47results about How to "Reduce drift error" patented technology

The invention discloses a simultaneous localization and mapping (SLAM) method for an unmanned aerial vehicle based on mixed vision odometers and a multi-scale map, and belongs to the technical field of autonomous navigation of unmanned aerial vehicles. According to the SLAM method, an overlooking monocular camera, a foresight binocular camera and an airborne computer are carried on an unmanned aerial vehicle platform; the monocular camera is used for the visual odometer based on a direct method, and binocular camera is used for the visual odometer based on feature point method; the mixed visual odometers conduct information fusion on output of the two visual odometers to construct the local map for positioning, and the real-time posture of the unmanned aerial vehicle is obtained; then theposture is fed back to a flight control system to control the position of the unmanned aerial vehicle; and the airborne computer transmits the real-time posture and collected images to a ground station, the ground station plans the flight path in real time according to the constructed global map and sends waypoint information to the unmanned aerial vehicle, and thus autonomous flight of the unmanned aerial vehicle is achieved. Real-time posture estimation and environmental perception of the unmanned aerial vehicle under the non-GPS environment are achieved, and the intelligent level of the unmanned aerial vehicle is greatly increased.

The invention discloses a range finding method of a pulsed laser rangefinder. The pulsed laser rangefinder comprises a pulsed laser, a photoelectric detector, an amplifier, a double-channel comparator, a time digital converter TDC and a measurement control module, wherein the photoelectric detector is connected with the amplifier; an output end of the amplifier is connected with two positive input ends of the double-channel comparator; two different discriminating threshold levels are respectively input to two positive input ends of the double-channel comparator; an output end of the double-channel comparator is connected with the time digital converter TDC; and the measurement control module is respectively connected with the time digital converter TDC and the pulsed laser; and by using the range finding method disclosed by the invention, the drift error can be reduced and the range finding accuracy can be improved.

A battery voltage detector includes, but is not limited to: a voltage detection circuit; and a voltage processor. The voltage detection circuit includes, but is not limited to: a capacitor configured to be charged by a battery cell; a pair of output terminals; an output switch; and a voltage processor. While the capacitor is charged, the output switch is configured to be off-state and insulate the capacitor from the pair of the output terminals. After the capacitor is charged, the output switch is configured to be on-state and connect the capacitor to the pair of the output terminals. The voltage processor is configured to obtain, as a cell voltage, a voltage between the output terminals of the voltage detection circuit while the output switch is on-state. A high-potential output terminal of the pair of the output terminals is connected to a power line via a pull-up resistor.

The invention belongs to the technical field of the laser ranging, and specifically relates to signal echo rate real-time controllable satellite laser ranging system, method and device. The system further comprises a laser device, a laser energy control system, an echo signal comprehensive simulation system, an transmitter-telescope, a dominant wave sampling circuit, a counter, a receiving telescope, a dominant wave sampling circuit and the counter; the laser device is used for producing light pulse and connected with the laser energy control system; the produced light pulse enters the laserenergy control system; the laser energy control system is connected with each of the echo signal comprehensive simulation system, the transmitter telescope and the dominant wave sampling circuit; thedominant sampling circuit is connected with the counter; and the counter is connected with the receiver telescope. The system precision is improved, and the system stability and effectiveness are improved.

The present invention relates to an intelligent agricultural machine optimization mu-counting method based on the internet of things. A lower computer collection mu-counting data is equal to the effective work time multiplied by the real-time vehicle speed multiplied by the agricultural machine work effective width and is calculated; the number of mu areas of the upper computer is equal to the difference of an agricultural machine treading track route and a twisted dragon stop track route multiplied by the agricultural machine work effective width, and the GPS mu-counting data is calculated; and the upper computer compares the lower computer collection mu-counting data and the GPS mu-counting data to record a server. The intelligent agricultural machine optimization area-metering method based on internet of things employs the lower computer to collect and calculate the area-metering data, and the upper computer employs the number of the mu areas reported by the lower computer as a main basis and corrects the obtained correction mu-counting data according to the GPS, and therefore the mu-counting precision is high and the drift error of the GPS location points is small. Besides, the lower machine collection mu-counting data is used for correction of the GPS mu-counting data calculated by the upper computer so as to avoid the conditions of the work track overlapping or the polygonon self intersection formed by the work tracks.

The invention relates to an indoor trajectory tracking method with self-adaptive step length. The indoor trajectory tracking method comprises the following steps: setting the initial speed and the final speed of every step of walking are zero, judging whether to be in a walking state, if so, collecting the number of accelerations in every step, and calculating to obtain the step length of the first step according to the accelerations and the sampling time of the accelerations; by combining with the direction of every step, carrying out vector superposition on every step, and thus obtaining the motion trajectory. The indoor trajectory tracking method has the advantages that by adoption of indoor-pedestrian trajectory tracking based on an MEMS inertial sensor, the accuracy of gesture detection of an inertial navigation positioning system is improved and the errors of the step-length calculation are reduced, so that the accuracy of navigation positioning is improved; and by adoption of the self-adaptive mechanism, the step length of every step can be accurately calculated, the accuracy of navigation positioning can be improved and the promotion of inertial navigation positioning application can be enhanced.

The invention discloses a wireless sensor network data acquisition method and system based on broadcast synchronization, and the method specifically comprises: a host node broadcasting synchronizationheaders to all network sensor nodes, and the network sensor nodes carrying out the calibration of respective sampling timers according to the time calibration information; determining or updating therespective sampling rate according to the query period and the respective sampling rate; according to the time slot distribution information, packaging the sampling data according to a sampling timesequence and sending the sampling data to a host node in a datagram form; and the host node analyzing the content of each datagram, reproducing the data of each network sensor node, and transmitting the data to a comprehensive control computer or a remote measurement system. Whole network management and data collection are realized by adopting the host broadcast message, the method is simple and reliable, the data synchronization precision is high, the data reported in each period are equal in length, the hardware processing is convenient, the sampling rate can be dynamically changed, and theproblems in the prior art are solved.

The invention discloses a method for obtaining the displacement of a space mouse. The method comprises the following steps of setting a first reference coordinate system of the space mouse on a display screen, and recording coordinates of the space mouse in the first reference coordinate system; setting a second reference coordinate system of the space mouse in a stereoscopic space; detecting a course angle, a pitch angle and a roll angle, which are relative to the second reference coordinate system, of the space mouse; mapping the course angle, the pitch angle and the roll angle of the space mouse to the first reference coordinate system, and obtaining corresponding state quantities of the space mouse in the first reference coordinate system; and sending the state quantities of the space mouse in the first coordinate system to a host computer in real time. According to the method disclosed by the invention, by combining the space mouse with a navigation posture theory, the displacement of the space mouse can be detected and mapped to the display screen, and thus the function of an existing mouse can also be realized by the space mouse without depending on a reflection platform.

The invention provides a pose estimation method of a mobile robot and a computer readable storage medium. The method comprises the following steps: acquiring multi-source sensor data, the multi-source sensor data comprising: an image acquisition device acquires a ground scene image, an inertial measurement unit acquires ground data, and a wheel encoder acquires ground data; initializing pose estimation of the mobile robot according to scene image detection scene dynamics; collecting ground data by an inertial measurement unit, collecting ground data by a wheel type encoder, and calculating a prior estimator of a state vector of the mobile robot at the current moment and a corresponding covariance transfer matrix through a state transition equation; and iterating the prior estimator of the state vector at the current moment and the corresponding covariance matrix according to the scene image until convergence to complete filtering update. The data acquired by the image acquisition equipment, the data acquired by the inertial measurement unit and the data acquired by the wheel type encoder are used as the input data of the pose estimation and are combined, so that the advantages are complementary, and the tightly coupled pose estimation data can be obtained.

The invention discloses an attitude obtaining method of a micro-inertia sailing attitude reference system. The method comprises the following steps: 1, obtaining an attitude angle initial value of a carrier according to carrier acceleration information collected by a sensor and three-dimensional magnetic field intensity information, and obtaining a system attitude matrix at the current moment according to the attitude angle initial value; 2, obtaining gyroscopic drift error compensation amount according to the system attitude matrix, and conducting compensation on data output by a gyroscope according to a gyroscopic drift error adjusting model; 3, updating a system attitude matrix of the next moment according to data which are output by the gyroscope and obtained after compensation, and obtaining an attitude angle of the carrier according to the updated attitude matrix. By means of the attitude obtaining method, the problems that a sailing attitude reference system is low in attitude calculation precision and cannot meet engineering application due to the fact that an MEMS gyroscope is low in precision and large in shift error are solved; the MEMS gyroscope can be inhibited from shifting, and attitude calculation precision can be improved; high engineering application value and promotional value are achieved.

The invention provides a delay time measuring circuit for an optical fiber delay line. Narrow-pulse lasers emitted by a laser unit of a laser pulse transmitting part are divided into two paths through an optical fiber branching device. A laser pulse receiving part comprises photoelectric detectors, automatic gain control circuits and moment discriminator circuits, wherein the photoelectric detectors, the automatic gain control circuits and the moment discriminator circuits are all arranged in two same sets. One path of lasers directly enter the first photoelectric detector, and the other path of narrow-pulse lasers enter the second photoelectric detector through the optical fiber delay line to be measured. Two paths of converted electric signals are connected to the corresponding moment discriminator circuits through the corresponding automatic gain control circuits respectively. Output of the first moment discriminator circuit and output of the second moment discriminator circuit are connected to a start channel and a stop channel of a time digital processing module respectively, and the output of the second moment discriminator circuit is connected to a master control module connected with an upper computer. The time different between the timing start signals and the timing termination signals is acquired through the digital processing module, the timing start signals and the timing termination signals are converted into digital signals, the digital signals are transmitted to the upper computer to be displayed through the master control module, and a measurement result is output. By the adoption of the delay time measuring circuit, picosecond-level delay time measurement is achieved, accuracy and the refresh rate are high, and implementation is easy.

The invention discloses a compensation method for MEMS (Micro-electromechanical Systems) gyroscopic drifting errors based on accelerometer coupling. The compensation method comprises the following steps: (1) a gyroscopic drifting error amount delta omega (t) is obtained according to carrier accelerated speed information which is measured in real time according to an accelerometer; (2) an error adjusting model omega C (t)=delta omega P+delta omega I is established; a first error adjusting control amount delta omega P and a second error adjusting control amount delta omega I are obtained according to formulas delta omega P=KP*delta omega (t) and delta omega I =delta omega I+KI*dt*delta omega (t), and the gyroscopic drifting error amount delta omega (t); the first error adjusting control amount delta omega P and the second error adjusting control amount delta omega I are substituted into the error adjusting model to obtain a gyroscopic drifting error compensation amount omega C (t); (3) error compensation is carried out on gyroscopic data according to the gyroscopic drifting error compensation amount to obtain compensated gyroscopic information. According to the compensation method disclosed by the invention, the problems that the posture resolving precision is low and engineering applications cannot be met caused by low gyroscopic precision of MEMS and large accumulated drifting errors are solved; the MEMS gyroscopic drifting can be inhibited and the posture resolving precision is improved; the compensation method has high engineering application values and promotional values.

The invention discloses a comb electrode. A signal processing unit is electrically contacted with a life body. The comb electrode comprises an electrode plate and a plurality of electrode posts, wherein the plurality of electrode posts are convexly arranged on the electrode plate and comprises at least one main electrode post and at least one reference electrode post; and the plurality of electrode posts are electrically connected with the signal processing unit. Therefore, during the electric signal transmission on the main electrode posts, reference potentials (levels) of the reference electrode posts are compared, so that the aim of reducing the level drift error is fulfilled.

The invention relates to the technical field of piezosurgery dynamic impedance feedback, and discloses a piezosurgery dynamic impedance feedback method, the specific circuit comprises a main power supply, an HMI human-computer interaction module, an MCU, a numerical control excitation power supply, a matching circuit consisting of a matching inductor and a matching capacitor, a sampling circuit composed of a resistance-capacitance voltage division circuit and a Hall sensor, a gain amplification circuit, a band-pass filter circuit, a level adjustment circuit, an in-amplitude phase detection andlow-pass filter circuit and a RMS true virtual value circuit. The resistance-capacitance circuit is adopted to divide voltage and sample the Hall sensor, so that the interference of the sampled original signal is reduced, no extra component is connected in series into the matching circuit, the acquired original signal is more accurate, the signal precision of the signal processing circuit is ensured, the drift error is reduced, the band-pass filter circuit is introduced, and the final signal is more accurate and cleaner, the corrected resonant frequency is calculated by adopting an error PIDalgorithm, and the frequency tracking speed is higher.

The invention relates to a hemispherical harmonic oscillator parameter identification method. The method comprises the steps of self-excitation angular velocity application, gyroscope internal control force signal output, gyroscope error evolution model and harmonic oscillator parameter inverse solution identification model construction, single-axis forward and reverse rotation self-calibration and the like. A set of rate HRG control system simulation model with a self-excitation control module is constructed, and self-excitation angular velocity application, gyroscope error self-calibration and harmonic oscillator parameter autonomous identification under two inverse solution models can be completed. According to the method, the harmonic oscillator non-equal damping error amplitude and the main shaft deflection angle can be rapidly and autonomously identified by utilizing self-excitation in any stage of a full life cycle in a gyroscope working environment, and the method is a new method for rapidly and autonomously identifying the harmonic oscillator non-equal damping error amplitude and the main shaft deflection angle by utilizing various methods and means, such as self-excitation-based rate/rate integral HRG self-compensation (force compensation), non-equal damping error suppression and resonance mode drift error reduction. The output angular velocity/angular increment precision of the gyroscope is improved, application conditions are created, and a solution is provided.

The invention discloses an RGB-D visual SLAM method based on dot-line features. The RGB-D visual SLAM method comprises the following steps: S1, calibrating internal parameters of an RGBD camera; s2, performing line feature extraction; s3, acquiring an initial transformation pose of the camera; s4, performing linear projection from the key frame to the current frame; s5, forming an error function of the visual odometer module; s6, performing iterative optimization of the initial transformation pose of the current frame of camera and pose solution of the current frame of camera; s7, judging thekey frame; s8, performing local BA optimization; s9, performing loop detection; s10, performing repositioning; s11, constructing a map; s12, outputing a result. According to the SLAM method provided by the invention, the RGB-D camera is used as image acquisition equipment, points and edge lines of an object in a scene are used as positioning features to realize SLAM, and the method has relativelygood accuracy in challenging scenes such as low semantics and low texture.

The invention relates to an MEMS inertial positioning system course optimization method based on a redundancy technology, which uses a plurality of low-precision sensors to replace a high-precision sensor under the existing MEMS sensor technology level, thereby achieving the purposes of improving the reliability and the positioning precision of the system and reducing the cost of the system at the same time. A device redundancy technology is utilized, gyroscopes are configured at different positions, according to data measured by a sensor, the acceleration of a carrier in the x-axis direction, the y-axis direction and the z-axis direction is calculated, different weights are set according to the acceleration, a system state equation and an observation equation of the redundant accelerometer are established through Kalman filtering, and the system state equation and the observation equation of the redundant accelerometer are calculated. A sensor data fusion model of the redundant system is obtained by combining a configuration matrix of the sensor; and finally, the data is fused according to the weight to solve the three-axis optimal angular velocity of the carrier. Weighted fusion is carried out according to the acceleration of each gyroscope sensitive shaft, the drift error influence caused by external acceleration impact and vibration on the gyroscope is reduced, and the course precision of the system is effectively improved.

The invention provides a multi-machine cooperative target high-precision positioning system and method based on visual navigation. The system comprises a visual inertial odometer module which is used for fusing the results of visual measurement and inertial measurement through a sliding window filter, stably tracking the pose of an unmanned plane, and obtaining a ground surface point cloud at the same time; a scene matching module which is used for analyzing the surface flatness by analyzing the elevation distribution of the point cloud, and observing the pose of the unmanned aerial vehicle in a geographical environment by adopting scene matching for a flat point cloud; a terrain matching module which is used for analyzing the surface flatness by analyzing the elevation distribution of the point cloud, and observing the pose of the unmanned aerial vehicle in a geographical environment by adopting terrain matching for a fluctuating point cloud; and a reference map management module which is used for realizing storage and effective retrieval of geographic information by utilizing a grid and quadtree mixed index structure, providing map data for scene matching and terrain matching, and extracting stable structures in a real-time map and a reference map through optimized line segments.