CN105509748B - The air navigation aid and device of robot - Google Patents
The air navigation aid and device of robot Download PDFInfo
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- CN105509748B CN105509748B CN201511016707.2A CN201511016707A CN105509748B CN 105509748 B CN105509748 B CN 105509748B CN 201511016707 A CN201511016707 A CN 201511016707A CN 105509748 B CN105509748 B CN 105509748B
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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
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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Abstract
The present invention is suitable for robotic technology field, provides the air navigation aid and device of robot, comprising: by point cloud data collection PkKD tree adaptation is inputted with the point cloud data collection X of the collected previous frame of body-sensing sensor, is found in X from PkNearest corresponding data point generates point to set Yk=C (Pk, X), wherein the k is the number of iterations, initializes k=0, P0For the point cloud data collection of the collected present frame of body-sensing sensor；By the point cloud data collection PkIt is registrated with the point cloud data collection X；Before not up to preset termination condition, k=k+1 is enabled, it is described by point cloud data collection P to return to executionkWith the operation of the point cloud data collection X input KD tree adaptation of the collected previous frame of body-sensing sensor；If having reached the preset termination condition, according to current point cloud data collection PkCorrect the amount of state variation of the robot.The embodiment of the present invention greatly reduces the manufacturing cost of robot.
Description
Technical field
The invention belongs to robotic technology field more particularly to the air navigation aids and device of robot.
Background technique
From the sixties in last century movable machine people Stanford University occur since, with science and technology hair
Exhibition, the application field of movable machine people, which also plays, to be come more extensive, extends to family, service, amusement, military affairs etc. no from industry
Same field.The operation of movable machine people is to need robot to understand the map of its local environment based on navigating
And itself position is positioned, the robot of traditional indoor movable generallys use laser equipment navigation, although laser equipment
Navigation accuracy is high, but its price up to ten thousand brings the excessively high manufacturing cost of mobile robot easily.
Summary of the invention
In view of this, the embodiment of the invention provides the air navigation aid of robot and device, to solve existing robot
Airmanship will lead to the excessively high problem of robot building cost.
In a first aspect, provide a kind of air navigation aid of robot, built-in body-sensing sensor, described in the robot
Method includes:
By point cloud data collection PkIt is matched with the point cloud data collection X of the collected previous frame of body-sensing sensor input KD tree
Device is found in X from PkNearest corresponding data point generates point to set Yk=C (Pk, X), wherein the k is the number of iterations,
Initialize k=0, P0For the point cloud data collection of the collected present frame of body-sensing sensor；
By the point cloud data collection PkIt is registrated with the point cloud data collection X；
Before not up to preset termination condition, k=k+1 is enabled, it is described by point cloud data collection P to return to executionkWith it is described
The operation of the point cloud data collection X input KD tree adaptation of the collected previous frame of body-sensing sensor；
If having reached the preset termination condition, according to current point cloud data collection PkCorrect the state of the robot
Variable quantity.
Second aspect, provides a kind of navigation device of robot, and built-in body-sensing sensor, described in the robot
Device includes:
Input unit is used for point cloud data collection PkWith the point cloud data collection of the collected previous frame of body-sensing sensor
X inputs KD tree adaptation, finds in X from PkNearest corresponding data point generates point to set Yk=C (Pk, X), wherein institute
Stating k is the number of iterations, initializes k=0, P0For the point cloud data collection of the collected present frame of body-sensing sensor；
Registration unit is used for the point cloud data collection PkIt is registrated with the point cloud data collection X；
First return unit returns for before not up to preset termination condition, enabling k=k+1 and executes the input
The operation of unit；
First correcting unit, if for having reached the preset termination condition, according to current point cloud data collection PkIt rectifys
The amount of state variation of the just described robot.
In embodiments of the present invention, laser equipment is substituted using body-sensing sensor, during realizing robot navigation
Pose correction, greatly reduces the manufacturing cost of robot.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the structural block diagram of robot hardware's system provided in an embodiment of the present invention；
Fig. 2 is the structural block diagram of robot software's system provided in an embodiment of the present invention；
Fig. 3 is the implementation flow chart of the air navigation aid of robot provided in an embodiment of the present invention；
Fig. 4 is the processing module schematic diagram of the air navigation aid of robot provided in an embodiment of the present invention；
Fig. 5 be another embodiment of the present invention provides robot air navigation aid implementation flow chart；
Fig. 6 is the point set alignment schematic diagram of the air navigation aid of robot provided in an embodiment of the present invention；
Fig. 7 is the structural block diagram of the navigation device of robot provided in an embodiment of the present invention.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details understands the embodiment of the present invention to cut thoroughly.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
The structural block diagram that Fig. 1 shows robot hardware's system provided in an embodiment of the present invention is only shown for ease of description
Part related to the present embodiment is gone out.
As shown in Figure 1, the hardware system of robot is mainly made of following components:
1, industrial control computer: being equipped with operating system thereon, for being handled data and being stored, and is hardware
Other modules in system provide service；
2, body-sensing sensor: color and depth information for collecting robot people's local environment；
3, motion sensor: for obtaining the sensors such as the motion information of robot, including code-disc, gyroscope；
4, drive control unit: by the way that driving signal is inputted bottom controller, to drive robot ambulation.
5, other modules: the communication interface including display module, between communication module and each module.
Fig. 2 shows the structural block diagrams of robot software's system provided in an embodiment of the present invention only to show for ease of description
Part related to the present embodiment is gone out.
As shown in Fig. 2, the software systems of robot are mainly made of following components from the bottom to top:
1, operating system: it is mounted on industrial control computer；
2, robotically-driven program；
3, robot operating system (ROS)；
4, navigation feature packet: it is mounted among robot operating system.
In embodiments of the present invention, using industrial control computer as main calculation processing unit, body-sensing sensor, code
The data of acquisition are sent industrial control computer by disk, by calculating the positioning for constructing map and realizing mobile robot.?
During navigation, mobile robot controls robotically-driven walking by the embedded system of bottom.
Software and hardware structure based on Fig. 1 and robot shown in Fig. 2, next to robot provided in an embodiment of the present invention
Air navigation aid be illustrated:
Fig. 3 shows the implementation process of the air navigation aid of robot provided in an embodiment of the present invention, and details are as follows:
In S301, by point cloud data collection PkIt is defeated with the point cloud data collection X of the collected previous frame of body-sensing sensor
Enter KD (K-dimensional, K dimension) tree adaptation, finds in X from PkNearest corresponding data point generates point to set Yk=
C(Pk, X), wherein the k is the number of iterations, initializes k=0, P0For the point cloud of the collected present frame of body-sensing sensor
Data set.
The rate of body-sensing sensor acquisition image is 30 frames/second constantly body-sensing to be sensed by iterative closest point approach
The point cloud data of the collected present frame of device is matched with the point cloud data of previous frame, to realize further pose correction.Such as Fig. 4
Shown, data point filter exports another point cloud data using point cloud data as input after treatment, and processing mode includes
Increase descriptor, number of data points etc. is reduced by sampling, multiple data point filters can also be used simultaneously, user can be on-demand
Selection.
Further, after S301, before S302, the method also includes:
By point described in outer layer filter detection to set Yk, the point is removed to set YkIn be unsatisfactory for preset rules
Point pair.
For example, the two can be removed if being more than by judging whether the distance between two points are more than some threshold value
Point.
In S302, by the point cloud data collection PkIt is registrated with the point cloud data collection X.
It specifically, can calculating matrix Q (∑ firstpy) feature vector qR=[q0 q1 q2 q3], whereinThe ∑pyIt is point set PkWith
YkThe mutual variance matrix of association, I3It is 3 rank unit matrixs, Δ=[A23 A31 A12]T,
Secondly, according to described eigenvector qRCalculate spin matrix R and translation vector qT, obtain registration vector q=[qR|
qT]T, to realize the point cloud data collection PkIt is registrated with the point cloud data collection X.Wherein:qT=μy-R
(qR)μp, the μyAnd μpIt is point set Y respectivelykAnd PkMass center.
In S303, before not up to preset termination condition, k=k+1 is enabled, it is described by point cloud data collection to return to execution
PkWith the operation of the point cloud data collection X input KD tree adaptation of the collected previous frame of body-sensing sensor.
In S304, if having reached the preset termination condition, according to current point cloud data collection PkCorrect the machine
The amount of state variation of device people.
In embodiments of the present invention, the preset termination condition includes:
The value of the k has been more than default the number of iterations；Alternatively,
The point cloud data collection PkError to the point cloud data collection X is less than preset error value.
Further, while movement, motion sensor can obtain shape of the robot within the unit time for robot
State variable quantity.Typically, it is influenced, is moved by factors such as sliding, offsets between the wheel of robot and smooth earth
The confidence level of amount of state variation acquired in sensor is not high, therefore, in embodiments of the present invention, using method shown in Fig. 5 come
Increase the confidence level of amount of state variation acquired in motion sensor:
In S501, the correction parameter of robot motion's sensor is obtained, the correction parameter includes linear correction parameter
With rotational correction parameter.
For example, the correction program carried using the gyroscope of robot built-in, after repeatedly being verified, being verified, is determined
The linear correction parameter and rotational correction parameter of gyroscope.
In S502, it is possible in the secondary motion process to calculate robot for the state moved every time according to robot
Error increment direction and numerical value, and the amount of state variation obtained with the motion sensor merges, operation obtains modified state
Variable quantity.
In S503, the correction parameter is merged with the modified amount of state variation, estimates the shape for obtaining robot
State variable quantity.
The amount of state variation finally got is the higher value of confidence level.
Further, it is assumed that robot is in initial pose PrefIt has been single pass Sref, later by primary small fortune
It is dynamic to reach new pose Pnew, and it has been single pass S again on the posenew, in general, in above process, PrefAnd PnewIt can
To be obtained from motion sensor, however, in order to further increase PrefAnd PnewAccuracy, can be by by twice sweep
SrefAnd SnewIn point alignment, obtain PrefAnd PnewBetween more accurate relationship, the state obtained with correction motion sensor
Variable quantity, as follows:
Step 1: initialization preset threshold e and initiation parameter l=0, dl=d0=0.
Illustratively, preset threshold e can be set to 0.0001.
Step 2: for the new pose S of the robotnewOn each of point Pn, in the robot initial pose SrefOn
Find the point P for being less than the preset threshold apart from the nearest and described distance therewithr, composition point is to set
Step 3: calculating the point to the spin matrix R of setwWith translation matrix T, and calculate
Step 4: calculatingWherein, the num is the point to collection
It closesIn pairing quantity.
Step 5: if | dl-dl+1| < e then exports the RwWith the T, and according to the RwThe machine is corrected with the T
The amount of state variation of people.
Step 6: if | dl-dl+1| >=e, enables k=l+1, returns to step 2.
By algorithm above, the variation square between two neighboring amount of state variation can be obtained according to the scanning of adjacent two frame
Battle array, to obtain the amount of state variation of the robot of correction.As shown in fig. 6, with SnewOn each point, in SrefIt is upper to find phase therewith
Corresponding nearest point, if the distance between they are less than the threshold value of setting, being considered as them is match point, calculates match later
To the spin matrix R between pointwWith translation matrix T, iterative calculation makes capable of being preferably aligned for these match points, has reduced
The distance between they function.
In embodiments of the present invention, laser equipment is substituted using body-sensing sensor, during realizing robot navigation
Pose correction, greatly reduces the manufacturing cost of robot, meanwhile, the correction strategy of motion sensor measured value and a variety of matchings
The convergence strategy of algorithm also contributes to drawing out environmental map more accurately, and determines the state of robot.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Corresponding to the air navigation aid of robot described in foregoing embodiments, Fig. 7 shows machine provided in an embodiment of the present invention
The structural block diagram of the navigation device of device people.For ease of description, only the parts related to this embodiment are shown.
Referring to Fig. 7, which includes:
Input unit 71, by point cloud data collection PkWith the point cloud data collection X of the collected previous frame of body-sensing sensor
KD tree adaptation is inputted, is found in X from PkNearest corresponding data point generates point to set Yk=C (Pk, X), wherein it is described
K is the number of iterations, initializes k=0, P0For the point cloud data collection of the collected present frame of body-sensing sensor；
Registration unit 72, by the point cloud data collection PkIt is registrated with the point cloud data collection X；
First return unit 73 enables k=k+1 before not up to preset termination condition, returns and executes the input list
The operation of member；
First correcting unit 74, if having reached the preset termination condition, according to current point cloud data collection PkCorrection
The amount of state variation of the robot.
Optionally, described device further include:
Acquiring unit, obtains the correction parameter of the motion sensor of the robot, and the correction parameter includes linear rectifys
Positive parameter and rotational correction parameter；
First computing unit calculates the robot in the secondary movement according to the state that the robot moves every time
Possible error increment direction and numerical value in the process, and the amount of state variation obtained with the motion sensor merges, operation obtains
To modified amount of state variation；
Unit is estimated, the correction parameter is merged with the modified amount of state variation, estimates to obtain the robot
Amount of state variation.
Optionally, described device further include:
Initialization unit initializes preset threshold e and initiation parameter l=0, dl=d0=0；
Unit is found, for the new pose S of the robotnewOn each of point Pn, in the robot initial pose
SrefUpper searching is less than the point P of the preset threshold apart from the nearest and described distance therewithr, composition point is to set
Second computing unit calculates the point to the spin matrix R of setwWith translation matrix T, and calculate
Third computing unit calculatesWherein, the num is described
Point is to setIn pairing quantity；
Output unit, if | dl-dl+1| < e then exports the RwWith the T, and according to the RwWith the T correction described in
The amount of state variation of robot；
Second return unit, if | dl-dl+1| >=e enables l=l+1, returns and executes the operation for finding unit.
Optionally, the preset termination condition includes:
The value of the k has been more than default the number of iterations；Alternatively,
The point cloud data collection PkError to the point cloud data collection X is less than preset error value.
Optionally, described device further include:
Removal unit detects the point to set Yk, the point is removed to set YkIn be unsatisfactory for the points pair of preset rules.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device and method can pass through others
Mode is realized.For example, system embodiment described above is only schematical, for example, the division of the module or unit,
Only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units or components can be with
In conjunction with or be desirably integrated into another system, or some features can be ignored or not executed.Another point, it is shown or discussed
Mutual coupling or direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING of device or unit or
Communication connection can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, the technical solution of the embodiment of the present invention
Substantially all or part of the part that contributes to existing technology or the technical solution can be with software product in other words
Form embody, which is stored in a storage medium, including some instructions use so that one
Computer equipment (can be personal computer, server or the network equipment etc.) or processor (processor) execute this hair
The all or part of the steps of bright each embodiment the method for embodiment.And storage medium above-mentioned include: USB flash disk, mobile hard disk,
Read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic
The various media that can store program code such as dish or CD.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and model of each embodiment technical solution of the embodiment of the present invention that it does not separate the essence of the corresponding technical solution
It encloses.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (8)
1. a kind of air navigation aid of robot, which is characterized in that built-in body-sensing sensor, the method packet in the robot
It includes:
By point cloud data collection PkKD tree adaptation is inputted with the point cloud data collection X of the collected previous frame of body-sensing sensor,
It finds in X from PkNearest corresponding data point generates point to set Yk=C (Pk, X), wherein the k is the number of iterations, initially
Change k=0, P0For the point cloud data collection of the collected present frame of body-sensing sensor；
By the point cloud data collection PkIt is registrated with the point cloud data collection X；
Before not up to preset termination condition, k=k+1 is enabled, it is described by point cloud data collection P to return to executionkIt is passed with the body-sensing
The operation of the point cloud data collection X input KD tree adaptation of the collected previous frame of sensor；
If having reached the preset termination condition, according to current point cloud data collection PkCorrect the state change of the robot
Amount；
Initialize preset threshold e and initiation parameter l=0, dl=d0=0；
For the new pose S of the robotnewOn each of point Pn, in the robot initial pose SrefIt is upper searching therewith away from
It is less than the point P of the preset threshold with a distance from nearest and describedr, composition point is to set
The point is calculated to setSpin matrix RwWith translation matrix T, and calculate
It calculatesWherein, the num is the point to setIn
Match quantity；It is describedIndicate obtained point cloud data collection after the l+1 times iterationIn i-th point,It indicates
Point cloud data collectionIn i-th point；
If | dl-dl+1| < e then exports the RwWith the T, and according to the RwThe state of the robot is corrected with the T
Variable quantity；
If | dl-dl+1| >=e enables l=l+1, returns and executes the pose S new for the robotnewOn each of point Pn,
In the robot initial pose SrefUpper searching is less than the point P of the preset threshold apart from the nearest and described distance therewithr, group
At point to setOperation.
2. the method as described in claim 1, which is characterized in that described by point cloud data collection PkIt is adopted with the body-sensing sensor
Before the point cloud data collection X input KD tree adaptation of the previous frame collected, the method also includes:
The correction parameter of the motion sensor of the robot is obtained, the correction parameter includes that linear correction parameter and rotation are rectified
Positive parameter；
According to the state that the robot moves every time, calculates the robot possible error in the secondary motion process and increase
Direction and numerical value are measured, and the amount of state variation obtained with the motion sensor merges, operation obtains modified amount of state variation；
The correction parameter is merged with the modified amount of state variation, estimates to obtain the amount of state variation of the robot.
3. the method as described in claim 1, which is characterized in that the preset termination condition includes:
The value of the k has been more than default the number of iterations；Alternatively,
The point cloud data collection PkError to the point cloud data collection X is less than preset error value.
4. the method as described in claim 1, which is characterized in that described by point cloud data collection PkIt is adopted with the body-sensing sensor
The point cloud data collection X of the previous frame collected inputs KD tree adaptation, finds in X from PkNearest corresponding data point generates point
To set Yk=C (Pk, X) after, it is described by the point cloud data collection PkIt is described before being registrated with the point cloud data collection X
Method further include:
The point is detected to set Yk, the point is removed to set YkIn be unsatisfactory for the points pair of preset rules.
5. a kind of navigation device of robot, which is characterized in that built-in body-sensing sensor, described device packet in the robot
It includes:
Input unit is used for point cloud data collection PkIt is inputted with the point cloud data collection X of the collected previous frame of body-sensing sensor
KD tree adaptation, finds in X from PkNearest corresponding data point generates point to set Yk=C (Pk, X), wherein the k is
The number of iterations initializes k=0, P0For the point cloud data collection of the collected present frame of body-sensing sensor；
Registration unit is used for the point cloud data collection PkIt is registrated with the point cloud data collection X；
First return unit returns for before not up to preset termination condition, enabling k=k+1 and executes the input unit
Operation；
First correcting unit, if for having reached the preset termination condition, according to current point cloud data collection PkDescribed in correction
The amount of state variation of robot；
Initialization unit, for initializing preset threshold e and initiation parameter l=0, dl=d0=0；
Unit is found, for the pose S new for the robotnewOn each of point Pn, in the robot initial pose Sref
Upper searching is less than the point P of the preset threshold apart from the nearest and described distance therewithr, composition point is to set
Second computing unit, for calculating the point to setSpin matrix RwWith translation matrix T, and calculateI indicates at i-th point, and l is k,
Third computing unit, for calculatingWherein, the num is the point
To setIn pairing quantity；It is describedIndicate obtained point cloud data collection after the l+1 times iterationIn
I-th point,Indicate point cloud data collectionIn i-th point；
Output unit, if for | dl-dl+1| < e then exports the RwWith the T, and according to the RwWith the T correction described in
The amount of state variation of robot；
Second return unit, if for | dl-dl+1| >=e enables l=l+1, returns and executes the operation for finding unit.
6. device as claimed in claim 5, which is characterized in that described device further include:
Acquiring unit, the correction parameter of the motion sensor for obtaining the robot, the correction parameter include linear rectify
Positive parameter and rotational correction parameter；
First computing unit, the state for being moved every time according to the robot calculate the robot in the secondary movement
Possible error increment direction and numerical value in the process, and the amount of state variation obtained with the motion sensor merges, operation obtains
To modified amount of state variation；
Unit is estimated, for merging the correction parameter with the modified amount of state variation, estimates to obtain the robot
Amount of state variation.
7. device as claimed in claim 5, which is characterized in that the preset termination condition includes:
The value of the k has been more than default the number of iterations；Alternatively,
The point cloud data collection PkError to the point cloud data collection X is less than preset error value.
8. device as claimed in claim 5, which is characterized in that described device further include:
Removal unit, for detecting the point to set Yk, the point is removed to set YkIn be unsatisfactory for the points pair of preset rules.
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| CN105955275B (en) * | 2016-05-26 | 2021-07-13 | 华讯方舟科技有限公司 | Robot path planning method and system |
| CN108053446A (en) * | 2017-12-11 | 2018-05-18 | 北京奇虎科技有限公司 | Localization method, device and electronic equipment based on cloud |
| CN108334080B (en) * | 2018-01-18 | 2021-01-05 | 大连理工大学 | Automatic virtual wall generation method for robot navigation |
| CN111473785B (en) * | 2020-06-28 | 2020-09-25 | 北京云迹科技有限公司 | Method and device for adjusting relative pose of robot to map |
| CN112650250A (en) * | 2020-12-23 | 2021-04-13 | 深圳市杉川机器人有限公司 | Map construction method and robot |
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| CN103247225A (en) * | 2012-02-13 | 2013-08-14 | 联想(北京)有限公司 | Instant positioning and map building method and equipment |
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