CN108241365A - The method and apparatus that estimation space occupies - Google Patents
The method and apparatus that estimation space occupies Download PDFInfo
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- CN108241365A CN108241365A CN201611227286.2A CN201611227286A CN108241365A CN 108241365 A CN108241365 A CN 108241365A CN 201611227286 A CN201611227286 A CN 201611227286A CN 108241365 A CN108241365 A CN 108241365A
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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Abstract
The embodiment of the present invention provides the method and apparatus that estimation space occupies, and belongs to automatic Pilot field, this method includes：The filtering information of each point in the point cloud information of sensor detection is calculated under map coordinates system, wherein map coordinates system is fixed relative to sensing station, and attitude information is consistent in world coordinate system in map coordinates system in the point cloud information of sensor detection；The occupation probability of the space lattice is calculated according to the filtering information for each point for being located at space lattice in cloud information.The embodiment of the present invention can utilize situation about being occupied with the data under the relatively-stationary map coordinates system of sensor come estimation space, reduce the error of introducing, and then improve the accuracy of estimation, reduce estimated bias.
Description
Technical field
The present invention relates to automatic Pilot fields, and in particular, to the method and apparatus that a kind of estimation space occupies.
Background technology
In automatic Pilot, need to be detected space object using sensor, and obtain point cloud data, Ran Hougen
According to the occupancy of point cloud data estimation space.For example, when bumpy road automatic running in the wild, if GPS signal is unstable
Situation fixed, then that point cloud information estimation space can be utilized to occupy, to provide prior information for path planning and Object identifying.
At present, the estimation of volume exclusion is by the world coordinate system of the point cloud data convert to static under sensor coordinate system
Under data, according to the situation that the data under world coordinate system occupy come estimation space, it is accumulative that translation is introduced using this method
Error, attitude error and measurement error.Present inventor has found that the said program of the prior art has volume exclusion estimation
The defects of accuracy is relatively low, and deviation is excessive.
Invention content
The purpose of the embodiment of the present invention is to provide the method and apparatus that a kind of estimation space occupies, and is asked with solving above-mentioned technology
Topic solves above-mentioned technical problem at least partly.
To achieve these goals, the embodiment of the present invention provides a kind of method that estimation space occupies, and this method includes：
The filtering information of each point in the point cloud information of sensor detection is calculated under map coordinates system, wherein map coordinates system is relative to biography
Sensor position is fixed, and attitude information is consistent in world coordinate system in map coordinates system in the point cloud information of sensor detection；
The occupation probability of the space lattice is calculated according to the filtering information for each point for being located at space lattice in cloud information.
Optionally, the filtering information packet for putting each point in cloud information that sensor detection is calculated under map coordinates system
It includes：The location information of each point in point cloud information under sensor coordinate system is converted to the location information under map coordinates system,
The coordinate system that wherein described sensor coordinate system is established for foundation sensing station；For each point in cloud information, according to institute
State the positional information calculation corresponding measurement error of point and the position error a little under map coordinates system；For each in cloud information
Point calculates the filtering information of the point according to the measurement error of the point and position error.
Optionally, the filtering information according to each point for being located at space lattice in cloud information calculates the space grating
The occupation probability of lattice includes：For being located at each point of space lattice in cloud information, space grating is calculated according to the position of the point
Lattice correspond to the occupation probability of the point；Filtering information positioned at each point of the space lattice and space in point of use cloud information
Grid calculates the occupation probability of the space lattice corresponding to the occupation probability of each point.
Optionally, each point for being located at space lattice in cloud information calculates space according to the position of the point
Grid includes corresponding to the occupation probability of the point：For in cloud information be located at space lattice each point, calculate respectively the point with
The inverse of distance between space lattice center, the inverse of the distance to being calculated, which is normalized, obtains space lattice corresponding to this
The occupation probability of point.
Optionally, positioned at the filtering information and space lattice of each point of the space lattice in the point of use cloud information
Include corresponding to the occupation probability of the occupation probability calculating space lattice of each point：Using in cloud information be located at the space
The filtering information and space lattice of the point of grid are corresponding to the occupation probability of the occupation probability iteration update space lattice of the point.
According to another aspect of the present invention, the device that a kind of estimation space occupies is provided, which includes：Filtering information
Computing module, for calculating the filtering information of each point in the point cloud information of sensor detection under map coordinates system, wherein
Figure coordinate system is fixed relative to sensing station, and sensor detection point cloud information in attitude information in map coordinates system and generation
It is consistent in boundary's coordinate system；Occupation probability computing module, for the filtering according to each point for being located at space lattice in cloud information
Information calculates the occupation probability of the space lattice.
Optionally, the filtering information computing module includes：Converting unit, for the point cloud under sensor coordinate system to be believed
The location information of each point is converted to the location information under map coordinates system in breath, wherein the sensor coordinate system is according to biography
The coordinate system that sensor position is established；First computing unit, for for each point in cloud information, being sat according to the point in map
The positional information calculation corresponding measurement error of point and position error under mark system；Second computing unit, for believing for cloud
Each point in breath calculates the filtering information of the point according to the measurement error of the point and position error.
Optionally, the occupation probability computing module includes：Third computing unit, for for being located at sky in cloud information
Between grid each point, according to the position of the point calculate space lattice correspond to the point occupation probability；4th computing unit is used
Filtering information and space lattice positioned at each point of the space lattice in point of use cloud information correspond to occupying for each point
The occupation probability of space lattice described in probability calculation.
Optionally, the third computing unit is used for each point for being located at space lattice in cloud information, calculates respectively
The inverse of distance between the point and space lattice center, the inverse of the distance to being calculated, which is normalized, obtains space lattice phase
It should be in the occupation probability of the point.
Optionally, the 4th computing unit is used to believe using the filtering of point for being located at the space lattice in point cloud information
Breath and space lattice update the occupation probability of space lattice corresponding to the occupation probability iteration of the point.
Through the above technical solutions, the filtering for putting each point in cloud information of sensor detection is calculated under map coordinates system
Information, wherein map coordinates system are fixed relative to sensing station, and sensor detection point cloud information in attitude information on ground
Figure coordinate system is consistent in world coordinate system；It is calculated according to the filtering information for each point for being located at space lattice in cloud information empty
Between grid occupation probability；It can so utilize and be accounted for the data under the relatively-stationary map coordinates system of sensor come estimation space
According to situation, reduce the error of introducing, and then improve the accuracy of estimation, reduce estimated bias.
The other feature and advantage of the embodiment of the present invention will be described in detail in subsequent specific embodiment part.
Description of the drawings
Attached drawing is that the embodiment of the present invention is further understood for providing, and a part for constitution instruction, under
The specific embodiment in face is used to explain the embodiment of the present invention, but do not form the limitation to the embodiment of the present invention together.Attached
In figure：
Fig. 1 is the method flow diagram that estimation space according to embodiments of the present invention occupies；
Fig. 2 is the signal of scene that sports type robot system according to embodiments of the present invention is advanced in the environment that jolts
Figure；
Fig. 3 is the flow chart of the process of calculating filtering information according to embodiments of the present invention；
Fig. 4 is the stream of the process according to embodiments of the present invention that space lattice occupation probability is calculated according to the filtering information of point
Cheng Tu；
Fig. 5 is the method flow diagram according to embodiments of the present invention that estimation space occupies under scene as shown in Figure 2；
Fig. 6 is the structure chart for the device that estimation space according to embodiments of the present invention occupies；
Fig. 7 is the structure chart for the device that estimation space according to embodiments of the present invention occupies；And
Fig. 8 is the structure chart for the device that estimation space according to embodiments of the present invention occupies.
Specific embodiment
The specific embodiment of the embodiment of the present invention is described in detail below in conjunction with attached drawing.It should be understood that this
Locate described specific embodiment and be merely to illustrate and explain the present invention embodiment, be not intended to restrict the invention embodiment.
Embodiment one
Fig. 1 is the method flow diagram that estimation space according to embodiments of the present invention occupies, and this method can be used for driving automatically
It sails in system, such as the automated driving system of robot, vehicle, as shown in Figure 1, this method may include following steps.
In step s 110, the filtering letter of each point in the point cloud information of sensor detection is calculated under map coordinates system
Breath.
Wherein, map coordinates system is fixed relative to sensing station, and the attitude information of the point cloud information of sensor detection
It is consistent in world coordinate system in map coordinates system.
For example, in environment as shown in Figure 2, S point representative sensors, sensor coordinate system is static using S points as origin
World coordinate system is using I points as origin, rISVector for I points to S points.M points are fixed with respect to S points, and map coordinates system is using M points as original
Point, and it is consistent in world coordinate system in map coordinates system to put the attitude information in cloud information, i.e. roll (roll), pitch
(pitching) is consistent in world coordinate system in map coordinates system with the value of yaw (rotation).
The point cloud information of normal conditions lower sensor detection is the data information under sensor coordinate system, in the present invention will
Point cloud information under sensor coordinate system is converted to the data information under map coordinates system, then according under the map coordinates system
Data information obtains the filtering information of each point in cloud information.
In the step s 120, space lattice is calculated according to the filtering information for each point for being located at space lattice in cloud information
Occupation probability.
For example, dividing space into the cube of pre-set dimension, which is space lattice, for each space grating
Lattice calculate the occupation probability of space lattice according to the filtering information for each point for being located at space lattice in cloud information, thus just
Obtain the occupancy in space.
By the above embodiment, it can utilize and estimate sky with the data under the relatively-stationary map coordinates system of sensor
Between occupy, and only introduce attitude error and measurement error, reduce the margin of error of introducing, and then improve the accurate of estimation
Property, reduce estimated bias.
Embodiment two
Fig. 3 is the flow chart of the process of calculating filtering information according to embodiments of the present invention, as shown in figure 3, described on ground
The filtering information of each point in the point cloud information of sensor detection is calculated under figure coordinate system may include following steps.
In step s 302, the location information of each point in the point cloud information under sensor coordinate system is converted to map to sit
Location information under mark system.
Wherein, the coordinate system that sensor coordinate system is established for foundation sensing station.
For example, in environment as shown in Figure 2, location informations of the point cloud information midpoint P under map coordinates system is such as
Shown in formula 1.
Pm=mrMP=mrSP-mrSM=Cms (q | t) × srSP-mrSMFormula 1
Wherein, mrMPFor the position of the P points under map coordinates system, mrSPFor the S- under map coordinates system>P (S points to P points)
Vector information, mrSMFor the S- under map coordinates system>The vector information of M (S points to M points)；Cms is opposite for sensor coordinate system
In the transitional information of map coordinates system, q is to correspond to the quaternary number that the coordinate of t moment is converted, srSPFor S- under sensor coordinate system>P
The vector information of (S points to P points).
In step s 304, for each point in cloud information, according to positional information calculation point of the point under map coordinates system
Corresponding measurement error and position error.
For example, since the origin of the origin of map coordinates system and sensor coordinate system is relatively fixed, in formula 1
mrSMFor constant, so control information comes from srSPAnd q, correspond respectively to measurement error and attitude error.As shown in formula 2,
To PmSeek local derviation.
Ds=dPm/d(srSP)=Cms (q | t)；Dq=dPm/ (dq)=Cms × (srSPX) formula 2
Wherein Ds is the local derviation to metrical information, such as corresponds to the local derviation of laser measurement information, represents measurement error；Dq is
To the partial derivative of quaternary number, attitude error, sr are representedSPX is srSPMatrix tiltedly poised for battle.
In step S306, for each point in cloud information, which is calculated according to the measurement error of point and position error
Filtering information.
For example, 3 the filtering information put is calculated as follows.
E=Ds × Es × (Ds)T+Dq×Eq×(Dq)TFormula 3
Wherein, E is filtering information a little, and Es is the covariance matrix of the estimation measurement error of laser sensor, and matrix is joined
Number is related to sensor model, and Eq is the covariance matrix of the estimation measurement error of inertial navigation sensors.(Ds)TRepresent Ds's
Transposition, (Dq)TRepresent the transposition of Dq.The formula 3 is directed to the example using laser sensor and usual navigation sensor, in difference
It can think that suitable any mode obtains a filtering information at cloud information midpoint in scene using those skilled in the art.
The filtering information of each point in cloud information can be obtained by above-described embodiment, due to the use of data under map coordinates system
The filtering information of point is calculated, the complexity of calculating is reduced, improves computational efficiency.
Embodiment three
Fig. 4 is the stream of the process according to embodiments of the present invention that space lattice occupation probability is calculated according to the filtering information of point
Cheng Tu, as shown in figure 4, the filtering information according to each point for being located at space lattice in cloud information calculates space lattice
Occupation probability may include following steps.
In step S402, for being located at each point of space lattice in cloud information, space grating is calculated according to the position of point
Lattice correspond to the occupation probability of the point.
Further, each point for being located at space lattice in cloud information calculates empty according to the position of the point
Between grid may include corresponding to the occupation probability of the point：The point is calculated respectively for each point for being located at space lattice in cloud information
The inverse of distance between space lattice center；The inverse of distance to being calculated is normalized acquisition space lattice and corresponds to
The occupation probability of the point.
For example, for the point positioned at space lattice in cloud information, the location information of the point is obtained from cloud information,
Using the distance d between the midpoint of the positional information calculation point and space lattice, the 1/d reciprocal of d is taken, then using normalization letter
1/d is normalized to the numerical value between 0~1 by number.Mode used in normalization can be that those skilled in the art think suitable any
Mode.
In step s 404, the filtering information of each point of space lattice and space lattice phase are located in point of use cloud information
The occupation probability of space lattice should be calculated in the occupation probability of each point.
Further, the filtering information of each point of space lattice and space lattice phase are located in the point of use cloud information
The occupation probability of space lattice should be calculated in the occupation probability of each point may include：Utilize the point for being located at space lattice in cloud information
Filtering information and space lattice corresponding to the point occupation probability iteration update space lattice occupation probability.
For example, when initial, the filtering information and space grating for being located at a point in space lattice in cloud information are taken
Lattice are stored for the occupation probability of the point respectively as the initial covariance information and occupation probability of space lattice.Then,
The filtering information for being located at another point in space lattice in cloud information and space lattice is taken to be updated for the occupation probability of the point
The covariance information and occupation probability of the space lattice of storage, the point being so located in point of use cloud information one by one in space lattice
Filtering information and space lattice are directed to the occupation probability of the point to the occupation probability of space lattice of storage and covariance information progress
Iteration updates, and is all used as stopping until being located at the point in space lattice in cloud information.For example, as follows 4 and formula 5
The occupation probability and covariance information of the space lattice of storage are updated, finally estimate space lattice occupying in practice
Probability.
P+=((E) × (p)+(E-) × (p-))/((E-)+E) formula 4
E+=(E-) × (E)/((E-) × (E)) formula 5
Wherein (p-, E-) represents the occupation probability and covariance information of currently stored space lattice, (p, E) representation space grid
Lattice correspond to the point occupation probability at cloud information midpoint of extraction and the filtering information of the point, (p+, E+) represent updated space
The occupation probability and covariance information of grid.
Above-mentioned update mode is not limited to mode shown in formula 4 and formula 5, and usable those skilled in the art think suitable
Any mode be updated.
It can be counted using the above embodiment positioned at the relevant information of multiple points of space lattice in point of use cloud information
The occupation probability of space lattice is calculated, improves the accuracy of occupation probability.
Example IV
Fig. 5 is the method flow diagram according to embodiments of the present invention that estimation space occupies under scene as shown in Figure 2,
In the present invention will be described for the space hold information of estimation is provided for kinematic robot.As shown in figure 5, this method can
Include the following steps.In step S502, the location information of each point in the point cloud information under sensor coordinate system is converted to
Location information under map coordinates system.Map coordinates system with the relatively-stationary M points in S points position at wherein S points, as origin, to sense
Attitude information in the point cloud information of device detection is consistent in world coordinate system in map coordinates system.It for example, can be by public affairs
Mode shown in formula 1 is converted.In step S504, for each point in cloud information, according to position of the point under map coordinates system
Confidence breath calculates the corresponding measurement error of point and position error.For example, it is calculated in a manner that formula 2 seeks local derviation in cloud information
The corresponding measurement error of each point and position error.In step S506, for each point in cloud information, according to the measurement error of point
The filtering information of the point is calculated with position error.For example, the mode as shown in formula 3 calculates a filtering information at cloud information midpoint.
In step S508, for being located at each point of space lattice in cloud information, calculate respectively between the point and space lattice center
The inverse of distance, the inverse of the distance to being calculated, which is normalized, obtains the occupation probability that space lattice corresponds to the point.
In step S510, the filtering information for being located at a point in space lattice in cloud information and space lattice accounting for for the point are taken
It is stored according to initial covariance information and occupation probability of the probability respectively as space lattice.In step S512, carry one by one
Take the point in cloud information in space lattice filtering information and space lattice for the point occupation probability come iteration more
The covariance information and occupation probability of the space lattice newly stored are all used until being located at the point in space lattice in cloud information
Until.For example, the occupation probability and covariance information of the space lattice of storage are updated in the way of formula 4 and formula 5.Such as
This, Pass through above-mentioned technical proposal obtains the occupation probability of each space lattice, and then estimates the occupancy in space.
Technical solution is intended to illustrate technical solution in invention in the present embodiment, is not used in the protection model of the limitation present invention
It encloses.
Fig. 6 is the structure chart for the device that estimation space according to embodiments of the present invention occupies, which can be used for automatically
In control loop, such as the automated driving system of robot, vehicle, as shown in fig. 6, the device may include following module.
Filtering information computing module 610, it is each in the point cloud information of sensor detection for being calculated under map coordinates system
The filtering information of point；Wherein map coordinates system is fixed relative to sensing station, and posture in the point cloud information of sensor detection
Information is consistent in world coordinate system in map coordinates system；
Occupation probability computing module 620, for the filtering information according to each point for being located at space lattice in cloud information
Calculate the occupation probability of space lattice.
By the above embodiment, it can utilize and estimate sky with the data under the relatively-stationary map coordinates system of sensor
Between occupy, and only introduce attitude error and measurement error, reduce the margin of error of introducing, and then improve the accurate of estimation
Property, reduce estimated bias.
As shown in fig. 7, in an optional embodiment, filtering information computing module 610 may include such as lower unit.
Converting unit 702, for being converted to ground by the location information of each point in the point cloud information under sensor coordinate system
Location information under figure coordinate system, wherein the coordinate system that the sensor coordinate system is established for foundation sensing station；
First computing unit 704, for for each point in cloud information, according to position of the point under map coordinates system
Information calculates the corresponding measurement error of point and position error；
Second computing unit 706, for for each point in cloud information, according to the measurement error of the point and position error meter
Calculate the filtering information of the point.
The filtering information of each point in cloud information can be obtained by above-described embodiment, due to the use of data under map coordinates system
The filtering information of point is calculated, the complexity of calculating is reduced, improves computational efficiency.
As shown in figure 8, in an optional embodiment, occupation probability computing module 620 may include such as lower unit.
Third computing unit 802 for each point for being located at space lattice in cloud information, is counted according to the position of the point
Calculate the occupation probability that space lattice corresponds to the point.
Further, third computing unit 802 is used for each point for being located at space lattice in cloud information, calculates respectively
The inverse of distance between the point and space lattice center, the inverse of the distance to being calculated, which is normalized, obtains space lattice phase
It should be in the occupation probability of the point.
4th computing unit 804, for being located at the filtering information and sky of each point of space lattice in point of use cloud information
Between grid corresponding to each point occupation probability calculate space lattice occupation probability.
Further, the 4th computing unit 804 is used for the filtering information using the point for being located at space lattice in point cloud information
With space lattice corresponding to the occupation probability of the occupation probability iteration update space lattice of the point.
It can be counted using the above embodiment positioned at the relevant information of multiple points of space lattice in point of use cloud information
The occupation probability of space lattice is calculated, improves the accuracy of occupation probability.
Above device is corresponding with preceding method, and specific embodiment can be found in preceding method and be described in detail, herein not
It repeats again.
The optional embodiment of example of the present invention, still, the embodiment of the present invention and unlimited are described in detail above in association with attached drawing
Detail in the above embodiment, can be to the embodiment of the present invention in the range of the technology design of the embodiment of the present invention
Technical solution carry out a variety of simple variants, these simple variants belong to the protection domain of the embodiment of the present invention.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case of shield, it can be combined by any suitable means.In order to avoid unnecessary repetition, the embodiment of the present invention pair
Various combinations of possible ways no longer separately illustrate.
It will be appreciated by those skilled in the art that all or part of the steps of the method in the foregoing embodiments are can to pass through
Program is completed to instruct relevant hardware, which is stored in a storage medium, is used including some instructions so that one
A (can be microcontroller, chip etc.) or processor (processor) perform the whole of each embodiment the method for the application
Or part steps.And aforementioned storage medium includes：USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can store journey
The medium of sequence code.
In addition, arbitrary combination can also be carried out between a variety of different embodiments of the embodiment of the present invention, as long as it is not
The thought of the embodiment of the present invention is violated, should equally be considered as disclosure of that of the embodiment of the present invention.
Claims (10)
1. a kind of method that estimation space occupies, which is characterized in that this method includes：
The filtering information of each point in the point cloud information of sensor detection, wherein map coordinates system phase are calculated under map coordinates system
Sensing station is fixed, and sensor detection point cloud information in attitude information in map coordinates system and world coordinate system
Unanimously；
The occupation probability of the space lattice is calculated according to the filtering information for each point for being located at space lattice in cloud information.
2. the according to the method described in claim 1, it is characterized in that, point that sensor detection is calculated under map coordinates system
The filtering information of each point includes in cloud information：
The location information of each point in point cloud information under sensor coordinate system is converted to the location information under map coordinates system,
The coordinate system that wherein described sensor coordinate system is established for foundation sensing station；
For each point in cloud information, according to positional information calculation of the point under map coordinates system, the point measures mistake accordingly
Difference and position error；
For each point in cloud information, the filtering information of the point is calculated according to the measurement error of the point and position error.
3. according to the method described in claim 1, it is characterized in that, it is described according in cloud information be located at space lattice it is each
The occupation probability that the filtering information of point calculates the space lattice includes：
For being located at each point of space lattice in cloud information, space lattice is calculated corresponding to the point according to the position of the point
Occupation probability；
Filtering information and space lattice in point of use cloud information positioned at each point of the space lattice correspond to accounting for for each point
According to the occupation probability of space lattice described in probability calculation.
It is 4. according to the method described in claim 3, it is characterized in that, described for being located at each of space lattice in cloud information
Point calculates space lattice according to the position of the point and includes corresponding to the occupation probability of the point：
For being located at each point of space lattice in cloud information, falling for the distance between the point and space lattice center is calculated respectively
Number, the inverse of the distance to being calculated, which is normalized, obtains the occupation probability that space lattice corresponds to the point.
5. according to the method described in claim 3, it is characterized in that, positioned at the space lattice in the point of use cloud information
The occupation probability that the filtering information and space lattice of each point calculate the space lattice corresponding to the occupation probability of each point includes：
It is general corresponding to occupying for the point using the filtering information and space lattice for the point for being located at the space lattice in cloud information
Rate iteration updates the occupation probability of space lattice.
6. the device that a kind of estimation space occupies, which is characterized in that the device includes：
Filtering information computing module, for calculating the filtering of each point in the point cloud information of sensor detection under map coordinates system
Information, wherein map coordinates system are fixed relative to sensing station, and sensor detection point cloud information in attitude information on ground
Figure coordinate system is consistent in world coordinate system；
Occupation probability computing module, described in being calculated according to the filtering information for each point for being located at space lattice in cloud information
The occupation probability of space lattice.
7. device according to claim 6, which is characterized in that the filtering information computing module includes：
Converting unit, for the location information of each point in the point cloud information under sensor coordinate system to be converted to map coordinates system
Under location information, wherein the sensor coordinate system is the coordinate system established according to sensing station；
First computing unit, for for each point in cloud information, according to location information meter of the point under map coordinates system
Calculate the corresponding measurement error of point and position error；
Second computing unit, for for each point in cloud information, being calculated according to the measurement error of the point and position error should
The filtering information of point.
8. device according to claim 6, which is characterized in that the occupation probability computing module includes：
Third computing unit for each point for being located at space lattice in cloud information, calculates empty according to the position of the point
Between grid correspond to the point occupation probability；
4th computing unit, for being located at the filtering information and space grating of each point of the space lattice in point of use cloud information
Lattice calculate the occupation probability of the space lattice corresponding to the occupation probability of each point.
9. device according to claim 8, which is characterized in that the third computing unit is used for for position in cloud information
In each point of space lattice, the inverse of the distance between the point and space lattice center is calculated respectively, to falling for the distance that is calculated
Number, which is normalized, obtains the occupation probability that space lattice corresponds to the point.
10. device according to claim 8, which is characterized in that the 4th computing unit is used for using in point cloud information
Filtering information and space lattice positioned at the point of the space lattice update space lattice corresponding to the occupation probability iteration of the point
Occupation probability.
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| CN108240807A (en) * | 2016-12-27 | 2018-07-03 | 乐视汽车（北京）有限公司 | The method that estimation space occupies |
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