordinate systems are obtained. The joint measurement experiment results show the accuracy and reliability of the proposed method.
2017, 38(10):2484-2491.
Abstract:
In order to improve the accuracy of 5axis machine tool, a geometric error detection method for rotary feed drive using laser interferometer is presented, which realizes geometry error measurement for rotary axis. This method can be implemented in general rotary feed drive such as AC table tilting type and BC tilting table type. Synchronized motion with linear axis and rotary axis is applied in the measurement. The dependence of traditional methods on rotary center coordinate can be avoided during the measurement. The constraints between the angular error of the linear axis and the geometric error of the rotation axis are deduced. The time cost of setup and measurement can be decreased guaranteeing with the measurement accuracy. Compensation and fast measurement are is realized on measurement of positioning error, resettle error and backlash in rotary axis. An experiment of geometric error measurement is conducted based on XKR50A 5axis machine tool. The accuracy of the rotary feed drive is largely improved after the compensation. The feasibility and engineering application of the method is proved.
In order to improve the accuracy of 5axis machine tool, a geometric error detection method for rotary feed drive using laser interferometer is presented, which realizes geometry error measurement for rotary axis. This method can be implemented in general rotary feed drive such as AC table tilting type and BC tilting table type. Synchronized motion with linear axis and rotary axis is applied in the measurement. The dependence of traditional methods on rotary center coordinate can be avoided during the measurement. The constraints between the angular error of the linear axis and the geometric error of the rotation axis are deduced. The time cost of setup and measurement can be decreased guaranteeing with the measurement accuracy. Compensation and fast measurement are is realized on measurement of positioning error, resettle error and backlash in rotary axis. An experiment of geometric error measurement is conducted based on XKR50A 5axis machine tool. The accuracy of the rotary feed drive is largely improved after the compensation. The feasibility and engineering application of the method is proved.
2017, 38(10):2407-2414.
Abstract:
In order to realize the reuse of the main components of the general handeye system and the structuredlight seam tracking system, the installation of a laser, filter and protective device on the basis of the general handeye system makes it used as a seam tracking sensor. Calibration results of the original handeye system were experimentally modified to replace the calibration of the structuredlight seam tracking sensor. The influence caused by the installation of laser and filter on the original handeye calibration result is analyzed in detail. The method of data approximation is used to improve the handeye calibration accuracy of the line laser structured light seam tracking sensor. In the experiment, the handeye system is calibrated firstly to obtain the original matrix of the camera coordinate system to the tool coordinate system. The error of welding point data obtained from the original extrinsic matrix and the actual coordinate of the solder joint is analyzed to correct the handeye calibration result. Experimental results show that the average precision of the handeye calibration of the lightseam tracking sensor based on the calibration results of the general handeye system is 0.53mm, which can meet the requirements of engineering welding.
In order to realize the reuse of the main components of the general handeye system and the structuredlight seam tracking system, the installation of a laser, filter and protective device on the basis of the general handeye system makes it used as a seam tracking sensor. Calibration results of the original handeye system were experimentally modified to replace the calibration of the structuredlight seam tracking sensor. The influence caused by the installation of laser and filter on the original handeye calibration result is analyzed in detail. The method of data approximation is used to improve the handeye calibration accuracy of the line laser structured light seam tracking sensor. In the experiment, the handeye system is calibrated firstly to obtain the original matrix of the camera coordinate system to the tool coordinate system. The error of welding point data obtained from the original extrinsic matrix and the actual coordinate of the solder joint is analyzed to correct the handeye calibration result. Experimental results show that the average precision of the handeye calibration of the lightseam tracking sensor based on the calibration results of the general handeye system is 0.53mm, which can meet the requirements of engineering welding.
2017, 38(10):2381-2390.
Abstract:
In order to improve the coordinated motion ability of the limbs of patients with hemiplegia, a new type of a sitting singleinput rehabilitation robot for coordinated movement of limbs rehabilitation training robot is developed. This robot can provide the synchronous and asynchronous cooperation training for hemiplegic patients under the active and passive training mode. Based on the 7R linkage metamorphic mechanism, a rehabilitation training mechanism is designed to realize the coordinated movement of the upper and lower limbs. By the transmission system，the crank initial phase of the training mechanism can be adjusted, which can realize the synchronous or asynchronous movement of the left and right sides of the limbs. The kinematics analysis of the training mechanism is conducted, and it is proved theoretically that the mechanism can achieve the coordination movement of the limbs. The upper and lower computer control system is exploited by intelligent mobile terminal and microcontroller. Finally, the experiments are carried out on the prototype of the robot. The test results are as follows: The robot can realize cooperative motion of upper and lower limbs that the shoulder joint of the subject can move between -16.9° and 15.1°, and the knee joint can move between 121.5° and 172.5°; The robot can achieve passive training of synchronous and asynchronous limbs with the speed limit (0~6 r/min) and active training of asynchronous limbs with plantar pressure range (61.82~227 N). Synchronous and asynchronous training modes can be switched automatically.
In order to improve the coordinated motion ability of the limbs of patients with hemiplegia, a new type of a sitting singleinput rehabilitation robot for coordinated movement of limbs rehabilitation training robot is developed. This robot can provide the synchronous and asynchronous cooperation training for hemiplegic patients under the active and passive training mode. Based on the 7R linkage metamorphic mechanism, a rehabilitation training mechanism is designed to realize the coordinated movement of the upper and lower limbs. By the transmission system，the crank initial phase of the training mechanism can be adjusted, which can realize the synchronous or asynchronous movement of the left and right sides of the limbs. The kinematics analysis of the training mechanism is conducted, and it is proved theoretically that the mechanism can achieve the coordination movement of the limbs. The upper and lower computer control system is exploited by intelligent mobile terminal and microcontroller. Finally, the experiments are carried out on the prototype of the robot. The test results are as follows: The robot can realize cooperative motion of upper and lower limbs that the shoulder joint of the subject can move between -16.9° and 15.1°, and the knee joint can move between 121.5° and 172.5°; The robot can achieve passive training of synchronous and asynchronous limbs with the speed limit (0~6 r/min) and active training of asynchronous limbs with plantar pressure range (61.82~227 N). Synchronous and asynchronous training modes can be switched automatically.
2017, 38(10):2573-2580.
Abstract:
Moving object detection in indoor environment is a research hotspot in the field of computer vision. The dynamic background caused by moving the camera is a challenge in moving target detection. In this paper, a moving object detection algorithm based on ORBSLAM (oriented FAST and rotated BRIEFSimultaneous Localization and Mapping) is proposed. Firstly, the entire indoor environment is traversed using a moving camera, ORBSLAM is used to establish the 3D feature cloud model of the global background. Then, based on the environmental information, local 3D feature point cloud is built. By embedding the local 3D feature points into the global 3D background feature cloud, 3D Meanshift is applied to extracting the foreground points from the local 3D feature points. Finally, deep convolution neural network is utilized to confirm the moving target of the candidate region where the extracted foreground feature points are located. The experimental results on multi indoor scenes show that the proposed method has high detection accuracy and recall rate. The proposed moving object detection algorithm makes full use of the background information, and the depth convolution neural network is used to confirm candidate regions, which effectively improves the detection accuracy and robustness.
Moving object detection in indoor environment is a research hotspot in the field of computer vision. The dynamic background caused by moving the camera is a challenge in moving target detection. In this paper, a moving object detection algorithm based on ORBSLAM (oriented FAST and rotated BRIEFSimultaneous Localization and Mapping) is proposed. Firstly, the entire indoor environment is traversed using a moving camera, ORBSLAM is used to establish the 3D feature cloud model of the global background. Then, based on the environmental information, local 3D feature point cloud is built. By embedding the local 3D feature points into the global 3D background feature cloud, 3D Meanshift is applied to extracting the foreground points from the local 3D feature points. Finally, deep convolution neural network is utilized to confirm the moving target of the candidate region where the extracted foreground feature points are located. The experimental results on multi indoor scenes show that the proposed method has high detection accuracy and recall rate. The proposed moving object detection algorithm makes full use of the background information, and the depth convolution neural network is used to confirm candidate regions, which effectively improves the detection accuracy and robustness.
2017, 38(10):2508-2517.
Abstract:
Residual stress is an internal stress, which remains existing after eliminating the external force or uneven temperature field and other effects. This residual stress has a significant effect on the mechanical properties of the components, which can cause the warp, distortion, or even cracking in parts. Quantitative measurement of the residual stress is of great significance to change the fatigue life and prevent the brittle failure of the components. A variety of test methods of residual stress measurement. This paper introduces the principle and the research progress of destructive and nondestructive testing methods. The accuracy influencing factors and the improvement in measuring instruments are also investigated. The advanced instruments and their suppliers are surveyed on the market. Aiming at an improvement for the deformation of the blind hole and the borehole eccentricity, plastic area radius, internal microstructure, zero drift, measurement, the improved methods are put forward and the prospect of stress testing technology is also discussed.
Residual stress is an internal stress, which remains existing after eliminating the external force or uneven temperature field and other effects. This residual stress has a significant effect on the mechanical properties of the components, which can cause the warp, distortion, or even cracking in parts. Quantitative measurement of the residual stress is of great significance to change the fatigue life and prevent the brittle failure of the components. A variety of test methods of residual stress measurement. This paper introduces the principle and the research progress of destructive and nondestructive testing methods. The accuracy influencing factors and the improvement in measuring instruments are also investigated. The advanced instruments and their suppliers are surveyed on the market. Aiming at an improvement for the deformation of the blind hole and the borehole eccentricity, plastic area radius, internal microstructure, zero drift, measurement, the improved methods are put forward and the prospect of stress testing technology is also discussed.
2017, 38(10):2422-2429.
Abstract:
Current masterslave hand mapping in the humancomputer interaction has shortcomings such as lack of feedback, poor mapping accuracy and poor wearability. A masterslave mapping system based on fabric strain sensor and feedback mechanism is presented to address these issues. The strain sensitive unit is constituted of Lycra fabric surface spinning graphene/polyaniline composite conductive materials, in which the silver conductive adhesive is used as the electrode. The fabric strain sensor is layout in masterslave hand to construct 2×5 array. The gesture recognition model is obtained by combining stretch sensor information and the improved DH algorithm. The BP neural network is used to model the information of the masterslave strain sensor. Combining with the online optimization algorithm, the feedback mechanism of the strain sensor is introduced to realize the efficient and accurate mapping of the masterslave hand gestures, and the gesture mapping with feedback mechanism is established. The strain characteristics of the sensors are tested and the mapping accuracy of the gesture mapping system with and without feedback mechanism is compared. The experimental results indicate that the masterslave control system based on fabric strain sensor and feedback mechanism can improve mapping precision and wearability.
Current masterslave hand mapping in the humancomputer interaction has shortcomings such as lack of feedback, poor mapping accuracy and poor wearability. A masterslave mapping system based on fabric strain sensor and feedback mechanism is presented to address these issues. The strain sensitive unit is constituted of Lycra fabric surface spinning graphene/polyaniline composite conductive materials, in which the silver conductive adhesive is used as the electrode. The fabric strain sensor is layout in masterslave hand to construct 2×5 array. The gesture recognition model is obtained by combining stretch sensor information and the improved DH algorithm. The BP neural network is used to model the information of the masterslave strain sensor. Combining with the online optimization algorithm, the feedback mechanism of the strain sensor is introduced to realize the efficient and accurate mapping of the masterslave hand gestures, and the gesture mapping with feedback mechanism is established. The strain characteristics of the sensors are tested and the mapping accuracy of the gesture mapping system with and without feedback mechanism is compared. The experimental results indicate that the masterslave control system based on fabric strain sensor and feedback mechanism can improve mapping precision and wearability.
2017, 38(10):2415-2421.
Abstract:
Diseases or accidents often lead to hand dysfunction. At present, the assessment of hand rehabilitation mainly depends on the experience and judgment of doctors. Most of hand rehabilitation products on the market are complex and expensive. The daily training data for further diagnosis of patients cannot be recorded by the existed products. In this paper, a data glove with multisensors is designed for hand rehabilitation. The least square approach is adopted to correct the accelerometer and magnetometer. The complementary filter algorithm is used for sensor data fusion. Realtime hand gesture can be obtained and demonstrated in Unity 3D platform. Four kinds of gestures are captured and reconstructed by the proposed approach. It reveals that the data glove can effectively improve the hand rehabilitation procedure for both patients and doctors.
Diseases or accidents often lead to hand dysfunction. At present, the assessment of hand rehabilitation mainly depends on the experience and judgment of doctors. Most of hand rehabilitation products on the market are complex and expensive. The daily training data for further diagnosis of patients cannot be recorded by the existed products. In this paper, a data glove with multisensors is designed for hand rehabilitation. The least square approach is adopted to correct the accelerometer and magnetometer. The complementary filter algorithm is used for sensor data fusion. Realtime hand gesture can be obtained and demonstrated in Unity 3D platform. Four kinds of gestures are captured and reconstructed by the proposed approach. It reveals that the data glove can effectively improve the hand rehabilitation procedure for both patients and doctors.
2017, 38(10):2446-2452.
Abstract:
Aiming at the magnetic interference problem of threeaxis magnetometers in magnetic field measurement process, a new magnetic field measurement error compensation method based on damped particle swarm optimization (DPSO) algorithm is proposed. A comprehensive error compensation model for magnetometer error and geomagnetic interference field is established. DPSO algorithm and twostep method are used to carry out the parameter estimation work of nonlinear observation model, respectively. The scalar value of the proton magnetometer is taken as the true value and a nonmagnetic turntable is employed in the experiment for continuous sampling. Experiment results demonstrate that the DPSO algorithm has good suppression capability to magnetic field measurement error. After compensation, the root mean square errors (RMSE) are reduced from 1 025.7 to 60.304 4 and 581 nT for DPSO algorithm and twostep method, respectively. The results indicate that better compensation performance is achieved with DPSO algorithm, and the compensation accuracy is improved at least by one order of magnitude, which provides an efficient compensation method for magnetic field measurement error.
Aiming at the magnetic interference problem of threeaxis magnetometers in magnetic field measurement process, a new magnetic field measurement error compensation method based on damped particle swarm optimization (DPSO) algorithm is proposed. A comprehensive error compensation model for magnetometer error and geomagnetic interference field is established. DPSO algorithm and twostep method are used to carry out the parameter estimation work of nonlinear observation model, respectively. The scalar value of the proton magnetometer is taken as the true value and a nonmagnetic turntable is employed in the experiment for continuous sampling. Experiment results demonstrate that the DPSO algorithm has good suppression capability to magnetic field measurement error. After compensation, the root mean square errors (RMSE) are reduced from 1 025.7 to 60.304 4 and 581 nT for DPSO algorithm and twostep method, respectively. The results indicate that better compensation performance is achieved with DPSO algorithm, and the compensation accuracy is improved at least by one order of magnitude, which provides an efficient compensation method for magnetic field measurement error.
2017, 38(10):2469-2476.
Abstract:
Pallet picking is one of the important links of automated warehousing. An algorithm was proposed for estimating the localization and angle of pallet with lake information, based on 2D Lidar. It aims at improving the recognition pallet ability of forklift and the flexibility in automated warehousing. A detection model was built to define the geometry relationship between detection region the number of lidar point (detecting the pallet foot), the width of pallet foot and the resolution of Lidar. The algorithm extracted the lines as candidate pallet foot with the improved incremental algorithm and calculate the angle of pallet. Then the dynamic template was created and matched with sliding window, to calculated the position of the pallet. The result shows that the detect region was expend with smaller the threshold number of laser, longer the width of pallet foot and higher resolution of Lidar; the detect region met the result calculated based on the pallet detect model; error on x axis and y axis were ±60 mm mm and ±59 mm respectively; pallet angle error was . With the flexible pallet detecting algorithm, the requirement of localization of warehouse equipment and human was reduced and effect would be enhanced.
Pallet picking is one of the important links of automated warehousing. An algorithm was proposed for estimating the localization and angle of pallet with lake information, based on 2D Lidar. It aims at improving the recognition pallet ability of forklift and the flexibility in automated warehousing. A detection model was built to define the geometry relationship between detection region the number of lidar point (detecting the pallet foot), the width of pallet foot and the resolution of Lidar. The algorithm extracted the lines as candidate pallet foot with the improved incremental algorithm and calculate the angle of pallet. Then the dynamic template was created and matched with sliding window, to calculated the position of the pallet. The result shows that the detect region was expend with smaller the threshold number of laser, longer the width of pallet foot and higher resolution of Lidar; the detect region met the result calculated based on the pallet detect model; error on x axis and y axis were ±60 mm mm and ±59 mm respectively; pallet angle error was . With the flexible pallet detecting algorithm, the requirement of localization of warehouse equipment and human was reduced and effect would be enhanced.
2017, 38(10):2477-2483.
Abstract:
Nonlinear Vector Network Analyzer (NVNA) is a measurement setup for characterizing the nonlinear behavior of RF/Microwave devices. It uses a phase reference to achieve the phase spectrum measurement of a complex test target, and is mainly used for the power amplifier characterization and modeling at present. This paper presents an improved twophasereference NVNA setup, and investigates its performance for mixer characterization with nonlinear behaviors. This novel NVNA setup uses a “stepped” multisine as the primary phase reference, to achieve multiband measurement on a dense spectral grid, and uses a second “auxiliary” phase reference on a coarse grid to ensure the synchronization between multiband phase measurements. As a result, the signaltonoise ratio of the test bench can be largely improved, and a complex test target with multiband and “modulated multiharmonic” components can be characterized. According to the experimental results, the proposed method can guarantee a phase measurement stability of less than ±0.2° fluctuation, and achieve the phase and harmonic distortion analysis of a mixer under complex modulation.
Nonlinear Vector Network Analyzer (NVNA) is a measurement setup for characterizing the nonlinear behavior of RF/Microwave devices. It uses a phase reference to achieve the phase spectrum measurement of a complex test target, and is mainly used for the power amplifier characterization and modeling at present. This paper presents an improved twophasereference NVNA setup, and investigates its performance for mixer characterization with nonlinear behaviors. This novel NVNA setup uses a “stepped” multisine as the primary phase reference, to achieve multiband measurement on a dense spectral grid, and uses a second “auxiliary” phase reference on a coarse grid to ensure the synchronization between multiband phase measurements. As a result, the signaltonoise ratio of the test bench can be largely improved, and a complex test target with multiband and “modulated multiharmonic” components can be characterized. According to the experimental results, the proposed method can guarantee a phase measurement stability of less than ±0.2° fluctuation, and achieve the phase and harmonic distortion analysis of a mixer under complex modulation.
2017, 38(10):2492-2499.
Abstract:
In order to improve the modeling accuracy of piezoelectric ultra precision positioning stage, the hysteresis model of BacklashLike is used to describe the hysteresis characteristics of piezoelectric ultra precision positioning stage. The recursive least squares method based on genetic algorithm is utilized to identify the parameters of BacklashLike model. Combined with the dynamic characteristics of the piezoelectric ultra precision positioning stage, the secondorder dynamic hysteresis model is established for the piezoelectric ultra precision positioning stage. The experimental results show that, compared with the BacklashLike model under frequencies of 30 and 40 Hz, the maximum output displacement error of the dynamic hysteresis model decreases from 1.21 and 1.39 μm to 0.32 and 0.44 μm, and the maximum relative error are 3.5% and 4.4%. The average displacement error decreases from 0.53 and 0.76 μm to 0.17 and 0.21 μm, the average relative error decreases from 1.93% and 3.38% to 1.11% and 1.37%. The experimental results verify the dynamic hysteresis model and prove that the proposed model can not only reduce the system error caused by the dynamic characteristics of the piezoelectric ultra precision positioning stage, but also simulate the hysteresis characteristic and dynamic characteristic, and avoid the repeated model parameters identification under different frequencies. The accuracy of piezoelectric ultra precision positioning stage is improved in high frequency, fast, and large stroke location. This method is simple and has strong adaptability, easy to implement in engineering.
In order to improve the modeling accuracy of piezoelectric ultra precision positioning stage, the hysteresis model of BacklashLike is used to describe the hysteresis characteristics of piezoelectric ultra precision positioning stage. The recursive least squares method based on genetic algorithm is utilized to identify the parameters of BacklashLike model. Combined with the dynamic characteristics of the piezoelectric ultra precision positioning stage, the secondorder dynamic hysteresis model is established for the piezoelectric ultra precision positioning stage. The experimental results show that, compared with the BacklashLike model under frequencies of 30 and 40 Hz, the maximum output displacement error of the dynamic hysteresis model decreases from 1.21 and 1.39 μm to 0.32 and 0.44 μm, and the maximum relative error are 3.5% and 4.4%. The average displacement error decreases from 0.53 and 0.76 μm to 0.17 and 0.21 μm, the average relative error decreases from 1.93% and 3.38% to 1.11% and 1.37%. The experimental results verify the dynamic hysteresis model and prove that the proposed model can not only reduce the system error caused by the dynamic characteristics of the piezoelectric ultra precision positioning stage, but also simulate the hysteresis characteristic and dynamic characteristic, and avoid the repeated model parameters identification under different frequencies. The accuracy of piezoelectric ultra precision positioning stage is improved in high frequency, fast, and large stroke location. This method is simple and has strong adaptability, easy to implement in engineering.
2017, 38(10):2564-2572.
Abstract:
With the rapid growth of DLP projection technology in the late years, DLP projection technology has been gradually applied to numerous disciplines. Phaseshifting method often works with DLP projection technology due to its flexibility and high precision. As a nonlinear instrument, the projector could hardly project ideal fringe patterns, and could hardly achieve high projection speed. The binary defocusing provides a new solution for high speed and high precision measurement. This paper analyses the current status and development trend of 3D shape measurement by using projector defocusing at home and aboard. A survey is presented for the working principle of DMD, phaseshifting algorithms, unwrappingalgorithms, error compensation methods, the modulating methods for fringe pattern, the calibration methods and some of the details about projector defocusing further. This work can provide references for the researchers engaged in 3D shape measurement by using projector defocusing.
With the rapid growth of DLP projection technology in the late years, DLP projection technology has been gradually applied to numerous disciplines. Phaseshifting method often works with DLP projection technology due to its flexibility and high precision. As a nonlinear instrument, the projector could hardly project ideal fringe patterns, and could hardly achieve high projection speed. The binary defocusing provides a new solution for high speed and high precision measurement. This paper analyses the current status and development trend of 3D shape measurement by using projector defocusing at home and aboard. A survey is presented for the working principle of DMD, phaseshifting algorithms, unwrappingalgorithms, error compensation methods, the modulating methods for fringe pattern, the calibration methods and some of the details about projector defocusing further. This work can provide references for the researchers engaged in 3D shape measurement by using projector defocusing.
2017, 38(10):2500-2507.
Abstract:
A shielded cylinder microwave resonant cavity is adopted to realize the precise measurement of permittivity of microwave dielectric ceramics and other kinds of low and medium loss materials, the modematching technique is employed to realize the precise solution of the electromagnetic field in the cavity under dielectricloading condition, and the rigorous relationship between the cavity resonant frequency and material permittivity is obtained. The measurement results of various typical dielectric materials and the test data compared with those of several other methods show that compared with traditional methods, the proposed method achieves higher measurement accuracy with an estimated uncertainty as low as 0.1%; and the permittivity measurement range is extended wider. This method can not only measure the microwave dielectric ceramics with high permittivity, but also measure the low permittivity materials such as crosslinked polystyrene, teflon and etc. Furthermore, as the radiation loss is eliminated in shielded cavity, and the electric current loss in metal surface is restrained, a more accurate quality factor measurement can be realized for low loss materials; the lower limit of the loss angle tangent measurement range can be lower than 1×10-6. This method is suitable for the accurate permittivity measurement of various dielectric materials with the permittivity range of εr=1~100 and above, and the loss angle tangent of tanσ=1×10-3~1×10-6.
A shielded cylinder microwave resonant cavity is adopted to realize the precise measurement of permittivity of microwave dielectric ceramics and other kinds of low and medium loss materials, the modematching technique is employed to realize the precise solution of the electromagnetic field in the cavity under dielectricloading condition, and the rigorous relationship between the cavity resonant frequency and material permittivity is obtained. The measurement results of various typical dielectric materials and the test data compared with those of several other methods show that compared with traditional methods, the proposed method achieves higher measurement accuracy with an estimated uncertainty as low as 0.1%; and the permittivity measurement range is extended wider. This method can not only measure the microwave dielectric ceramics with high permittivity, but also measure the low permittivity materials such as crosslinked polystyrene, teflon and etc. Furthermore, as the radiation loss is eliminated in shielded cavity, and the electric current loss in metal surface is restrained, a more accurate quality factor measurement can be realized for low loss materials; the lower limit of the loss angle tangent measurement range can be lower than 1×10-6. This method is suitable for the accurate permittivity measurement of various dielectric materials with the permittivity range of εr=1~100 and above, and the loss angle tangent of tanσ=1×10-3~1×10-6.
