CN115657673B - Path planning optimization method and device, computer equipment and storage medium - Google Patents
Path planning optimization method and device, computer equipment and storage medium Download PDFInfo
- Publication number
- CN115657673B CN115657673B CN202211305378.3A CN202211305378A CN115657673B CN 115657673 B CN115657673 B CN 115657673B CN 202211305378 A CN202211305378 A CN 202211305378A CN 115657673 B CN115657673 B CN 115657673B
- Authority
- CN
- China
- Prior art keywords
- cell
- vector
- path planning
- cells
- value
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 58
- 238000005457 optimization Methods 0.000 title claims abstract description 30
- 230000003247 decreasing effect Effects 0.000 claims abstract description 16
- 238000012216 screening Methods 0.000 claims abstract description 7
- 238000004590 computer program Methods 0.000 claims description 14
- 230000005484 gravity Effects 0.000 claims description 14
- 238000010586 diagram Methods 0.000 description 10
- 238000004364 calculation method Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 4
- 238000012790 confirmation Methods 0.000 description 3
- 238000007689 inspection Methods 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 235000019800 disodium phosphate Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000009191 jumping Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Landscapes
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention discloses a path planning optimization method, a path planning optimization device, computer equipment and a storage medium. The method comprises the following steps: confirming a departure point cell, a target point cell and an obstacle cell; setting a vector direction and a vector increasing and decreasing value relation moving along different vector directions; according to the set vector direction and vector increasing and decreasing value relation, calculating the cell value of the next cell of the departure point cell moving to each direction respectively, and screening the cell corresponding to the maximum cell value as the next cell actually moving; and according to a preset judging relation, finishing path planning when the current point cell is judged to be the target point cell. The breadth-first method is optimized, the path planning function from the departure point to the target point is realized under the condition of insufficient computing capacity, and the method has the advantage of saving computing power.
Description
Technical Field
The present invention relates to the field of path planning technologies, and in particular, to a path planning optimization method, a path planning optimization device, a computer device, and a storage medium.
Background
Path planning is an important content of intelligent traffic systems and is also an important component of vehicle positioning and navigation systems. In addition, path planning is very important for the inspection path of operation and maintenance staff, the moving path of robot operation, the track path of robot arm movement and the like.
For path planning, various path planning methods are proposed in the related art, mainly including Dijkstra method, breadth-first method, a-method, and the like. For the breadth-first method, the operation amount is larger, and the breadth-first method can be optimized by the method A and the method Dijsktra, but under the condition of insufficient operation capability, the existing path planning method still has difficulty in realizing better path planning.
Disclosure of Invention
The invention aims to provide a path planning optimization method, a device, computer equipment and a storage medium, and aims to solve the problem that the existing path planning method is difficult to realize better path planning under the condition of insufficient operation capability.
In a first aspect, an embodiment of the present invention provides a path planning optimization method, including:
confirming a departure point cell, a target point cell and an obstacle cell;
setting a vector direction and a vector increasing and decreasing value relation moving along different vector directions;
According to the set vector direction and vector increasing and decreasing value relation, calculating the cell value of the departure point cell moving to the next cell in each direction respectively, and screening the cell corresponding to the maximum cell value as the next cell actually moving;
and according to a preset judging relation, finishing path planning when the current point cell is judged to be the target point cell.
In a second aspect, an embodiment of the present invention provides a path planning optimization apparatus, including:
a confirmation unit configured to confirm the departure point cell, the destination point cell, and the obstacle cell;
the setting unit is used for setting a vector direction and a vector increasing and decreasing value relation moving along different vector directions;
The calculating unit is used for respectively calculating the cell value of the next cell of the departure point cell moving to each direction according to the set vector direction and vector increasing and decreasing value relation, and screening the cell corresponding to the maximum cell value as the next cell actually moving;
and the judging unit is used for completing path planning when the current point cell is judged to be the target point cell according to the preset judging relation.
In a third aspect, an embodiment of the present invention provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the path planning optimization method described in the first aspect when executing the computer program.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium, where the computer readable storage medium stores a computer program, where the computer program when executed by a processor causes the processor to perform the path planning optimization method according to the first aspect.
The embodiment of the invention discloses a path planning optimization method, a path planning optimization device, computer equipment and a storage medium. The method comprises the following steps: confirming a departure point cell, a target point cell and an obstacle cell; setting a vector direction and a vector increasing and decreasing value relation moving along different vector directions; according to the set vector direction and vector increasing and decreasing value relation, calculating the cell value of the next cell of the departure point cell moving to each direction respectively, and screening the cell corresponding to the maximum cell value as the next cell actually moving; and according to a preset judging relation, finishing path planning when the current point cell is judged to be the target point cell. The embodiment of the invention optimizes the breadth-first method, realizes the path planning function from the departure point to the target point under the condition of insufficient computing capacity, and has the advantage of saving computing force.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a path planning optimization method according to an embodiment of the present invention;
Fig. 2 is a schematic sub-flowchart of a path planning optimization method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of another sub-flowchart of a path planning optimization method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of another sub-flowchart of a path planning optimization method according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of another sub-flowchart of a path planning optimization method according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of grid construction in a scenario provided by an embodiment of the present invention;
fig. 7 is a schematic diagram of path planning in a scenario provided by an embodiment of the present invention;
FIG. 8 is a schematic block diagram of a path planning optimization device provided by an embodiment of the present invention;
fig. 9 is a schematic block diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Referring to fig. 1, fig. 1 is a schematic flow chart of a path planning optimization method according to an embodiment of the present invention;
As shown in fig. 1, the method includes steps S101 to S104.
S101, confirming a departure point cell, a target point cell and an obstacle cell;
in this step, as shown in fig. 6, a scene is constructed into a grid according to a corresponding proportion; corresponding departure point cell a, target point cell B, and obstacle cell (hatched in the figure) are confirmed from the positions of the departure point, target point, and obstacle in the scene.
S102, setting a vector direction and a vector increasing and decreasing value relation moving along different vector directions;
s103, according to the set vector direction and vector increasing and decreasing value relation, calculating the cell value of the next cell of the departure point cell moving to each direction respectively, and screening the cell corresponding to the maximum cell value as the next cell actually moving;
In steps S102-S103, based on the constructed grid, different vector directions and vector increasing and decreasing value relationships moving along different vector directions are set for each case when the departure point cell moves up, down, left and right, so that the cell values of four next cells after moving from the current cell to the four directions can be calculated, and then the cell corresponding to the largest cell value is selected from the four cell values as the next cell actually moving, and it can be understood that one of the four directions is necessarily the previous cell in the moving process, and the corresponding three next cells can be calculated for reducing the calculation force.
S104, according to a preset judging relation, when the current point cell is judged to be the target point cell, path planning is completed.
In the embodiment, the method can be applied to a plurality of application scenes such as robot path planning, inspection task path planning, security task path planning and the like; the breadth-first method is optimized, the relation between the vector direction and the target summation is combined, and the problem of high method pressure caused by the way of diffuse and purposeless summation in the breadth-first method is avoided; the path planning function from the departure point to the target point is realized under the condition of insufficient computing capability.
In one embodiment, as shown in fig. 2, step S102 includes:
s201, setting a vector direction of movement of the departure point cell towards the target point cell as a gravity vector direction;
s202, increasing vector increment of a first preset value when a departure point cell moves one cell towards the gravity vector direction;
S203, when the departure point cell moves one cell in the non-gravity vector direction, increasing the vector decrement value of the first preset value.
In this embodiment, each time the departure point cell moves by one cell, the departure point cell is close to the target point cell or far from the target point cell, and for convenience of understanding, the direction from the departure point cell a to the target point cell B may be understood as the gravitational direction; when the sending point cell A moves to the next cell, if the next cell is close to the target point cell, the next cell is considered to move towards the gravity vector direction, and the cell value of the next cell needs to be increased by a vector increment of a first preset value; if the next cell is far from the target cell, it is considered that the cell value of the next cell is shifted away from the gravity vector direction by a vector decrement value (i.e., subtracting a first preset value) of the first preset value.
In one embodiment, as shown in fig. 3, step S102 further includes:
s301, setting a vector direction of transverse movement of a departure point cell relative to a target point cell as a transverse vector direction;
s302, when the departure point cell moves one cell in the transverse vector direction, increasing the vector increment of the second preset value.
In this embodiment, every time the departure point cell a moves by one cell, the lateral movement or the vertical movement is necessarily performed; that is, when the originating cell a moves to the next cell, if the next cell is moved laterally, the cell value of the next cell is increased by a vector increment of a second preset value.
In one embodiment, as shown in fig. 4, step S102 further includes:
S401, setting a vector direction of vertical movement of a departure point cell relative to a target point cell as a vertical vector direction;
and S402, increasing the vector increment of a third preset value when the departure point cell moves one cell in the vertical vector direction.
In this embodiment, every time the departure point cell a moves by one cell, the lateral movement or the vertical movement is necessarily performed; that is, when the sending cell a moves to the next cell, if the next cell is vertically moving, the cell value of the next cell is increased by the vector increment of the first third preset value.
In an embodiment, based on the above description of step S102, the set vector increment/decrement values are sequentially a first preset value, a second preset value, and a third preset value from high to low.
Taking a specific scene as an example for introduction: setting a first preset value alpha as 5, setting a second preset value gamma as 2 and setting a third preset value beta as 1;
as shown in fig. 7, when the cell a moves toward the cell A1, the cell value of the corresponding cell increases by α×1+β× 1=6 when the cell a moves in the gravity vector direction and the vertical vector direction, that is, each time one cell is moved, it can be obtained that the cell a moves toward the cell A1 as an actual movement path by calculation;
When the cell a moves to the cell A1, the obstacle cell is reached, and only the movement can be performed transversely, wherein the left transverse movement is taken as an example, that is, in the process that the cell A1 moves towards the cell A2, each moving cell belongs to the target point cell B, that is, each moving cell needs to subtract a first preset value alpha;
when the cell A1 moves to A2, the obstacle side is reached, and the cell A2 can move transversely to A3 or vertically to A4 (the cell above the cell A2 is simply calculated to be unsuitable and is not specifically described); if the cell A2 moves towards the cell A3, the cell A2 still belongs to the cell B far away from the target point, and a first preset value alpha needs to be continuously subtracted and a second preset value gamma needs to be added; if the cell A2 moves towards A4, which is close to the target cell B, a first preset value α and a third preset value β may be added, and the next cell of the cell A2 is known to be A4 by calculation, and the cell A4 continues to move towards A5;
And when the cell A4 moves to A5, the cell A5 can move vertically to A6 or transversely to A7; if the cell A5 moves towards A6, it is moving along the gravity vector direction and the vertical vector direction, a first preset value α and a third preset value γ may be added; if the cell A5 moves towards A7, it is moving along the gravity vector direction and the transverse vector direction, a first preset value α and a second preset value β may be added, and the next cell of the cell A5 is known to be A7 by calculation, and the movement from the cell A7 towards A8 is continued;
And when the cell A7 moves to A8, if the lateral movement is continued, the cell A8 is required to be vertically moved to the target cell B until the path planning is completed after the cell A8 reaches the target cell B.
In one embodiment, as shown in fig. 5, step S104 includes:
s501, calculating cell values of a plurality of next cells after the current point cell moves to all vector directions;
In this step, it should be understood that, in the process of determining, one of the four directions is necessarily the previous cell, and the corresponding three next cells may be determined to reduce the calculation force.
S502, judging whether the cell values of a plurality of next cells are all smaller than the cell value of the current point cell based on the cell value of the current point cell, if so, entering a step S503, and if not, jumping to a step S504;
s503, judging that the current point cell is a target point cell;
s504, judging that the current point cell is not the target point cell, and continuing to move.
In this embodiment, based on the determination process of steps S501 to S503, a determination is performed once every one cell is moved until the current point cell is confirmed as the target point cell after the determination relation is satisfied, and the path planning is completed.
The embodiment of the invention also provides a path planning optimizing device which is used for executing any embodiment of the path planning optimizing method. Specifically, referring to fig. 8, fig. 8 is a schematic block diagram of a path planning optimizing apparatus according to an embodiment of the present invention.
As shown in fig. 8, the path planning optimizing apparatus 800 includes: a confirmation unit 801, a setting unit 802, a calculation unit 803, and a judgment unit 804.
A confirmation unit 801 for confirming a departure point cell, a destination point cell, and an obstacle cell;
a setting unit 802 for setting a vector direction and a vector increment/decrement relation moving in different vector directions;
A calculating unit 803, configured to calculate, according to the set vector direction and vector increasing/decreasing value relationship, a cell value of a cell from the start point to a next cell in each direction, and screen a cell corresponding to the largest cell value as the next cell that is actually moved;
The judging unit 804 is configured to complete path planning when the current point cell is determined to be the target point cell according to the preset determining relationship.
The device can be applied to a plurality of application scenes such as robot path planning, inspection task path planning, security task path planning and the like; the breadth-first method is optimized, the relation between the vector direction and the target summation is combined, and the problem of high method pressure caused by the way of diffuse and purposeless summation in the breadth-first method is avoided; the path planning function from the departure point to the target point is realized under the condition of insufficient computing capability.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
The path planning optimizing means described above may be implemented in the form of a computer program which can be run on a computer device as shown in fig. 9.
Referring to fig. 9, fig. 9 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device 900 is a server, and the server may be a stand-alone server or a server cluster formed by a plurality of servers.
With reference to fig. 9, the computer device 900 includes a processor 902, a memory, and a network interface 905, which are connected by a system bus 901, wherein the memory may include a non-volatile storage medium 903 and an internal memory 904.
The non-volatile storage medium 903 may store an operating system 9031 and a computer program 9032. The computer program 9032, when executed, may cause the processor 902 to perform a path planning optimization method.
The processor 902 is operative to provide computing and control capabilities supporting the operation of the entire computer device 900.
The internal memory 904 provides an environment for the execution of a computer program 9032 in the non-volatile storage medium 903, which computer program 9032, when executed by the processor 902, may cause the processor 902 to perform a path planning optimization method.
The network interface 905 is used for network communication such as providing transmission of data information, etc. It will be appreciated by those skilled in the art that the architecture shown in fig. 9 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting of the computer device 900 to which the present inventive arrangements may be implemented, and that a particular computer device 900 may include more or less components than those shown, or may combine some components, or have a different arrangement of components.
Those skilled in the art will appreciate that the embodiment of the computer device shown in fig. 9 is not limiting of the specific construction of the computer device, and in other embodiments, the computer device may include more or less components than those shown, or certain components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may include only a memory and a processor, and in such embodiments, the structure and function of the memory and the processor are consistent with the embodiment shown in fig. 9, and will not be described again.
It should be appreciated that in an embodiment of the invention, the Processor 902 may be a central processing unit (Central Processing Unit, CPU), the Processor 902 may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL processors, DSPs), application SPECIFIC INTEGRATED Circuits (ASICs), off-the-shelf Programmable gate arrays (Field-Programmable GATEARRAY, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In another embodiment of the invention, a computer-readable storage medium is provided. The computer readable storage medium may be a non-volatile computer readable storage medium. The computer readable storage medium stores a computer program, wherein the computer program when executed by a processor implements the path planning optimization method of the embodiment of the invention.
The storage medium is a physical, non-transitory storage medium, and may be, for example, a U-disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus, device and unit described above may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (7)
1. A method of path planning optimization, comprising:
Constructing grids according to the corresponding proportion of the scene; confirming corresponding departure point cells, target point cells and obstacle cells according to the positions of the departure point, the target point and the obstacle in the scene;
setting the vector direction of the departure point cell moving towards the target point cell as a gravity vector direction, and increasing the vector increment of a first preset value when the departure point cell moves towards the gravity vector direction by one cell each time; when the departure point unit cell moves one unit cell in the direction which is not the gravity vector direction, increasing a vector decrement value of a first preset value;
According to the set vector direction and vector increasing and decreasing value relation, calculating the cell value of the departure point cell moving to the next cell in each direction respectively, and screening the cell corresponding to the maximum cell value as the next cell actually moving;
Calculating cell values of a plurality of next cells after the current point cell moves to all vector directions; based on the cell values of the current point cells, judging whether the cell values of a plurality of next cells are all smaller than the cell values of the current point cells, if so, judging that the current point cells are target point cells.
2. The path planning optimization method according to claim 1, wherein the setting of the vector direction and the vector increasing/decreasing value relationship moving in different vector directions further comprises: setting the vector direction of the transverse movement of the departure point cell relative to the target point cell as a transverse vector direction;
And when the departure point cell moves one cell towards the transverse vector direction, increasing the vector increment of a second preset value.
3. The path planning optimization method according to claim 2, wherein the setting of the vector direction and the vector increasing and decreasing value relationship of the movement in different vector directions further comprises:
Setting the vector direction of the vertical movement of the departure point cell relative to the target point cell as a vertical vector direction;
And when the departure point cell moves one cell towards the vertical vector direction, increasing the vector increment of a third preset value.
4. The path planning optimization method of claim 3, wherein the vector increment and decrement values are a first preset value, a second preset value and a third preset value in order from high to low.
5. A path planning optimization apparatus, comprising:
The confirming unit is used for constructing grids according to the corresponding proportion of the scene; confirming corresponding departure point cells, target point cells and obstacle cells according to the positions of the departure point, the target point and the obstacle in the scene;
The setting unit is used for setting the vector direction of the movement of the departure point unit cell towards the target point unit cell as the gravity vector direction; when the departure point cell moves one cell towards the gravity vector direction, increasing the vector increment of a first preset value; when the departure point unit cell moves one unit cell in the direction which is not the gravity vector direction, increasing a vector decrement value of a first preset value;
The calculating unit is used for respectively calculating the cell value of the next cell of the departure point cell moving to each direction according to the set vector direction and vector increasing and decreasing value relation, and screening the cell corresponding to the maximum cell value as the next cell actually moving;
the judging unit is used for calculating cell values of a plurality of next cells after the current point cell moves to all vector directions; based on the cell values of the current point cells, judging whether the cell values of a plurality of next cells are all smaller than the cell values of the current point cells, if so, judging that the current point cells are target point cells.
6. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the path planning optimization method according to any one of claims 1 to 4 when executing the computer program.
7. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, causes the processor to perform the path planning optimization method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211305378.3A CN115657673B (en) | 2022-10-24 | 2022-10-24 | Path planning optimization method and device, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211305378.3A CN115657673B (en) | 2022-10-24 | 2022-10-24 | Path planning optimization method and device, computer equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115657673A CN115657673A (en) | 2023-01-31 |
| CN115657673B true CN115657673B (en) | 2024-08-02 |
Family
ID=84991895
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211305378.3A Active CN115657673B (en) | 2022-10-24 | 2022-10-24 | Path planning optimization method and device, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115657673B (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111428919A (en) * | 2020-03-17 | 2020-07-17 | 深圳先进技术研究院 | Path planning method and device, electronic equipment and storage medium |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9599987B2 (en) * | 2012-09-27 | 2017-03-21 | Koninklijke Philips N.V. | Autonomous mobile robot and method for operating the same |
| US10133827B2 (en) * | 2015-05-12 | 2018-11-20 | Oracle International Corporation | Automatic generation of multi-source breadth-first search from high-level graph language |
| CN106357312B (en) * | 2016-09-12 | 2019-09-27 | 南京信息工程大学 | Lattice about subtract auxiliary breadth First tree search MIMO detection method |
| CN107392143B (en) * | 2017-07-20 | 2019-12-27 | 中国科学院软件研究所 | Resume accurate analysis method based on SVM text classification |
| US11630864B2 (en) * | 2020-02-27 | 2023-04-18 | Oracle International Corporation | Vectorized queues for shortest-path graph searches |
| CN113435650A (en) * | 2021-06-29 | 2021-09-24 | 上海东普信息科技有限公司 | Planning method, device and equipment for vehicle driving path and storage medium |
-
2022
- 2022-10-24 CN CN202211305378.3A patent/CN115657673B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111428919A (en) * | 2020-03-17 | 2020-07-17 | 深圳先进技术研究院 | Path planning method and device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115657673A (en) | 2023-01-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112016730B (en) | Port berth loading and unloading efficiency mining method, device, equipment and storage medium | |
| CN110634054B (en) | Fixed-point vehicle returning method and device and electronic equipment | |
| CN110232368B (en) | Lane line detection method, lane line detection device, electronic device, and storage medium | |
| CN102736940A (en) | Resource loading method | |
| CN111178342B (en) | Pose graph optimization method, device, equipment and medium | |
| CN115384508B (en) | Channel change decision method, device, equipment and readable storage medium | |
| EP4239596A1 (en) | Method and apparatus for detecting drivable area, mobile device and storage medium | |
| CN110555242B (en) | Method, device, equipment and storage medium for evaluating wind resistance of old towers | |
| CN111885618A (en) | Network performance optimization method and device | |
| CN103425526B (en) | A kind of control method of interface interchange and device | |
| CN114670823A (en) | Method, device and equipment for correcting running track and automatic driving vehicle | |
| CN115657673B (en) | Path planning optimization method and device, computer equipment and storage medium | |
| CN117389305A (en) | Unmanned aerial vehicle inspection path planning method, system, equipment and medium | |
| CN113935634A (en) | Track point processing method and device | |
| CN117664167A (en) | Transverse path planning method and device and unmanned vehicle | |
| CN113436068A (en) | Image splicing method and device, electronic equipment and storage medium | |
| CN117390448A (en) | Client model aggregation method and related system for inter-cloud federal learning | |
| US20230345289A1 (en) | Method, electronic device and computer program product for data transmission | |
| CN114379594B (en) | Safety driving corridor construction method and device, automatic driving vehicle and storage medium | |
| CN116481513A (en) | Map generation method and device and electronic equipment | |
| CN112020723A (en) | Training method and device for classification neural network for semantic segmentation, and electronic equipment | |
| CN111562609B (en) | Automatic excitation point obstacle avoidance method and system | |
| CN111220149B (en) | Navigation method, device and equipment of mobile equipment and computer storage medium | |
| CN113390425A (en) | Map data processing method, map data processing device, map data processing equipment and storage medium | |
| CN110704461A (en) | Data verification method and device, computer equipment and readable storage medium |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |