CN116185039A - AGV following method based on radar inter-frame difference maximum line area - Google Patents

AGV following method based on radar inter-frame difference maximum line area Download PDF

Info

Publication number
CN116185039A
CN116185039A CN202310249312.5A CN202310249312A CN116185039A CN 116185039 A CN116185039 A CN 116185039A CN 202310249312 A CN202310249312 A CN 202310249312A CN 116185039 A CN116185039 A CN 116185039A
Authority
CN
China
Prior art keywords
target
following
point cloud
point
cloud data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310249312.5A
Other languages
Chinese (zh)
Inventor
彭可
张志成
刘宏胜
贺劢勍
胡有章
邓学兵
李贲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Hezhong Huineng Technology Co ltd
Hunan Normal University
Original Assignee
Beijing Hezhong Huineng Technology Co ltd
Hunan Normal University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Hezhong Huineng Technology Co ltd, Hunan Normal University filed Critical Beijing Hezhong Huineng Technology Co ltd
Priority to CN202310249312.5A priority Critical patent/CN116185039A/en
Publication of CN116185039A publication Critical patent/CN116185039A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Optics & Photonics (AREA)
  • Electromagnetism (AREA)
  • Acoustics & Sound (AREA)
  • Optical Radar Systems And Details Thereof (AREA)

Abstract

The invention discloses an AGV following method based on a radar inter-frame difference maximum line area, which comprises the following steps: controlling the laser radar to scan to obtain a point cloud data array of a previous frame, storing the point cloud data array into a point cloud data buffer area, and continuing scanning to obtain a point cloud data array of a current frame; the current frame point cloud data array and the previous frame point cloud data array are subjected to differential processing; calculating and judging the maximum line area of continuous 1 in the differential result as a calibration following target; determining the polar diameter and the polar angle of a target following point, and comparing the polar diameter and the polar angle with a preset target following distance threshold value and a preset polar angle threshold value to realize target following; after confirming that the AGV trolley reaches a target following position, clearing the point cloud data buffer area, and acquiring a frame of complete Lei Dadian cloud data as the point cloud data of the previous frame identified by the next calibration following target; the invention reduces the requirements of the AGV trolley on the operation speed and the memory of the processor at any time, and improves the following instantaneity, stability and accuracy when the target moving speed is high and the size is large.

Description

AGV following method based on radar inter-frame difference maximum line area
Technical Field
The invention relates to the technical field of intelligent control of AGVs, robots, industrial mechanical arms and automatic driving automobiles, in particular to an AGV following method based on a radar inter-frame difference maximum line area.
Background
In industries such as manufacturing industry, commodity circulation, etc., the AGV dolly based on radar follows method has played important effect in the transport link, has solved the transportation difficult problems such as the labour demand is big, inefficiency and easy repetition.
However, at present, the application of the radar following technology in a real scene has some problems, in a scene of multiple obstacles, most of the existing radar target recognition methods are used for extracting characteristic data of different targets to construct a characteristic database by a clustering method, then the characteristic database is classified in a classifier, and finally a specific target is recognized, so that the characteristic database needs to be built, the algorithm is complex, the operation speed and the memory requirement on a processor are high, and the following instantaneity is weak; the object is easy to lose when the high-speed moving object is identified, and the accuracy of identifying the high-speed moving object is low.
In view of this, there is a need to develop a following method to solve the above-mentioned technical problems, reduce the requirements of the AGV trolley on the processor operation speed and the memory, and improve the instantaneity, stability and accuracy when following the fast and bulky targets in the multi-obstacle scene.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides an AGV following method based on the maximum line area of the difference between radar frames, which is used for reducing the operation speed and the memory requirement of an AGV trolley on a processor and enhancing the instantaneity, the stability and the accuracy of the AGV trolley when following a target with high speed and large volume in a multi-obstacle scene.
The technical scheme adopted by the invention is as follows:
an AGV following method based on radar inter-frame difference maximum line area comprises the following steps:
s1, controlling a laser radar to perform continuous scanning to obtain environmental point cloud data, wherein the environmental point cloud data comprise polar angle and distance information of an obstacle under a radar polar coordinate system, and the scanned point cloud data array of the previous frame is obtained
Figure SMS_1
Storing the point cloud data buffer area, and continuously scanning by the laser radar until a complete current frame point cloud data array +.>
Figure SMS_2
；
S2, the current frame point cloud data array
Figure SMS_3
And the previous frame point cloud data array +.>
Figure SMS_4
Differential and with target decision threshold +.>
Figure SMS_5
Comparing to obtain differential discrimination bit array +.>
Figure SMS_6
；
S3, analyzing and calculating the differential discrimination bit group
Figure SMS_7
Maximum line area of the middle continuous "1->
Figure SMS_8
Judging the maximum line area of the continuous' 1 +.>
Figure SMS_9
The corresponding point cloud is a calibration following target;
s4, taking the central scanning point of the calibration following target as a target following point
Figure SMS_10
Following the target with the point
Figure SMS_11
Is->
Figure SMS_12
And polar angle->
Figure SMS_13
A preset target following distance threshold +.>
Figure SMS_14
And polar angle threshold>
Figure SMS_15
Comparing to realize target following;
and S5, after the AGV trolley is confirmed to reach the target following position, the point cloud data buffer area is cleared, and a frame of complete radar point cloud data is obtained and used as the point cloud data of the previous frame identified by the next calibration following target.
Further, in the step S1, the lidar is a single-line lidar; the origin of the radar polar coordinate system is the origin of the AGV trolley coordinate system, the polar axis is the ordinate axis of the AGV trolley coordinate system, the positive direction of the polar angle is the anticlockwise direction, the scanning distance from the laser radar to the obstacle is taken as the polar diameter, and the polar diameter is inf when the obstacle exceeds the radar measuring range; the memory size of the point cloud data buffer area is the size of one frame of point cloud data.
Further, in step S2, the current frame point cloud data array is set
Figure SMS_16
And the previous frame point cloud data array +.>
Figure SMS_17
Differential and with target decision threshold +.>
Figure SMS_18
Comparing to obtain differential discrimination bit array +.>
Figure SMS_19
The method specifically comprises the following steps:
the formula of the difference judgment algorithm is as follows:
Figure SMS_20
；
wherein the method comprises the steps of
Figure SMS_21
For the current frame point cloud data array +.>
Figure SMS_22
At address->
Figure SMS_23
Data in->
Figure SMS_24
For the previous frame point cloud data array +.>
Figure SMS_25
At address->
Figure SMS_26
Data in->
Figure SMS_27
Determining a threshold for the target;
if it is
Figure SMS_28
In the differential discrimination bit array +.>
Figure SMS_29
The address t of (1) is assigned to>
Figure SMS_30
Preliminarily judging the target following point;
if it is
Figure SMS_31
In the differential discrimination bit array +.>
Figure SMS_32
The address t of (1) is assigned 0 +.>
Figure SMS_33
Judging that the target following point is not the target following point;
finally obtaining the differential discrimination bit group
Figure SMS_34
。
Further, the target determination threshold value
Figure SMS_35
Multiplying the speed of the following target for the desired calibration by a factor +.>
Figure SMS_36
And the time difference between the current frame and the previous frame +.>
Figure SMS_37
。
Further, in step S3, the differential discrimination bit set is analyzed and calculated
Figure SMS_38
Maximum line area of the middle continuous "1->
Figure SMS_39
Judging the maximum line area of the continuous' 1 +.>
Figure SMS_40
The corresponding point cloud is a calibration following target, and specifically comprises the following steps:
(1) The differential discrimination bit group is adopted in a cyclic traversal and pointer mode
Figure SMS_41
Grouping and summing according to the principle of continuous identical elements, comparing the sizes of the groups in turn, and preliminarily determining the maximum line area of the continuous' 1 +.>
Figure SMS_42
Following a target for the calibration;
(2) Setting a calibration following target line area threshold
Figure SMS_43
For preventing misrecognition, if->
Figure SMS_44
Then the maximum line area of the succession "1" is determined +.>
Figure SMS_45
The corresponding point cloud is the calibration following target; if->
Figure SMS_46
And judging that the target is misidentified, namely that the target is not identified at this time, and carrying out next calibration following target identification again.
Further, the differential discrimination bit group is adopted in a circulating traversing and pointer mode
Figure SMS_47
The method comprises the steps of carrying out grouping summation according to the principle of continuous identical elements, and comparing the sizes of all groups in sequence, and specifically comprises the following steps:
(1) Setting pointer variable to point to the differential discrimination bit array
Figure SMS_48
；
(2) From the differential number of discrimination bits
Figure SMS_49
Starting to perform loop judgment accumulation if judging address +.>
Figure SMS_50
Element in->
Figure SMS_51
And the latter address->
Figure SMS_52
Element in->
Figure SMS_53
If the element is equal to 1, element accumulation is carried out, and the element accumulation is stopped until the element is 0, so that the previous continuous 1-line area +.>
Figure SMS_54
；
(3) Continuing to judge until the element is 1, and then carrying out the cyclic judgment accumulation again to obtain the current continuous 1-line area
Figure SMS_55
And is continuous 1 line area +.>
Figure SMS_56
Size comparison is performed, larger values are retained and assigned to +.>
Figure SMS_57
While the address of the first element of the packet corresponding to said larger value is reserved and assigned +.>
Figure SMS_58
；
(4) Continuing the cycle comparison until the cycle is completed, and finally obtaining the maximum line area of the continuous' 1
Figure SMS_59
And the maximum line area of the consecutive "1->
Figure SMS_60
The address of the first element in the corresponding group is +.>
Figure SMS_61
。/>
Further, in step S4, the center scanning point of the calibration following target is taken as the target following point
Figure SMS_62
The target following point +.>
Figure SMS_63
Is->
Figure SMS_64
And polar angle->
Figure SMS_65
A preset target following distance threshold +.>
Figure SMS_66
And polar angle threshold>
Figure SMS_67
The comparison is carried out to realize target following, and the method specifically comprises the following steps:
(1) Calculating a center scanning point from the calibration following target as a target following point
Figure SMS_68
Determining the target following point +.>
Figure SMS_69
Is +.>
Figure SMS_70
And polar angle->
Figure SMS_71
：
Calculating the target following point
Figure SMS_74
Address->
Figure SMS_75
Obtaining the point cloud data array of the current frame +.>
Figure SMS_77
Is->
Figure SMS_73
Data in->
Figure SMS_76
And the previous frame point cloud data array +.>
Figure SMS_78
Is->
Figure SMS_79
Data in->
Figure SMS_72
；
If it is
Figure SMS_80
And->
Figure SMS_81
Then the target following point +.>
Figure SMS_82
Is->
Figure SMS_83
Get->
Figure SMS_84
And->
Figure SMS_85
Is smaller of (a);
if it is
Figure SMS_86
And->
Figure SMS_87
Then the target following point +.>
Figure SMS_88
Is->
Figure SMS_89
；
If it is
Figure SMS_90
And->
Figure SMS_91
Then the target following point +.>
Figure SMS_92
Is->
Figure SMS_93
；
The target following point
Figure SMS_94
Polar angle +.>
Figure SMS_95
Follow the point for the object>
Figure SMS_96
Address->
Figure SMS_97
Multiplying by radar angular resolution;
(2) Setting the target following distance threshold
Figure SMS_98
And the polar angle threshold +.>
Figure SMS_99
And follow the point with the target +.>
Figure SMS_100
Is->
Figure SMS_101
And polar angle->
Figure SMS_102
And comparing to realize the motion control of the AGV trolley:
if it is
Figure SMS_103
And->
Figure SMS_104
The system determines that the AGV trolley needs to be controlled to rotate anticlockwise or left
Figure SMS_105
；
If it is
Figure SMS_106
And->
Figure SMS_107
The system judges that the AGV trolley needs to be controlled to rotate clockwise or right
Figure SMS_108
；
If it is
Figure SMS_109
And->
Figure SMS_110
The system judges that the AGV trolley needs to be controlled to rotate clockwise or right
Figure SMS_111
；
If it is
Figure SMS_112
And->
Figure SMS_113
The system determines that the AGV trolley needs to be controlled to rotate anticlockwise or left
Figure SMS_114
；
If it is
Figure SMS_115
The system determines that the AGV needs to approach the target following point +.>
Figure SMS_116
Controlling the AGV trolley to be directed to the target following point +.>
Figure SMS_117
Is +.>
Figure SMS_118
；
If it is
Figure SMS_119
The system determines that the AGV needs to be far away from the target following point +.>
Figure SMS_120
Controlling the AGV trolley to be directed to the target following point +.>
Figure SMS_121
Is shifted in the opposite direction +.>
Figure SMS_122
。
Further, in step S5, the step of confirming that the AGV trolley reaches the target following position specifically includes the steps of:
estimating the position of a current radar polar coordinate system relative to an initial radar polar coordinate system through an AGV trolley positioning method, and carrying out coordinate transformation to obtain real-time transformation coordinates of the current radar polar coordinate system relative to the initial radar polar coordinate system
Figure SMS_123
And continuously transforming coordinates with the target +.>
Figure SMS_124
Comparing, and continuing to control the movement of the AGV until
Figure SMS_125
And->
Figure SMS_126
It is determined that the AGV trolley has reached the target following position.
Furthermore, the AGV following method based on the radar inter-frame difference maximum line area is not only suitable for target following of an AGV trolley, but also suitable for target following of robots, industrial mechanical arms and automatic driving automobiles.
The invention has the following beneficial effects:
(1) According to the AGV following method based on the radar inter-frame difference maximum line area, the maximum line area of the continuous 1' is obtained through a series of processes such as difference, threshold comparison and cyclic traversal on two adjacent frames of point cloud data to serve as a calibration following target;
(2) When the method identifies the targets with higher speed and larger volume, the largest line area of the continuous 1 is larger, so that the targets with high speed and large volume can be accurately identified in a multi-obstacle scene and are not easy to lose;
(3) The invention sets the polar angle threshold value
Figure SMS_127
The invention is not only suitable for the target following of the AGV trolley, but also suitable for the target following of robots, industrial mechanical arms and automatic driving automobiles.
The invention is described in further detail below with reference to the drawings and examples.
Drawings
For a clearer description of the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the related art of the embodiments will be briefly described, it will be apparent that the drawings in the following description are only embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person of ordinary skill in the art, in which:
FIG. 1 is a schematic flow chart of an AGV following method based on a radar inter-frame difference maximum line area according to an embodiment of the present invention;
FIG. 2 is a schematic structural view of a Mecanum wheel AGV provided by an embodiment of the present invention;
fig. 3 is a schematic diagram of a driving integrated module structure of a mecanum wheel type AGV trolley according to an embodiment of the present invention;
fig. 4 is a schematic diagram of radar inter-frame difference determination of a mecanum-type AGV trolley according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a post-target-identification rotation control of a Mecanum wheel AGV provided by an embodiment of the present invention;
in the figure: 1. an aluminum profile frame; 2. STM32 control box; 3. a drive integration module; 4. an inertial sensor; 5. an industrial personal computer; 6. a motor driver; 7. an ultrasonic module; 8. a laser radar; 9. a servo motor; 10. a speed reducer; 11. an L-shaped connecting plate; 12. a coupling; 13. a bearing seat; 14. mecanum wheel; 15. and a module mounting plate.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples, it being understood that the examples described herein are for the purpose of illustrating the present application only and are not intended to limit the present application.
Referring to fig. 2 and 3, an embodiment of the present invention provides a mecanum-type AGV trolley, comprising a vehicle body, a laser radar 8 arranged at the center of the top of the vehicle body, a control system arranged inside the vehicle body and connected with the laser radar 8, and an auxiliary sensing system arranged inside and around the vehicle body;
the vehicle body comprises an aluminum profile frame 1 and a driving integrated module 3;
the aluminum section frame is formed by connecting and fastening aluminum sections and aluminum corner brackets through T-shaped bolts;
the driving integrated module comprises a servo motor 9, a speed reducer 10, an L-shaped connecting plate 11, a coupler 12, a bearing seat 13, a Mecanum wheel 14 and a module mounting plate 15;
the laser radar 8 is an N10 TOF single-line laser radar, the radar scanning frequency is 10HZ, the radius of the radar measuring range is 0.5-11m, and the radar angular resolution is 0.5 degrees;
the control system is used for target identification and controlling the Mecanum wheel type AGV trolley to move along with a target and stop when encountering an obstacle during self-following;
the control system comprises an STM32 control box 2, an industrial personal computer 5 and a motor driver 6;
the chip in the STM32 control box 2 is STM32F103ZET6;
the industrial personal computer 5 runs an ROS system;
the auxiliary sensing system comprises an inertial sensor 4 and an ultrasonic module 7.
Referring to fig. 1, 2, 3, 4 and 5, the method for following an AGV based on a radar inter-frame difference maximum line area provided by the present invention is implemented in a mecanum wheel type AGV trolley provided in the present embodiment, and includes the steps of:
s101: controlling the laser radar 8 to perform continuous scanning to obtain environmental point cloud data, wherein the environmental point cloud data comprises polar angle and distance information of an obstacle under a radar polar coordinate system, and the scanned previous frame point cloud data array
Figure SMS_128
Storing the point cloud data buffer area, and continuing scanning by the laser radar 8 until a complete current frame point cloud data array is acquired +.>
Figure SMS_129
；
S102: setting the current frame point cloud data array
Figure SMS_130
And the previous frame point cloud data array +.>
Figure SMS_131
Differential and with target decision threshold +.>
Figure SMS_132
Comparing to obtain differential discrimination bit array +.>
Figure SMS_133
；
S103: analyzing and calculating the differential discrimination bit array
Figure SMS_134
Maximum line area of the middle continuous "1->
Figure SMS_135
Judging the maximum line area of the continuous' 1 +.>
Figure SMS_136
The corresponding point cloud is a calibration following target;
s104: taking the central scanning point of the calibration following target as a target following point
Figure SMS_137
Following the target with the point
Figure SMS_138
Is->
Figure SMS_139
And polar angle->
Figure SMS_140
A preset target following distance threshold +.>
Figure SMS_141
And polar angle threshold>
Figure SMS_142
Comparing to realize target following;
s105: after confirming that the Mecanum wheel type AGV reaches a target following position, clearing the point cloud data buffer area, and obtaining a complete frame of radar point cloud data as the point cloud data of the previous frame identified by the next calibration following target.
In this embodiment, the laser radar 8 is mounted at the center of the top of the vehicle body of the mecanum type AGV trolley, so that the origin and polar axis x of the radar polar coordinate system coincide with the origin and ordinate axis Y of the mecanum type AGV trolley coordinate system, the positive direction of the polar angle of the radar polar coordinate system is a counterclockwise direction, the scanning distance from the laser radar to the obstacle is a polar path, and the polar path is inf when the obstacle exceeds the radar measurement range.
In this embodiment, the industrial personal computer 5 controls the laser radar 8 to perform continuous scanning to obtain the environmental point cloud data, and in order to reduce the memory requirement, the point cloud data buffer area only needs to be set to the memory size of one frame of point cloud data.
In this embodiment, the industrial personal computer 5 sets the current frame point cloud data array
Figure SMS_143
And the previous frame point cloud data array +.>
Figure SMS_144
Differential and with target decision threshold +.>
Figure SMS_145
Comparing to obtain differential discrimination bit array +.>
Figure SMS_146
The method specifically comprises the following steps:
the formula of the difference judgment algorithm is as follows:
Figure SMS_147
；
wherein the method comprises the steps of
Figure SMS_148
For the current frame point cloud data array +.>
Figure SMS_149
At address->
Figure SMS_150
Data in->
Figure SMS_151
For the previous frame point cloud data array +.>
Figure SMS_152
At address->
Figure SMS_153
Data in->
Figure SMS_154
Determining a threshold for the target; />
If it is
Figure SMS_155
In the differential discrimination bit array +.>
Figure SMS_156
The address t of (1) is assigned to>
Figure SMS_157
Preliminarily judging the target following point;
if it is
Figure SMS_158
In the differential discrimination bit array +.>
Figure SMS_159
The address t of (1) is assigned 0 +.>
Figure SMS_160
Judging that the target following point is not the target following point;
finally obtaining the differential discrimination bit group
Figure SMS_161
。
In this embodiment, the industrial personal computer 5 analyzes and calculates the differential discrimination bit set
Figure SMS_162
Maximum line area of the middle continuous "1->
Figure SMS_163
Judging said succession'Maximum line area of 1->
Figure SMS_164
The corresponding point cloud is a calibration following target, and specifically comprises the following steps:
(1) The differential discrimination bit group is adopted in a cyclic traversal and pointer mode
Figure SMS_165
Grouping and summing according to the principle of continuous identical elements, comparing the sizes of the groups in turn, and preliminarily determining the maximum line area of the continuous' 1 +.>
Figure SMS_166
Following a target for the calibration;
(2) Setting a calibration following target line area threshold
Figure SMS_167
For preventing misrecognition, if->
Figure SMS_168
Then the maximum line area of the succession "1" is determined +.>
Figure SMS_169
The corresponding point cloud is the calibration following target; if->
Figure SMS_170
And judging that the target is misidentified, namely that the target is not identified at this time, and carrying out next calibration following target identification again.
In this example, the differential discrimination bit group is formed by adopting a cyclic traversal and pointer mode
Figure SMS_171
The method comprises the steps of carrying out grouping summation according to the principle of continuous identical elements, and comparing the sizes of all groups in sequence, and specifically comprises the following steps:
(1) Setting pointer variable to point to the differential discrimination bit array
Figure SMS_172
；
(2) From the differential number of discrimination bits
Figure SMS_173
Starting to perform loop judgment accumulation if judging address +.>
Figure SMS_174
Element in->
Figure SMS_175
And the latter address->
Figure SMS_176
Element in->
Figure SMS_177
If the element is equal to 1, element accumulation is carried out, and the element accumulation is stopped until the element is 0, so that the previous continuous 1-line area +.>
Figure SMS_178
；
(3) Continuing to judge until the element is 1, and then carrying out the cyclic judgment accumulation again to obtain the current continuous 1-line area
Figure SMS_179
And is continuous 1 line area +.>
Figure SMS_180
Size comparison is performed, larger values are retained and assigned to +.>
Figure SMS_181
While the address of the first element of the packet corresponding to said larger value is reserved and assigned +.>
Figure SMS_182
；
(4) Continuing the cycle comparison until the cycle is completed, and finally obtaining the maximum line area of the continuous' 1
Figure SMS_183
And the maximum line area of the consecutive "1->
Figure SMS_184
The address of the first element in the corresponding group is +.>
Figure SMS_185
。
As shown in fig. 4, in the present embodiment, the specific principle of identifying the desired calibration following target by radar inter-frame difference determination includes:
the target determination threshold value
Figure SMS_186
Following the speed of the target for the desired calibration +.>
Figure SMS_187
Multiplying by a coefficient->
Figure SMS_188
And the time difference between the current frame and the previous frame +.>
Figure SMS_189
I.e. < ->
Figure SMS_190
Wherein the coefficient->
Figure SMS_191
According to the radar scan frequency being 10HZ, the time difference is therefore +.>
Figure SMS_192
；
In the previous frame, the lidar 8 scans onto the desired target
Figure SMS_193
And->
Figure SMS_194
and Distance +.>
Figure SMS_195
In the current frame, the lidar 8 scans onto the desired target
Figure SMS_196
And->
Figure SMS_197
And +.sup.f with a distance of inf>
Figure SMS_198
Wherein inf represents that the distance of the scanning point is infinity;
due to
Figure SMS_208
And->
Figure SMS_205
Is of a distance inf such that the desired calibration follows the non-overlapping region of the target before and after movement
Figure SMS_210
And->
Figure SMS_203
Differential distance between inner front and rear frames +.>
Figure SMS_216
And->
Figure SMS_207
Greater than the target determination threshold +.>
Figure SMS_215
The non-overlapping region is similarly +.>
Figure SMS_206
And->
Figure SMS_212
The difference distance between all the front and rear frames is larger than the target judgment threshold value +.>
Figure SMS_199
At the same time due to the coefficient
Figure SMS_211
The appropriate said coefficient can be set>
Figure SMS_202
Ensuring that the desired calibration follows the overlapping area before and after the target movement +.>
Figure SMS_214
The differential distance of all the preceding and following frames includes +.>
Figure SMS_200
Are all greater than the target determination threshold +.>
Figure SMS_209
Finally, according to the differential decision algorithm formula, the non-overlapping area is +>
Figure SMS_201
And->
Figure SMS_213
Said overlap region->
Figure SMS_204
All of the inner is determined to be "1", so the faster the desired calibration follows the target, the larger the volume, and the larger the continuous "1" line area of the desired calibration follows the target.
In this embodiment, the industrial personal computer 5 selects the center scan point of the calibration following target as the target following point
Figure SMS_217
Calculating the target following point +.>
Figure SMS_218
Is->
Figure SMS_219
And polar angle->
Figure SMS_220
The method specifically comprises the following steps:
calculating the target following point
Figure SMS_222
Address->
Figure SMS_225
Obtaining the point cloud data array of the current frame +.>
Figure SMS_227
Is->
Figure SMS_223
Data in->
Figure SMS_224
And the previous frame point cloud data array +.>
Figure SMS_226
Is->
Figure SMS_228
Data in->
Figure SMS_221
；
If it is
Figure SMS_229
And->
Figure SMS_230
Then the target following point +.>
Figure SMS_231
Is->
Figure SMS_232
Get->
Figure SMS_233
And->
Figure SMS_234
Is smaller of (a);
if it is
Figure SMS_235
And->
Figure SMS_236
Then the target following point +.>
Figure SMS_237
Is->
Figure SMS_238
；
If it is
Figure SMS_239
And->
Figure SMS_240
Then the target following point +.>
Figure SMS_241
Is->
Figure SMS_242
；
The target following point
Figure SMS_243
Polar angle +.>
Figure SMS_244
Follow the point for the object>
Figure SMS_245
Address->
Figure SMS_246
Multiplying by the radar angular resolution, i.e. +.>
Figure SMS_247
；
And inf is the polar diameter of the obstacle exceeding the radar measurement range, and the radar angular resolution is 0.5 degrees.
In the present embodiment, as shown in FIG. 5, the target following distance threshold is set
Figure SMS_248
And the polar angle threshold +.>
Figure SMS_249
And follow the point with the target +.>
Figure SMS_250
Is->
Figure SMS_251
And polar angle->
Figure SMS_252
And comparing to realize the rotation control and the translation control of the Mecanum wheel type AGV:
if it is
Figure SMS_255
And->
Figure SMS_256
The system judges that the Mecanum wheel type AGV trolley needs to be controlled to rotate anticlockwise>
Figure SMS_258
At a polar angle threshold +.>
Figure SMS_254
And target following Point->
Figure SMS_257
For example, a->
Figure SMS_259
And->
Figure SMS_260
The Mecanum wheel type AGV trolley needs to rotate anticlockwiseTurn->
Figure SMS_253
；
If it is
Figure SMS_263
And->
Figure SMS_264
The system judges that the Mecanum wheel AGV needs to be controlled to rotate clockwise +.>
Figure SMS_266
At a polar angle threshold +.>
Figure SMS_262
And target following Point->
Figure SMS_265
For example, a->
Figure SMS_267
And->
Figure SMS_268
The Mecanum wheel AGV needs to rotate clockwise>
Figure SMS_261
；
If it is
Figure SMS_271
And->
Figure SMS_273
The system judges that the Mecanum wheel AGV needs to be controlled to rotate clockwise +.>
Figure SMS_275
At a polar angle threshold +.>
Figure SMS_270
And target following Point->
Figure SMS_272
For example, a->
Figure SMS_274
And->
Figure SMS_276
The Mecanum wheel AGV needs to rotate clockwise>
Figure SMS_269
；
If it is
Figure SMS_279
And->
Figure SMS_281
The system judges that the Mecanum wheel type AGV trolley needs to be controlled to rotate anticlockwise>
Figure SMS_283
At a polar angle threshold +.>
Figure SMS_278
And target following Point->
Figure SMS_280
For example, a->
Figure SMS_282
And is also provided with
Figure SMS_284
The Mecanum wheel AGV needs to rotate anticlockwise +>
Figure SMS_277
；/>
If it is
Figure SMS_285
The system determines that the Mecanum wheel AGV needs to approach the target following point +.>
Figure SMS_286
Controlling the microphoneThe trolley of the multi-wheeled AGV is +.>
Figure SMS_287
Is +.>
Figure SMS_288
；
If it is
Figure SMS_289
The system determines that the Mecanum wheel AGV needs to be far away from the target following point +.>
Figure SMS_290
Controlling the Mecanum wheel type AGV trolley to be directed to the target following point +.>
Figure SMS_291
Is shifted in the opposite direction +.>
Figure SMS_292
。
In the present embodiment, the rotation control is to maintain the target following point
Figure SMS_293
The polar angle under the Mecanum wheel type AGV trolley radar polar coordinate system is the polar angle threshold +.>
Figure SMS_294
The method comprises the steps of carrying out a first treatment on the surface of the The translational control can be decomposed into control in both directions of the abscissa and ordinate axes Y-axis in the mecanum-type AGV carriage coordinate system in order to maintain the target following point +.>
Figure SMS_295
The distance between the AGV and the origin of the radar polar coordinate system of the Mecanum wheel type AGV is the target following distance threshold value
Figure SMS_296
。
In this embodiment, the target following point is selected
Figure SMS_297
After that, the Mecanum wheel AGV needs to reach the target following position, and the specific steps include:
(1) According to the target following point
Figure SMS_298
Polar angle +.>
Figure SMS_299
Said target transformation coordinates +.>
Figure SMS_300
The industrial personal computer 5 calculates a transverse speed value +.A transverse speed value of the Mecanum wheel type AGV trolley on an abscissa axis of an initial Mecanum wheel type AGV trolley coordinate system>
Figure SMS_301
Longitudinal speed value of Y-axis of the ordinate axis +.>
Figure SMS_302
Angular velocity value about the vertical axis +.>
Figure SMS_303
Wherein n is the time required by the Mecanum wheel AGV to reach the target following position;
(2) The industrial personal computer 5 establishes communication with the STM32F103ZET6 of the STM32 control box 2, and the STM32F103ZET6 receives the transverse speed value sent by the industrial personal computer 5
Figure SMS_304
Said longitudinal speed value->
Figure SMS_305
And the angular velocity value +.>
Figure SMS_306
Data information;
(3) The STM32F103ZET6 calculates an inverse kinematics equation of the Mecanum wheel type AGV trolley, obtains speed information required by the servo motor 9 and sends the speed information to the motor driver 6, so that the movement control of the Mecanum wheel type AGV trolley is realized;
(4) The industrial personal computer 5 determines that the Mecanum wheel type AGV trolley reaches the target following position:
estimating the position of the current radar polar coordinate system of the Mecanum wheel AGV relative to the initial radar polar coordinate system through a fusion positioning algorithm of the IMU and the wheel type odometer, and carrying out coordinate transformation to obtain real-time transformation coordinates of the current radar polar coordinate system relative to the initial radar polar coordinate system
Figure SMS_307
The information of the IMU is measured by the inertial sensor 4, the information of the wheel type odometer is fed back by the motor driver 6, and the industrial personal computer 5 adopts a PID control strategy, and the real-time transformation coordinates +_ are continuously compared>
Figure SMS_308
Transforming coordinates with the object>
Figure SMS_309
Thereby continuing to control the movement of the Mecanum wheel AGV until +.>
Figure SMS_310
And->
Figure SMS_311
And determining that the Mecanum wheel AGV has reached the target following position.
In this embodiment, if the mecanum wheel type AGV trolley reaches the target following position, the point cloud data buffer area is cleared, and a frame of complete radar point cloud data is obtained as the point cloud data of the previous frame identified by the next calibration following target; if the Mecanum wheel type AGV trolley encounters an obstacle before reaching the target following position, the ultrasonic module 7 is used for detecting the linear distance between the Mecanum wheel type AGV trolley and the surrounding obstacle, and when the linear distance is smaller than the set safety distance, the Mecanum wheel type AGV trolley is controlled to stop so as to ensure safety.
In summary, the embodiment of the invention provides a Mecanum wheel type AGV trolley, which is used for realizing an AGV following method based on the maximum line area of radar inter-frame difference, and the Mecanum wheel type AGV trolley can accurately follow a fast and large target in a multi-obstacle scene, can realize 360-degree omnibearing gesture following, is not easy to lose the target in the following process, and has strong real-time performance and high safety.
The foregoing description of the embodiments of the present disclosure is not intended to limit the disclosure to the particular embodiments disclosed, but on the contrary, the intention is to cover all modifications, equivalents, alternatives, and alternatives falling within the spirit and principles of the disclosure.

Claims (9)

1. The AGV following method based on the radar inter-frame difference maximum line area is characterized by comprising the following steps:
s1, controlling a laser radar to perform continuous scanning to obtain environmental point cloud data, wherein the environmental point cloud data comprise polar angle and distance information of an obstacle under a radar polar coordinate system, and the scanned point cloud data array of the previous frame is obtained
Figure QLYQS_1
Storing the point cloud data buffer area, and continuously scanning by the laser radar until a complete current frame point cloud data array +.>
Figure QLYQS_2
；
S2, the current frame point cloud data array
Figure QLYQS_3
And the previous frame point cloud data array +.>
Figure QLYQS_4
Differential and with target decision threshold +.>
Figure QLYQS_5
Comparing to obtain differential discrimination bit array +.>
Figure QLYQS_6
；
S3, analyzing and calculating the differential discrimination bit group
Figure QLYQS_7
Maximum line area of the middle continuous "1->
Figure QLYQS_8
Judging the maximum line area of the continuous' 1 +.>
Figure QLYQS_9
The corresponding point cloud is a calibration following target;
s4, taking the central scanning point of the calibration following target as a target following point
Figure QLYQS_10
The target following point +.>
Figure QLYQS_11
Is of the polar diameter of (2)
Figure QLYQS_12
And polar angle->
Figure QLYQS_13
A preset target following distance threshold +.>
Figure QLYQS_14
And polar angle threshold>
Figure QLYQS_15
Comparing to realize target following;
and S5, after the AGV trolley is confirmed to reach the target following position, the point cloud data buffer area is cleared, and a frame of complete radar point cloud data is obtained and used as the point cloud data of the previous frame identified by the next calibration following target.
2. The AGV following method based on the radar inter-frame difference maximum line area according to claim 1, wherein in step S1, the lidar is a single-line lidar; the origin of the radar polar coordinate system is the origin of the AGV trolley coordinate system, the polar axis is the ordinate axis of the AGV trolley coordinate system, the positive direction of the polar angle is the anticlockwise direction, the scanning distance from the laser radar to the obstacle is taken as the polar diameter, and the polar diameter is inf when the obstacle exceeds the radar measuring range; the memory size of the point cloud data buffer area is the size of one frame of point cloud data.
3. The AGV following method based on the radar inter-frame difference maximum line area according to claim 1, wherein in step S2, the current frame point cloud data array is set
Figure QLYQS_16
And the previous frame point cloud data array +.>
Figure QLYQS_17
Differential and with target decision threshold +.>
Figure QLYQS_18
Comparing to obtain differential discrimination bit array +.>
Figure QLYQS_19
The method specifically comprises the following steps:
the formula of the difference judgment algorithm is as follows:
Figure QLYQS_20
；
wherein the method comprises the steps of
Figure QLYQS_21
For the current frame point cloud data array +.>
Figure QLYQS_22
At address->
Figure QLYQS_23
Data in->
Figure QLYQS_24
For the previous frame point cloud data array +.>
Figure QLYQS_25
At address->
Figure QLYQS_26
Data in->
Figure QLYQS_27
Determining a threshold for the target;
if it is
Figure QLYQS_28
In the differential discrimination bit array +.>
Figure QLYQS_29
The address t of (1) is assigned to>
Figure QLYQS_30
Preliminarily judging the target following point;
if it is
Figure QLYQS_31
In the differential discrimination bit array +.>
Figure QLYQS_32
The address t of (1) is assigned 0 +.>
Figure QLYQS_33
Judging that the target following point is not the target following point;
finally obtaining the differential discrimination bit group
Figure QLYQS_34
。
4. The AGV following method based on the radar inter-frame difference maximum line area according to claim 3, wherein the target determination threshold value
Figure QLYQS_35
Multiplying the speed of the following target for the desired calibration by a factor +.>
Figure QLYQS_36
And the time difference between the current frame and the previous frame
Figure QLYQS_37
。
5. The AGV following method based on the radar inter-frame difference maximum line area according to claim 1, wherein in step S3, the difference discrimination bit group is analyzed and calculated
Figure QLYQS_38
Maximum line area of the middle continuous "1->
Figure QLYQS_39
Judging the maximum line area of the continuous' 1 +.>
Figure QLYQS_40
The corresponding point cloud is a calibration following target, and specifically comprises the following steps:
(1) The differential discrimination bit group is adopted in a cyclic traversal and pointer mode
Figure QLYQS_41
Grouping and summing according to the principle of continuous identical elements, comparing the sizes of the groups in turn, and preliminarily determining the maximum line area of the continuous' 1 +.>
Figure QLYQS_42
Following a target for the calibration;
(2) Setting a calibration following target line area threshold
Figure QLYQS_43
For preventing misrecognition, if->
Figure QLYQS_44
Then the maximum line area of the succession "1" is determined +.>
Figure QLYQS_45
The corresponding point cloud is the calibration following target; if->
Figure QLYQS_46
And judging that the target is misidentified, namely that the target is not identified at this time, and carrying out next calibration following target identification again.
6. The AGV following method based on the radar inter-frame difference maximum line area according to claim 5, wherein the difference discrimination bit group is formed by adopting a cyclic traversal and pointer mode
Figure QLYQS_47
The method comprises the steps of carrying out grouping summation according to the principle of continuous identical elements, and comparing the sizes of all groups in sequence, and specifically comprises the following steps:
(1) Setting pointer variable to point to the differential discrimination bit array
Figure QLYQS_48
；
(2) From the differential number of discrimination bits
Figure QLYQS_49
Starting to perform loop judgment accumulation if judging address +.>
Figure QLYQS_50
Elements in
Figure QLYQS_51
And the latter address->
Figure QLYQS_52
Element in->
Figure QLYQS_53
If the element is equal to 1, element accumulation is carried out, and the element accumulation is stopped until the element is 0, so that the previous continuous 1-line area +.>
Figure QLYQS_54
；
(3) Continuing to judge until the element is 1, and then carrying out the cyclic judgment accumulation again to obtain the current continuous 1-line area
Figure QLYQS_55
And is continuous 1 line area +.>
Figure QLYQS_56
Size comparison is performed, larger values are retained and assigned to +.>
Figure QLYQS_57
While the address of the first element of the packet corresponding to said larger value is reserved and assigned +.>
Figure QLYQS_58
；
(4) Continuing the cycle comparison until the cycle is completed, and finally obtaining the maximum line area of the continuous' 1
Figure QLYQS_59
And the maximum line area of the consecutive "1->
Figure QLYQS_60
To pair ofThe address of the first element in the corresponding group is +.>
Figure QLYQS_61
。
7. The AGV following method based on the radar inter-frame difference maximum line area according to claim 1, wherein in step S4, the center scanning point of the calibration following target is used as a target following point
Figure QLYQS_62
The target following point +.>
Figure QLYQS_63
Is->
Figure QLYQS_64
And polar angle->
Figure QLYQS_65
A preset target following distance threshold +.>
Figure QLYQS_66
And polar angle threshold>
Figure QLYQS_67
The comparison is carried out to realize target following, and the method specifically comprises the following steps:
(1) Calculating a center scanning point from the calibration following target as a target following point
Figure QLYQS_68
Determining the target following point
Figure QLYQS_69
Is +.>
Figure QLYQS_70
And polar angle->
Figure QLYQS_71
：
Calculating the target following point
Figure QLYQS_73
Address->
Figure QLYQS_75
Obtaining the point cloud data array of the current frame +.>
Figure QLYQS_77
Is->
Figure QLYQS_74
Data in->
Figure QLYQS_76
And the previous frame point cloud data array +.>
Figure QLYQS_78
Is->
Figure QLYQS_79
Data in->
Figure QLYQS_72
；
If it is
Figure QLYQS_80
And->
Figure QLYQS_81
Then the target following point +.>
Figure QLYQS_82
Is->
Figure QLYQS_83
Get->
Figure QLYQS_84
And->
Figure QLYQS_85
Is smaller of (a);
if it is
Figure QLYQS_86
And->
Figure QLYQS_87
Then the target following point +.>
Figure QLYQS_88
Is->
Figure QLYQS_89
；
If it is
Figure QLYQS_90
And->
Figure QLYQS_91
Then the target following point +.>
Figure QLYQS_92
Is->
Figure QLYQS_93
；
The target following point
Figure QLYQS_94
Polar angle +.>
Figure QLYQS_95
Follow the point for the object>
Figure QLYQS_96
Address->
Figure QLYQS_97
Multiplying by radar angular resolution;
(2) Setting the target following distance threshold
Figure QLYQS_98
And the polar angle threshold +.>
Figure QLYQS_99
And follow the point with the target +.>
Figure QLYQS_100
Is->
Figure QLYQS_101
And polar angle->
Figure QLYQS_102
And comparing to realize the motion control of the AGV trolley:
if it is
Figure QLYQS_103
And->
Figure QLYQS_104
The system determines that the AGV needs to be controlled to rotate anticlockwise or left +>
Figure QLYQS_105
；/>
If it is
Figure QLYQS_106
And->
Figure QLYQS_107
The system judges that the AGV trolley needs to be controlled to rotate clockwise or right
Figure QLYQS_108
；
If it is
Figure QLYQS_109
And->
Figure QLYQS_110
The system judges that the AGV needs to be controlled to rotate clockwise or right>
Figure QLYQS_111
；
If it is
Figure QLYQS_112
And->
Figure QLYQS_113
The system determines that the AGV trolley needs to be controlled to rotate anticlockwise or left
Figure QLYQS_114
；
If it is
Figure QLYQS_115
The system determines that the AGV needs to approach the target following point +.>
Figure QLYQS_116
Controlling the AGV trolley to follow the target following point
Figure QLYQS_117
Is +.>
Figure QLYQS_118
；
If it is
Figure QLYQS_119
The system determines that the AGV needs to be far away from the target following point +.>
Figure QLYQS_120
Controlling the AGV trolley to follow the target following point
Figure QLYQS_121
Is shifted in the opposite direction +.>
Figure QLYQS_122
。
8. The method for following the AGV based on the radar inter-frame difference maximum line area according to claim 1, wherein in the step S5, the step of confirming that the AGV trolley reaches the target following position specifically comprises the steps of:
estimating the position of a current radar polar coordinate system relative to an initial radar polar coordinate system through an AGV trolley positioning method, and carrying out coordinate transformation to obtain real-time transformation coordinates of the current radar polar coordinate system relative to the initial radar polar coordinate system
Figure QLYQS_123
And continuously transforming coordinates with the target +.>
Figure QLYQS_124
Comparing, and continuing to control the movement of the AGV until
Figure QLYQS_125
And->
Figure QLYQS_126
It is determined that the AGV trolley has reached the target following position.
9. The AGV following method based on the radar inter-frame difference maximum line area according to claim 1 is not only suitable for target following of an AGV trolley, but also suitable for target following of a robot, an industrial mechanical arm and an automatic driving automobile.
CN202310249312.5A 2023-03-15 2023-03-15 AGV following method based on radar inter-frame difference maximum line area Pending CN116185039A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310249312.5A CN116185039A (en) 2023-03-15 2023-03-15 AGV following method based on radar inter-frame difference maximum line area

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310249312.5A CN116185039A (en) 2023-03-15 2023-03-15 AGV following method based on radar inter-frame difference maximum line area

Publications (1)

Publication Number Publication Date
CN116185039A true CN116185039A (en) 2023-05-30

Family

ID=86446343

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310249312.5A Pending CN116185039A (en) 2023-03-15 2023-03-15 AGV following method based on radar inter-frame difference maximum line area

Country Status (1)

Country Link
CN (1) CN116185039A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116360378A (en) * 2023-06-02 2023-06-30 北京中鼎昊硕科技有限责任公司 AGV trolley safety scheduling method based on data analysis
CN116594431A (en) * 2023-07-17 2023-08-15 湖南尖山智能科技有限责任公司 Hydraulic engineering robot following method, device and system and hydraulic engineering robot
CN117368876A (en) * 2023-10-18 2024-01-09 广州易而达科技股份有限公司 Human body detection method, device, equipment and storage medium

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116360378A (en) * 2023-06-02 2023-06-30 北京中鼎昊硕科技有限责任公司 AGV trolley safety scheduling method based on data analysis
CN116360378B (en) * 2023-06-02 2023-09-19 北京中鼎昊硕科技有限责任公司 AGV trolley safety scheduling method based on data analysis
CN116594431A (en) * 2023-07-17 2023-08-15 湖南尖山智能科技有限责任公司 Hydraulic engineering robot following method, device and system and hydraulic engineering robot
CN117368876A (en) * 2023-10-18 2024-01-09 广州易而达科技股份有限公司 Human body detection method, device, equipment and storage medium
CN117368876B (en) * 2023-10-18 2024-03-29 广州易而达科技股份有限公司 Human body detection method, device, equipment and storage medium

Similar Documents

Publication Publication Date Title
CN116185039A (en) AGV following method based on radar inter-frame difference maximum line area
CN111337941B (en) Dynamic obstacle tracking method based on sparse laser radar data
CN110745140B (en) Vehicle lane change early warning method based on continuous image constraint pose estimation
Wang et al. Automatic parking of vehicles: A review of literatures
CN106462968B (en) Method and device for calibrating a camera system of a motor vehicle
CN110243380B (en) Map matching method based on multi-sensor data and angle feature recognition
CN108398672B (en) Forward-tilting 2D laser radar mobile scanning-based pavement and obstacle detection method
CN108415413B (en) Intelligent forklift local obstacle avoidance path planning method based on circular useful domain
CN108759829B (en) Local obstacle avoidance path planning method for intelligent forklift
CN106569225A (en) Range-finding sensor based real-time obstacle avoidance method of driveless car
CN105300390B (en) The determination method and device of obstructing objects movement locus
CN112278891B (en) Carriage internal attitude detection method
CN113701780A (en) Real-time obstacle avoidance planning method based on A-star algorithm
CN111402328A (en) Pose calculation method and device based on laser odometer
CN115144849A (en) Sensor fusion for object avoidance detection
Li et al. An end-to-end fully automatic bay parking approach for autonomous vehicles
CN114137984A (en) Modular transmission platform and control method and path planning method thereof
Clarembaux et al. Perception and control strategies for autonomous docking for electric freight vehicles
CN111290396A (en) Automatic control method for unmanned ship for pipeline detection
CN114578817B (en) Control method of intelligent carrier based on multi-sensor detection and multi-data fusion
CN115525054A (en) Large-scale industrial park unmanned sweeper edge path tracking control method and system
Surendharan et al. Environment conscious automated vehicle navigation system using pid controller
CN111474940A (en) Water drop sequencing algorithm for determining effective driving area of intelligent driving vehicle based on vehicle body posture
CN117036505B (en) On-line calibration method and system for vehicle-mounted camera
CN112415516A (en) Method and device for sensing obstacle area in front of vehicle

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination