A synchronous localization and mapping method for vision-inertia-laser fusion mainly relates to the technical fields of multi-sensor fusion, SLAM and the like. In order to solve a problem that single sensor SLAM has low precision and is easy to lose in localization and mapping, the invention provides a robust high precision vision, inertia, laser radar fusion SLAM system. A tightly-coupled visual inertia odometer is further optimized through laser radar scanning and matching so as to obtain a more accurate localization result. And when a camera or a laser radar degenerates, and a visual inertia module or a scanning and matching module can not work normally, a system automatically integrates remaining workable modules to maintain stable pose estimation. In order to remove cumulative errors, loopback detection based on an appearance and neighboring matching based on point cloud are added, and then six-degree-of-freedom pose optimization is performed to maintain global consistency. In the invention, robust high-precision localization and mapping effects can be obtained.

Synchronous localization and mapping method for vision-inertia-laser fusion

The invention discloses an online calibration method of field end multi-harness laser radars. The online calibration method includes the steps that to-be-calibrated laser radars of the field end are marked; initial external parameters are designated to the to-be-calibrated laser radars; obstacles are designated to the to-be-calibrated laser radars, and reference parameters of the obstacles relative to the to-be-calibrated laser radars are recorded; the obstacles are scanned by the to-be-calibrated laser radars according to a preset frequency under the initial external parameters, obtained parameters of the obstacles relative to the to-be-calibrated laser radars are compared with the reference parameters, and whether the external parameters need to be updated or not is judged according to difference values between the parameters and the reference parameters; and the updated external parameters are stored as new initial external parameters. The laser radars are calibrated online, the external parameters are adjusted in real time, and thus the field end radars can still operate stably even under interference of own or external factors and can keep high precision always; the precise external parameters are input for positioning and sensing division, the requirements for precision of positioning and sensing division results are met, and smooth automatic parking is guaranteed.

Online calibration method of field end multi-harness laser radars

The invention discloses an external parameter calibration and precise positioning method based on under-mine multi-sensor fusion. External parameter calibration comprises the steps that an absolute position of each UWB anchor node in a laneway under a world coordinate system is acquired, and observation information of each sensor is acquired; a rotating external parameter between a laser radar sensor and an inertial measurement unit is determined, and whether a rotating calibration process is completed or not is judged automatically; a linear estimator based on a sliding window is constructed,a correlation state quantity is estimated, and whether the linear estimator is converged or not is judged automatically; estimated position coordinates of the UWB anchor nodes under a local coordinate system are utilized to be aligned with absolute position coordinates of the UWB anchor nodes under the world coordinate system, and external parameter transformation between the local coordinate system and the world coordinate system is determined; and all estimated parameter values are output. Through the method, online real-time or intermittent external parameter automatic calibration can be realized, and precise mapping and positioning are realized.

External parameter calibration and precise positioning method based on under-mine multi-sensor fusion

The invention provides a method and system for laser-IMU external parameter calibration. The method comprises steps of acquiring IMU measurement data and laser radar measurement data; carrying out IMUpre-integration of the obtained IMU measurement data, carrying out calculation to obtain an IMU pose transformation estimated value of the IMU relative to the IMU initial pose at the next moment, andaccording to the estimated value and an actual measurement value of the IMU at the next moment, obtaining an associated residual error associated with the data; processing measurement data of the laser radar, utilizing IMU pre-integration to obtain projection coordinates of reprojecting a plurality of laser radar points to a world coordinate system, and calculating a reprojection error from eachlaser radar point to a calibration target map; adopting a nonlinear least square method to iteratively optimize laser radar-IMU external parameter calibration so that the external parameter calibration result can be obtained. The method is advantaged in problems that in laser-IMU external parameter calibration, mechanical external parameters are not easy to obtain, manual measurement errors are large, and measurement is troublesome are solved, defects of the laser radar and the IMU are mutually overcome to a certain extent, and pose solving precision and the speed of the SLAM method can be improved.

Method and system for laser-IMU external parameter calibration

The embodiment of the invention relates to a real-time positioning method, device and system and a storage medium. The method comprises the steps: acquiring an inertia data set and a first laser pointcloud data set; extracting feature points from the first laser point cloud data set to obtain a second laser point cloud data set; according to the structural position relationship among the featurepoints of the first N frames of laser point cloud data in the second laser point cloud data set, the first frame of inertia data and the inertia data between the two adjacent frames of laser point cloud data, obtaining a second laser point cloud data set; determining the state quantity of each frame of laser point cloud data in the first N frames of laser point cloud data according to the laser point cloud data and the conversion relationship between the inertial data and the laser point cloud data; taking the first N frames as key frames, and iteratively updating the key frames in the currentsliding window; performing primary optimization on the state quantity corresponding to the key frame in the currently updated sliding window to obtain an optimized state quantity; fusing the optimized state quantity with the inertial data set to obtain a final pose quantity, and completing real-time positioning.

Real-time positioning method, device and system and storage medium

An asynchronous on-line calibration method for multi-sensor fusion is disclosed. The mutual conversion relationship between the coordinate systems of the three sensors are calibrated, and the measurement information of the plurality of sensors is unified into the same coordinate system, The traditional calibration method is limited to the calibration between two sensors, and requires strict time synchronization, so the calibration process is more complex. The invention calculates the motion of the laser radar, the camera and the inertial measurement unit (IMU) respectively, obtains the motionof different sensors in the same time interval by using linear interpolation, and finally obtains the external rotation between two sensors by aligning the rotation sequence of the three sensors. Theinvention can obtain more accurate external orientation between the lidar, the camera and the inertial measurement unit (IMU), and provides initial value for subsequent calibration.

An asynchronous on-line calibration method for multi-sensor fusion

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Synchronous localization and mapping method for vision-inertia-laser fusion

An asynchronous on-line calibration method for multi-sensor fusion