WO2022193106A1 - 一种通过惯性测量参数将gps与激光雷达融合定位的方法 - Google Patents
一种通过惯性测量参数将gps与激光雷达融合定位的方法 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
Definitions
- the invention belongs to the field of positioning of unmanned aerial vehicles, and relates to a method for positioning by combining GPS and laser radar based on IMU.
- UAV is an unmanned aircraft operated by radio remote control equipment and self-provided program control device.
- the positioning technology of UAV is the basis of UAV safety and operation.
- the NDT algorithm is a kind of use of the existing high-precision Real-time measurement data of maps and lidars to achieve high-precision positioning technology for point cloud matching; the inertial measurement unit (IMU) is used to obtain the rotation angle and acceleration of the drone in all directions. Physical quantities can be considered accurate.
- lidar NDT algorithm needs to map the usage scene in advance, and various changes will occur over time, and the actual situation of the pre-established map and positioning may appear. deviation.
- the NDT algorithm it is difficult for the NDT algorithm to perform feature matching at this time, and an abnormal situation of localization loss occurs. In such a case, the positioning obtained by the NDT algorithm is not credible. Therefore, in some special situations, the reliability of single sensor positioning cannot be guaranteed.
- the purpose of the present invention is to solve the above-mentioned problems that may occur when using the laser radar NDT algorithm and the GPS sensor for positioning, and the physical quantity obtained by the IMU in a short time is reliable, and proposes a GPS and laser radar NDT using IMU.
- Algorithms are combined for positioning.
- the system first independently measures whether the data obtained by GPS or NDT is reliable, and uses the IMU real-time data to automatically select whether to use the data obtained by GPS or the data calculated by the lidar NDT algorithm as the final positioning data.
- the positioning data obtained by man-machine can be applied to some special environments to improve the robustness of positioning.
- the present invention comprises the following steps:
- Step 1 Pre-judgment of GPS/NDT coordinate feasibility: Obtain the acceleration a obtained by the IMU. If a is greater than the given threshold ⁇ , it is considered that the aircraft is moving. At this time, the following situations are discussed:
- step 2 move to step 2, and use IMU data fusion to decide the data obtained by GPS and NDT; if the GPS positioning obtained by the above rules is inaccurate, but the NDT data is tentatively accurate, then the NDT positioning coordinates are received as Return the coordinates; in the same way, if the NDT positioning is inaccurate and the GPS data is tentatively accurate, the GPS positioning coordinates are received as the returned coordinates; if the GPS and NDT positioning are both inaccurate, the positioning data returned at the last moment and the IMU real-time are used.
- the result of the acceleration estimation is used as the positioning value at this moment, and the steps are as follows:
- Step 1.1 Obtain the positioning data of the last time t 0 And the acceleration in three directions measured in real time by the IMU
- Step 1.2 According to the formula Estimate the movement displacement from time t 0 to time t 1 , namely:
- Step 1.3 According to The positioning data at time t 1 estimated by the IMU can be obtained, namely:
- Step 2 Data conversion, convert the GPS latitude and longitude coordinates obtained by the drone into three-dimensional coordinates in the NDT mapping coordinate system.
- Step 3 Let the drone take off at a distance of about 2m, and calculate the surface information and initial coordinate points of the drone.
- Step 4 Taking ⁇ t as the time interval, obtain the GPS positioning coordinates and lidar NDT positioning coordinates that are continuously updated within this time interval.
- This step mainly includes:
- Step 4.1 in the ⁇ t time interval after a certain time t 0 , obtain a set of GPS positioning coordinates and a set of lidar NDT positioning coordinates respectively. are recorded as and
- Step 4.2 coordinate data optimization.
- For the GPS coordinate data and NDT coordinate data groups divide them into two groups of equal numbers respectively.
- m and k are the number of GPS and NDT coordinates obtained in the ⁇ t time interval, respectively.
- Step 5 Calculate the average acceleration in three directions within ⁇ t using the GPS and NDT coordinates of two adjacent time instants t 0 and t 0 + ⁇ t, respectively. For the coordinates of two adjacent instants t 0 and t 0 + ⁇ t and Calculated from the displacement acceleration formula The acceleration values in three directions at time t 0 + ⁇ t, namely time t 1 , obtained by GPS and NDT can be calculated respectively.
- the positioning coordinates obtained by GPS are:
- the difference vector of displacement is:
- Step 6 Coordinate conversion, convert the obtained GPS and NDT acceleration from the NDT coordinates to the UAV body axis coordinate system. Get the converted acceleration value and
- Step 7 Calculate the deviation to obtain the calibration positioning.
- This step mainly includes:
- Step 7.1 obtain the acceleration of the IMU in three directions at time t 1
- Step 7.2 find the difference vector between the two sets of accelerations calculated by GPS and NDT with respect to the acceleration of the IMU, namely and
- Step 7.3 calculate the Euclidean norm of the difference vector, and obtain the acceleration difference norm of GPS and NDT as:
- Step 8 Given Threshold Compare the deviation and obtain the calibration positioning.
- the difference norm obtained in step 7 is divided into the following four cases:
- Figure 1 is a model diagram of the NDT and GPS integrated positioning algorithm
- Figure 2 is a flow chart of NDT and GPS comparative positioning
- the maximum number of iterations will be set for it to ensure that when the optimal value cannot always be matched, it will avoid falling into an infinite loop. Therefore, at the initial moment, if the return value of the NDT algorithm is returned when the maximum number of iterations is reached, there may be similar eigenvalues, obstacles occluded, etc. At this time, it is difficult for the NDT algorithm to perform feature matching, and the location is lost. . In this case, the accuracy of NDT positioning will be negated. That is, the number of iterations n when the NDT registration is successful is obtained. If n is exactly the maximum number of iterations of the point cloud parameters, it is considered that there is a problem in the matching of the NDT, and the accuracy of the NDT positioning is denied.
- the IMU can be used to determine whether the aircraft is in a moving state.
- the acceleration measured by the IMU in a short time interval is reliable. If the acceleration measured by the IMU is greater than a given threshold, it is considered that the aircraft is moving at this time. At this time, if the NDT or If the coordinates returned by GPS remain unchanged, the coordinates are considered inaccurate.
- the three-dimensional coordinates unified by GPS and NDT can be obtained as:
- the body coordinate system of the UAV is (i, j, k), and the coordinate system of NDT mapping is (I, J, K) as the global coordinate system, then the direction cosine matrix (DCM) of the UAV at this time for:
- the UAV In order to obtain the direction cosine of the UAV, according to the meter-level accuracy of GPS, consider letting the UAV take off at a distance of 2m to calculate its flight direction.
- the initial point (x 0 , y 0 , z 0 ) of the UAV is obtained by GPS, the movement point reached after taking off 2m is (x 1 , y 1 , z 1 ), and the trajectory vector is (x 1 -x 0 , y 1 -y 0 , z 1 -z 0 ), according to the above information, the flight direction of the UAV can be estimated, that is, the direction cosine vector is:
- the probability density function of the point cloud in the grid is calculated: when the number of points in the grid is greater than 5, the mean vector of each point cloud is:
- the covariance matrix of the point cloud in this grid is:
- the probability density function of the point cloud in the grid is:
- Eigenvectors of the covariance matrix It can represent the orientation of the drone.
- the covariance matrix does not have an inverse matrix, and its normal distribution is degenerate.
- the cosine vector is used to estimate its direction, namely:
- NDT transformation can be applied for localization.
- the optimized positioning coordinates of the two times obtained by GPS are:
- the difference vector of displacement is:
- the GPS and NDT accelerations obtained at time t1 are converted from the NDT coordinates to the UAV body axis coordinate system. Get the converted acceleration value and And obtain the acceleration of the onboard IMU in three directions at this moment in real time
- the actual acceleration value of the IMU is used to arbitrate whether the coordinates given by GPS and NDT deviate from the actual value, and the difference vector between the two sets of accelerations of GPS and NDT with respect to the acceleration of IMU is calculated, that is, and By calculating the Euclidean norm of the difference vector to measure the degree of deviation of the difference, the difference norm of GPS and NDT are calculated as:
Abstract
一种为民用无人机提供更可靠定位的方法，利用多传感器融合的思想，将IMU获取的惯性测量参数、GPS定位数据与激光雷达NDT算法计算数据相结合实现高可靠性定位。解决了无人机在一些环境下GPS信号弱，可能出现的GPS数据丢失以及无人机运动剧烈，或者现场发生变化与三维地图不一致导致的激光雷达扫描匹配失败的问题。确保无人机在能够获取当前的定位信息的情况下，能够采用更精确的定位数据。首先建立GPS与激光雷达的坐标关联，以进行对定位的一致描述。对GPS定位数据和激光雷达NDT算法匹配数据进行预判断，对不可靠定位数据进行初步筛除。然后利用IMU获取的惯性测量参数来比较两个定位数据的可靠性，决策出更可靠的定位数据。当GPS和激光雷达的数据均不可靠时，则利用IMU和上一时刻的定位数据来估计当前的定位值，保证无人机在特殊环境下的可靠定位。
Description
本发明属于无人机的定位领域，涉及一种基于IMU将GPS与激光雷达结合进行定位的方法。
无人机是利用无线电遥控设备以及自备的程序控制装置操纵的不载人飞行器，无人机的定位技术是无人机安全和操作的基础。在无人机定位的实际工程中，我们可以使用GPS定位系统来获取无人机的定位数据；应用激光雷达NDT算法获取无人机的定位数据，NDT算法即是一类利用已拥有的高精度地图和激光雷达实时测量数据来实现高精度定位的技术进行点云匹配；通过惯性测量单元(IMU)获取到无人机的旋转角度和各方位的加速度，IMU在较小时间间隔内测量到的物理量可认为是准确的。
当无人机处于室内、隧道、金属顶棚的交通工具、高楼大厦林立的城市街区、甚至密林内等上空有遮蔽的地方时，就几乎接收不到卫星信号，从而导致GPS信号丢失，此时的GPS定位是不准确的。与此同时，尽管激光雷达定位的精度很高，但使用激光雷达NDT算法需要提前对使用场景进行建图，经过时间推移会发生各种变化，预先建立的地图与定位时的实际情况可能会出现偏差。与此同时，在一些特征值相似的环境下，或者当前环境被突发的障碍物遮挡，此时的NDT算法难以进行特征匹配，出现定位丢失的异常情况。在这样的情况下，NDT算法得到的定位是不可信的。因此，在某些特殊情景下，单传感器得到定位的可靠性不能得到保证。
发明内容
本发明的目的在于，针对上述在利用激光雷达NDT算法和GPS传感器进行定位时可能会出现的问题，利用IMU在短时间的得到的物理量具有可靠性，提出一种利用IMU将GPS与激光雷达NDT算法相结合进行定位的方法，系统首先自主衡量GPS或NDT得到的数据是否可靠，并利用IMU实时数据自选择是否采用GPS获取的数据或激光雷达NDT算法计算得到的数据作为最终定位数据，使无人机得到的定位数据可以适用于一些特殊环境，提高定位的鲁棒性。
为实现上述目的，本发明包括以下步骤：
步骤1.GPS/NDT坐标可行性预判断：获取IMU得到的加速度a，如果a大于给定阈值ε，则认为飞机正在移动，此时分以下情况进行讨论：
1.GPS传来的位置信息没有改变，则认为GPS定位不准确。
2.NDT计算出的位置信息没有改变，则认为NDT定位不准确。
3.NDT实际迭代次数返回值恰为建立点云参数时的最大迭代次数，则认为NDT未进行精准匹配，NDT此时得到的定位信息不准确。
若以上三种情况均不存在，则转移到步骤2，利用IMU数据融合决策GPS和NDT得到的数据；若由上述规则得到GPS定位不准确，而NDT数据暂定准确，则接收NDT定位坐 标作为返回坐标；同理若NDT定位不准确，而GPS数据暂定准确，则接收GPS定位坐标作为返回坐标；若得到的GPS和NDT定位均不准确，则利用上一时刻返回的定位数据和IMU实时加速度估算的结果作为该时刻的定位值，步骤如下：
步骤1.1获取上一时刻t
0的定位数据
以及IMU实时测量到的关于三个方向的加速度
步骤1.2根据公式
估算出由t
0时刻到t
1时刻的运动位移大小，即：
步骤1.3根据
即可得到由IMU估算的t
1时刻的定位数据，即：
步骤2.数据转换，将无人机获取到的GPS经纬坐标转换为NDT建图坐标系下的三维坐标。
步骤3.令无人机起飞约2m的距离，计算无人机的表面信息和初始坐标点。
步骤4.以Δt为时间间隔，获取在此时间间隔内不断更新的GPS定位坐标和激光雷达NDT定位坐标。
本步骤主要包括：
步骤4.1，在某时刻t
0后的Δt时间间隔中，分别获取到一组GPS定位坐标和一组激光雷达NDT定位坐标。分别记为
和
步骤4.2，坐标数据优化，对于GPS坐标数据和NDT坐标数据组，分别将它们划分成等数量的两组，对于第一组，用空间直线方程Ax+By+Cz＝0来拟合这组定位坐标数据，运用梯度下降法得到一组A
1、B
1、C
1，使得坐标点到直线方程的距离d最小。即
求出直线A
1x+B
1y+C
1z＝0在xOy平面的投影方程a
1x+b
1y＝0。同理，获取另一组坐标点的拟合方程A
2x+B
2y+C
2z＝0及它在xOy平面的投影方程a
2x+b
2y＝0。联立两个投影方程，获取到其交点(x,y)作为无人机在t
0后一时刻t
1的平面坐标。此步骤下，可得到在(t
0+Δt)时刻的下GPS和NDT优化后的坐标，分别为：
m、k分别为Δt时间间隔内获取到的GPS和NDT的坐标数量.
步骤5.用相邻两个时刻t
0和t
0+Δt的GPS和NDT坐标分别计算Δt内的三个方向的平均加速度。对于相邻两个时刻t
0和t
0+Δt的坐标
和
由位移加速度计算公式
可以分别计算出由GPS和NDT得到的在t
0+Δt时刻即t
1时刻的三个方向的加速度值。
在t
0和t
1时刻，通过GPS得到的定位坐标分别为：
位移之差向量为：
根据
可以求解出由GPS得到的在t
1时刻的加速度
即：
同理，由NDT得到的在t
1时刻三个方向的加速度为：
步骤6.坐标换算，将得到的GPS、NDT加速度由NDT坐标换算为无人机机体轴坐标系。得到换算后的加速度值
和
步骤7.计算偏差获取校准定位，本步骤主要包括：
步骤7.1，获取到t
1时刻的IMU关于三个方向的加速度
步骤7.2，求出GPS、NDT计算出的两组加速度关于IMU加速度的差值向量，即
和
步骤7.3，计算差值向量的欧几里得范数，得到GPS和NDT的加速度差值范数分别为：
步骤8.给定阈值
比较偏差大小，获取校准定位。对于步骤7中获取到的差值范数，分为以下的4种情况：
1.如果
且
则认为GPS和NDT算法均比较稳定，因为激光雷达可以达到更高的精确度，因此取激光雷达获得的坐标作为最终定位坐标，取p＝p
N＝(x
N,y
N,z
N)作为校准坐标。
2.如果
且
则认为NDT获取到的定位偏差较大，取p＝p
G＝(x
G,y
G,z
G)作为校准坐标。
3.如果
且
则认为GPS获取到的定位偏差较大，取p＝p
N＝(x
N,y
N,z
N)作为校准坐标。
4.如果
且
则认为GPS和NDT获取到定位均可能存在偏差，取由步骤1介绍的利用IMU和上一时刻坐标估计出的t
1时刻坐标p
I，利用NDT和IMU的融合坐标作为校准坐标，即取
作为校准坐标。其中，β为NDT的点云匹配率，且α+β＝1
图1为NDT和GPS综合定位算法模型图
图2为NDT和GPS比较定位的流程图
算法实现的详细说明
1.在激光雷达的NDT算法中，配置点云参数时，将为其设置最大迭代次数，以保证当始终无法匹配到最优值时避免陷入死循环。因此，在初始时刻，如果NDT算法的返回值是以到达最大迭代次数的情况进行返回，则可能存在特征值相似、障碍物遮挡等情况，此时NDT算法难以进行特征匹配，出现定位丢失的情况。在这种情况下，将否定NDT定位的准确性。即，获取NDT配准成功时的迭代次数n，如果n恰为点云参数的最大迭代次数，则认为NDT的匹配出现问题，否定NDT定位的准确性。
2.利用IMU可以判别出飞机是否处于移动状态，IMU在短时间间隔内测量出的加速度是可靠的，如果IMU测量的加速度大于给定阈值，则认为此时飞机正在移动，此时如果NDT或GPS返回的坐标不变，则认为坐标不准确。
3.GPS经纬度与NDT三维坐标的转换
设
分别为地理坐标中的经度和纬度，对于地固坐标系，P与三维坐标P
u的对应关系为：
其中R是地球半径。
设NDT建图时坐标轴原点相对于地固坐标系的坐标为(x
0,y
0,z
0)，NDT坐标轴相对于低估坐标轴的x、y、z方向的旋转角度分别为α、β、γ.
则旋转矩阵为：
可得到GPS与NDT相统一的三维坐标为：
(x,y,z)＝M×(x
u,y
u,z
u)+(x
0,y
0,z
0)
4.无人机起飞方向的获取
应用激光雷达NDT算法来对无人机进行定位时需要获取无人机的表面参数，不仅需要获取无人机的初始点坐标，还需要获取无人机的飞行方向。我们可以用方向余弦和方向余弦矩阵来表达无人机的方向，计算方案如下：
已知无人机的本体坐标系为(i,j,k)，NDT建图的坐标系作为全局坐标系为(I,J,K)，则此时无人机的方向余弦矩阵(DCM)为：
为了获取无人机的方向余弦，根据GPS的米级精度，考虑让无人机起飞2m的距离后计算其飞行方向。由GPS获取到无人机的初始点(x
0,y
0,z
0)，起飞2m后到达的运动点为(x
1,y
1,z
1)，轨迹向量为(x
1-x
0,y
1-y
0,z
1-z
0)，根据上述信息可以估计出无人机的飞行方向，即方向余弦向量为:
根据NDT算法的要求，对于划分的每一个网格，计算网格内点云的概率密度函数：当网格内的点数大于5时，各点云的均值向量为：
其中x
k(k＝1、2、…)表示网格内所有的点云。
该网格内点云的协方差矩阵为:
网格内点云的概率密度函数为：
协方差矩阵的特征向量
可以表示无人机的朝向，当网格内的点云数小于5时，协方差矩阵不存在逆矩阵，其正态分布是退化的，此时用余弦向量来估计其方向，即：
因此，不论网格内点云是否稀疏，均可以应用NDT变换进行定位。
5.NDT与GPS定位基于IMU数据的决策
在t
0和t
1时刻，通过GPS得到的两时刻的优化定位坐标分别为：
位移之差向量为：
根据公式
可以求解出
由GPS在t
1时刻得到的三个方向的加速度为:
同理，由NDT在t
1时刻得到的三个方向的加速度为：
将在t
1时刻得到的GPS、NDT加速度由NDT坐标换算为无人机机体轴坐标系。得到换算后的加速度值
和
并实时获取到该时刻机载IMU关于三个方向的加速度
通过IMU实际加速度值来仲裁GPS和NDT给出的坐标是否偏离实际值，计算出GPS、NDT两组加速度关于IMU加速度的差值向量，即
和
通过计算差值向量的欧几里得范数，衡量差值的偏差程度，计算得到GPS和NDT的差值范数分别为：
将得到的GPS差值范数和NDT差值范数与阈值参数
进行比较，可以得到以下4种比较情况：
1.如果
且
则认为GPS和NDT算法均比较稳定，因为激光雷达可以达到更高的精确度，因此取激光雷达获得的坐标作为最终定位坐标，取p＝p
N＝(x
N,y
N,z
N)作为校准坐标。
2.如果
且
则认为NDT获取到的定位偏差较大，取p＝p
G＝(x
G,y
G,z
G)作为校准坐标。
3.如果
且
则认为GPS获取到的定位偏差较大，取p＝p
N＝(x
N,y
N,z
N)作为校准坐标。
4.如果
且
则认为GPS和NDT获取到定位均存在偏差，取由步骤1介绍的利用IMU和上一时刻坐标估计出的t
1时刻坐标p
I，利用NDT和IMU的加权坐标作为校准坐标，即取
作为校准坐标。其中，应满足理论NDT的精确度越高，β值越大。因此，可以将NDT的点云匹配率赋给β，且α+β＝1。
Claims (3)
- 一种基于IMU将GPS与激光雷达结合进行定位的方法，本方法利用了GPS定位和激光雷达NDT算法对无人机进行定位，改进了无人机单传感器定位的模式。其特征在于：结合IMU获取的惯性测量参数，对GPS和激光雷达的定位数据进行可靠性比较，决策出最终定位数据，步骤如下：步骤1：定位数据预判断和预处理；步骤2：结合IMU进行定位决策；步骤3：得出校准定位。
- 根据要求1中步骤1所述的对GPS和激光雷达的定位数据进行可靠性预判断，其特征在于：当IMU获取到的实时加速度大于阈值ε时，则认为无人机处于运动状态，此时若NDT算法和GPS返回的定位数据比较前一时刻未发生改变，则认为定位异常。再获取NDT算法定位时激光雷达点云匹配的迭代次数，如果已达到最大匹配次数，则认为NDT算法失配异常。预判断阶段有以下情形：当NDT算法异常而此时的GPS定位无异常时，返回GPS与IMU融合的定位数据作为最终定位；当NDT算法无异常而此时的GPS定位异常时，返回NDT定位数据作为最终定位；当NDT算法和GPS定位均出现异常时，利用IMU实时准确加速度和上一时刻的定位数据结合，估计出该时刻的数据作为最终定位数据。当NDT算法和GPS定位均未出现异常时，利用IMU实时准确加速度来决策出最终返回定位数据。
- 根据要求1步骤2所述的结合IMU进行定位决策，其特征在于：对于要求3得到的由GPS与NDT计算出的加速度，将它们分别与IMU实时加速度进行比较，计算出差值范数。将两个差值范数与给定阈值进行比较，有以下情形：当由NDT算法得到的差值范数和GPS得到的差值范数均小于给定阈值时，返回NDT定位数据作为最终定位；当由NDT算法得到的差值范数小于给定阈值而由GPS得到的差值范数大于给定阈值时，返回NDT定位数据作为最终定位；当由NDT算法得到的差值范数大于给定阈值而由GPS得到的差值范数小于给定阈值时，返回GPS定位数据作为最终定位；当由NDT算法得到的差值范数和GPS得到的差值范数均大于给定阈值时，返回NDT与IMU融合的定位数据作为最终定位。
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