CN108489501A - A kind of fast path searching algorithm based on intelligent cut-through - Google Patents
A kind of fast path searching algorithm based on intelligent cut-through Download PDFInfo
- Publication number
- CN108489501A CN108489501A CN201810220237.9A CN201810220237A CN108489501A CN 108489501 A CN108489501 A CN 108489501A CN 201810220237 A CN201810220237 A CN 201810220237A CN 108489501 A CN108489501 A CN 108489501A
- Authority
- CN
- China
- Prior art keywords
- occupy
- ptcur
- advance
- counterclockwise
- point
- 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
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
Abstract
The present invention discloses a kind of fast path searching algorithm based on intelligent cut-through comprising：The grid map for obtaining region to be measured identifies starting point on grid map, the location information of target point and barrier, if encountering barrier, carries out occupy-place block and intelligently detour until avoiding obstacles using approximate algorithm calculating starting point to the path of target point；The occupy-place block intelligently detours, and is using the method for detouring or detouring clockwise counterclockwise；Wherein, it detours counterclockwise and specifically includes following process：The front of cycle criterion direction of advance whether occupy-place, direction of advance is deflected counterclockwise if occupy-place；If front takes a step forward without occupy-place；If side coil is deflected clockwise without occupy-place, to direction of advance, advance to make it be close to barrier；Until clearing the jumps, then continue to calculate position to the path of target point at this time using approximate algorithm.
Description
Technical field
The present invention relates to field of intelligent control, specifically design a kind of fast path search calculation based on intelligent cut-through
Method, can be used for based on cell occupy-place information map path search application, be particularly suitable for also robot obstacle or
The scenes such as the quick contour detecting of person.
Background technology
With further increasing for industrial robot application requirement, existing 2D path planning technology can not meet
Industrial robot is in the demand in many fields, and there is an urgent need to a set of fast paths that is ripe, can apply to three dimensions by people
Planning technology.
In robot research field, often by continuous environment use environment grid map (Grid graphs), Visual Graph
(Visibility graphs), navigation network (Navigation mesh), probability route map (Probabilistic road
Map, PRMs) and rapid discovery random tree (Rapidly exploring random trees) indicate.Wherein, grid map
Map i.e. based on cell occupy-place information, by map partitioning be N*N sizes cell, the position of each cell, such as
Fruit is accessible, then is set as 0, has obstacle to be then set as 1, and the occupy-place letter of a map thus can be indicated with a two Dimension Numerical Value
Breath namely grid map include the vertex of barrier in starting point (Pstart), target point (Pgoal) and space, and if only if
When line between two nodes does not intersect with the barrier in space, two nodes are connected with straight line and just constitute grid
Trrellis diagram.
In practical applications, common graph search method is heuritic approach, such as the path of A* (A-Star) algorithm searches
Suo Silu is the heuristic traversal based on figure.Given starting point and coordinate of ground point, algorithm needs are searched out from starting automatically
Point can pass to target point.A* (A-Star) would generally be used at this time as basic algorithm to realize.A*(A-Star)
Algorithm is the common inspiration that the most effective direct search method of shortest path and many other problems are solved in a kind of static road network
Formula algorithm.Formula is expressed as：F (n)=g (n)+h (n), wherein f (n) is from original state via state n to dbjective state
Cost estimates that it from original state to the actual cost of state n, h (n) is from state n to target-like that g (n), which is in state space,
The estimate cost of the optimal path of state.For route searching problem, state is exactly the node in figure, and cost is exactly distance.A*(A-
Star) algorithm, which is realized, is usually：Two tables are created first, and OPEN tables preserve all generated and the node do not investigated, CLOSED
The node accessed is recorded in table；Then the h (s) of starting point is calculated；Storing path, i.e., since target point, each node
It is moved along father node until starting point is to get to path；Starting point is put into OPEN tables.Specific A* (A-Star) algorithm
Basic step is as follows：
Step 1 safeguards an OPEN table, for recording cell to be visited；And starting point is put into OPEN tables；
Step 2 takes out head node from OPEN tables, as current point；
Step 3 judges whether current point surrounding cells lattice have blocking, if it is unobstructed, and have not visited before, then should
Point is inserted into OPEN tables and (is not repeatedly inserted into then in table)；
Step 4, circular recursion execute step 2 and 3, and until current point is equal to target point, then route searching is successful.If
OPEN tables are sky, then route searching fails.
A* (A-Star) algorithm can find destination path well, but the node that A* (A-Star) algorithm is expanded is too many,
It needs to search destination path, the step number needed to be traversed for is very more so that search takes long.The especially landform of spill, pole
In the case of end, algorithm needs all attempt all possibility one time, destination path finally can be just found, even if using various inspirations
The valuation functions of formula go to optimize, speed or less desirable.Referring to Fig. 1, such landform searches target point from starting point A
B searches for 1000 times and takes 421 milliseconds.If using the algorithm, it is per second can only 2000 mulitpath of concurrent processing search ask
It asks.This is far from being enough in many application scenarios.
Invention content
Therefore, node for above-mentioned A* (A-Star) algorithm is more, search the problem of time-consuming, and the present invention proposes a kind of base
In the fast path searching algorithm of intelligent cut-through.
Specifically, the fast path searching algorithm based on intelligent cut-through of the present invention, including：Obtain region to be measured
Grid map, on grid map identify starting point, target point and barrier location information, using approximate algorithm calculate starting point
To the path of target point, if encountering barrier, carries out occupy-place block and intelligently detour until avoiding obstacles；The occupy-place block intelligence
It can detour, be using the method for detouring or detouring clockwise counterclockwise；It detours counterclockwise and specifically includes following process：Cycle is sentenced
The front of disconnected direction of advance whether occupy-place, direction of advance is deflected counterclockwise if occupy-place；If front without occupy-place, before
Further；If side coil (direction of advance turn 90 degrees direction partially clockwise) carries out direction of advance inclined clockwise without occupy-place
Turn, advances to make it be close to barrier；Until clearing the jumps, then continue using approximate algorithm calculate at this time position to target
The path of point.Wherein, in order to simplify algorithm and effectively judge, the determining method to clear the jumps is：If the next point to rotate
On approaching route line segment and its extended line from starting point to target point, then it is assumed that clear the jumps, the process of rotating terminates.
Specifically, the fast path searching algorithm specifically comprises the following steps：
Step 1：The environmental information where robot is obtained, grid map is made, and marks rising for robot on grid map
The location information of initial point A, target point B and barrier；Foundation rotates queue, and is defined as follows：Up time is selected when encountering obstacle
Needle bypasses counterclockwise, and program is what sequence executed, when selection is clockwise about turning, then being put into queue counterclockwise, looks for
It reattempts when less than road and rotates counterclockwise；When selection rotates counterclockwise, then being put into queue clockwise, Lu Shizai is can not find
Trial rotates clockwise；
Step 2：It is approached from approximating function from starting point A to target point B, approximating function is exited if encountering obstacle, it will
Following 2 group information is inserted into the head for the queue that rotates, that is, first-in last-out：
{ around turning point [1] coordinate, direction of advance rotates clockwise }, and around turning point [1] coordinate, direction of advance, counterclockwise around
Turn }；
Step 3：From rotating, head node is taken out in queue, is herein { around turning point [1] coordinate, direction of advance rotates counterclockwise },
Execution rotates process；
Step 4：When rotating, around turning point [1], current direction of advance is deflected into the first predetermined angle towards counterclockwise, as before
Side is accessible, then takes a step forward, while detecting side (i.e. about 90 degree of directions of deflection clockwise) whether there is or not occupy-place, has before then continuing
Into not then direction of advance towards second predetermined angle of deflection clockwise；Preferably, first predetermined angle and second is preset
Angle is 45 degree；
Step 5：Step 4 is executed until clearing the jumps, then rotate end；
Step 6：Continue recurrence and execute step 2, until reaching target point.
Specifically, the approximating function is described as follows：From current point, always it is an attempt to walk towards terminal direction, because only permitting
Perhaps 8 direction movements, the i.e. directions x are added and subtracted, and the directions y plus-minus, so according to the size of changing coordinates and terminal point coordinate, the directions XY add
Subtract 1, indicates to move 1 step toward terminal, pseudocode is as follows：
if(ptCur.x>PtEnd.x), ptCur.x=ptCur.x+1；
if(ptCur.y>PtEnd.y), ptCur.y=ptCur.y+1；
if(ptCur.x<PtEnd.x), ptCur.x=ptCur.x-1；
if(ptCur.y<PtEnd.y), ptCur.y=ptCur.y -1.
The present invention is by above-mentioned occupy-place block intelligence detour scheme, and the node that solves A* (A-Star) algorithm is more, search consumption
The problem of duration, does not need to search out the shortest path that the path come is stringent, as long as can walk from starting point in many occasions
To target point, therefore, the application simulates the mode that the mankind solve the problems, such as, direct straight line is advanced from starting point to target point,
Encountering obstacle, just intelligence detours, and until reaching target point, actual measurement can obtain good search result, and computational efficiency averagely may be used
With decades of times faster than A* algorithm.
Description of the drawings
Fig. 1 is the route searching schematic diagram of A* (A-Star) algorithm；
Fig. 2 is the route searching schematic diagram of algorithm using the present invention；
Fig. 3 is the general flow chart of fast path searching algorithm；
Fig. 4 is the flow chart that occupy-place block intelligently detours；
Fig. 5 is the algorithmic procedure figure by starting point A to target point B in specific embodiment.
Specific implementation mode
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, and is only used for explaining the present invention, and is not considered as limiting the invention.
In many occasions, it does not need to search out the shortest path that the path come is stringent, as long as can go to from starting point
Target point, the application is using more easy fast path searching algorithm at this time, to improve computational efficiency.This is easy to be quick
Path search algorithm does not use the thinking of A* (A-Star) figure traversal, but simulates the mode that the mankind solve the problems, such as, from starting
Point is directly advanced with straight line to target point, and encountering obstacle, just intelligence detours, and until reaching target point, actual measurement can obtain good
Search result, computational efficiency averagely can decades of times faster than A* algorithm.
Referring to Fig. 2, using the algorithm announced herein, the same searching request of the Fig. 1 mentioned in processing and background technology,
1000 search of test machine only take 16 milliseconds, and search speed has 26 times of promotion with respect to 421 milliseconds of A* algorithms.Fig. 2
In, the path searched is approximate shortest path.
Referring to Fig. 3, the fast path searching algorithm based on intelligent cut-through of the present invention of invention, including：Acquisition waits for
Survey region grid map, on grid map identify starting point, target point and barrier location information, using approximate algorithm meter
Initial point is counted to the path of target point, if encountering barrier, occupy-place block is carried out and intelligently detours until avoiding obstacles；It is described
Occupy-place block intelligently detours, and is using the method for detouring or detouring clockwise counterclockwise.
Referring to Fig. 4, detours specifically include following process counterclockwise：The front of cycle criterion direction of advance whether occupy-place, such as
Occupy-place then deflects direction of advance counterclockwise；If front takes a step forward without occupy-place；If side coil (direction of advance
It turn 90 degrees direction partially clockwise) without occupy-place, then direction of advance is deflected clockwise, is advanced to make it be close to barrier；
Until clearing the jumps, then continue to calculate position to the path of target point at this time using approximate algorithm.In order to simplify algorithm and have
Effect judges that the determining method to clear the jumps is：If the next point to rotate is approaching route line segment from starting point to target point
And its on extended line, then it is assumed that clear the jumps, the process of rotating terminates.
In addition, it is identical as the algorithm principle to detour counterclockwise to detour clockwise, direction is opposite.
As a specific embodiment, Fig. 5 is illustrated once from starting point A searching routes to the algorithm mistake of target point B
Journey：
Process 1：Approached from starting point A to target point B using approximate algorithm, approach route be in actual physical situation,
Extended line as from starting point to target point.But in view of in grid environment, coordinate can only with the unit rounding of grid, so
When starting point and target point be not on 45 degree of lines, as multiple broken line head and the tail phases in the oblique line performance to grid coordinate of formation
It is even the same, very bad calculating, therefore route will be approached and simplified, making it not influences the logic of algorithm, but very good calculating,
Specifically, improved approximate algorithm pseudocode is as follows：
if(ptCur.x>PtEnd.x), ptCur.x=ptCur.x+1；
if(ptCur.y>PtEnd.y), ptCur.y=ptCur.y+1；
if(ptCur.x<PtEnd.x), ptCur.x=ptCur.x-1；
if(ptCur.y<PtEnd.y), ptCur.y=ptCur.y-1；
Process 2：Obstacle is encountered in approximate procedure, then exits approximating function, and following 2 group information is inserted into the team that rotates
Row：
{ around turning point [1] coordinate, direction of advance rotates clockwise }, and around turning point [1] coordinate, direction of advance, counterclockwise around
Turn }
Queue head is inserted it into, that is, first-in last-out；
Process 3：From rotating, head node is taken out in queue, is herein { around turning point [1] coordinate, direction of advance rotates counterclockwise },
The process that rotates of implementation procedure 4；
Process 4：When rotating, becoming arrow direction by current direction of advance towards 45 degree of deflection counterclockwise around turning point [1]
A then takes a step forward if front is accessible, while detecting side (turning 90 degrees direction partially clockwise) whether there is or not occupy-places, have, and continues
Advance, not then direction of advance towards 45 degree of deflection clockwise, becomes arrow direction b；
Process 5：It if executed 4 processes always, then can turn-take around obstacle, but because not knowing when pitch of the laps terminates, then
Can mistake around the positions diagramatic curve q.We introduce a most important rule at this time, i.e., if the next point to rotate exists
To being approached from starting point to target point on route line segment and its extended line, then the process of rotating terminates；
Process 6：Rotate end, then continues recurrence and execute step 2, after being judged by the rule, then along the directions arrow direction b
It advances, until encountering barrier again, advances along arrow direction c, judge later by above-mentioned rule, along arrow direction d
It moves on namely the travelling route of robot is gone all around barrier, until reaching target point B.
The present invention specifically when realizing, can establish a mark to clear the jumps by starting point A and target point B first
Line；When then executing the algorithm that above-mentioned occupy-place block intelligently detours, first in front of cycle criterion whether occupy-place, to advancing if occupy-place
Direction is deflected counterclockwise, if front takes a step forward without occupy-place, if (direction of advance deflects 90 to side coil clockwise
Spend direction) without occupy-place, then direction of advance is deflected clockwise, ensures to advance close to obstacle always, barrier is crossed until encountering
Then intelligently terminate to detour after hindering the markings of object, avoid around 360 degree.
Wherein, as a concrete implementation scheme, the specific Implementation of pseudocode of the markings to clear the jumps is as follows：
//////////////////////////////////////////////////////////////////////////
/**
@name:Judge certain point whether on forthright
@brief:For terminating to detour, whether the main thought of this function is to judge set point in starting point to target
On the straight line (or broken line) that point is constituted
@brief:Actually judge whether when on broken line can a little minor error, but since we are intended merely to
It determines when to terminate to detour, this originally fuzzy concept, so not influencing to search road result completely
@param ptTile:Current point
@param ptStart:Search road starting point
@param ptEnd:Search road end point
@return:
Although specifically showing and describing the present invention in conjunction with preferred embodiment, those skilled in the art should be bright
In vain, it is not departing from the spirit and scope of the present invention defined by the appended claims, it in the form and details can be right
The present invention makes a variety of changes, and is protection scope of the present invention.
Claims (6)
1. a kind of fast path searching algorithm based on intelligent cut-through, which is characterized in that including：Obtain the grid in region to be measured
Trrellis diagram, on grid map identify starting point, target point and barrier location information, using approximate algorithm calculate starting point arrive
The path of target point carries out occupy-place block and intelligently detours until avoiding obstacles if encountering barrier；
The occupy-place block intelligently detours, and is using the method for detouring or detouring clockwise counterclockwise；
Wherein, it detours counterclockwise and specifically includes following process：The front of cycle criterion direction of advance whether occupy-place, it is right if occupy-place
Direction of advance is deflected counterclockwise；If front takes a step forward without occupy-place；If side coil is without occupy-place, to advance side
To being deflected clockwise, advance to make it be close to barrier；Until clearing the jumps, then continue to calculate using approximate algorithm
Position to the path of target point at this time.
2. the fast path searching algorithm according to claim 1 based on intelligent cut-through, it is characterised in that：Cross barrier
Hinder the judging rules of object as follows：If the next point to rotate is approaching route line segment and its extended line from starting point to target point
On, then it is assumed that it clears the jumps.
3. the fast path searching algorithm according to claim 2 based on intelligent cut-through, it is characterised in that：This is quickly
Path search algorithm specifically comprises the following steps：
Step 1：The environmental information where robot is obtained, grid map is made, and marks the starting point of robot on grid map
A, the location information of target point B and barrier；Foundation rotates queue, and is defined as follows：When encountering obstacle selection clockwise or
Person bypasses counterclockwise, and program is what sequence executed, when selection is clockwise about turning, then being put into queue counterclockwise, can not find
It reattempts when road and rotates counterclockwise；When selection rotates counterclockwise, then being put into queue clockwise, reattempted when can not find road
It rotates clockwise；
Step 2：It is approached from approximating function from starting point A to target point B, approximating function is exited if encountering obstacle, it will be with
Lower 2 group informations are inserted into the head for the queue that rotates：
{ around turning point [1] coordinate, direction of advance rotates clockwise }, { around turning point [1] coordinate, direction of advance rotates counterclockwise }；
Step 3：From rotating, head node is taken out in queue, is herein { around turning point [1] coordinate, direction of advance rotates counterclockwise }, executes
Rotate process；
Step 4：When rotating, around turning point [1], current direction of advance is deflected into the first predetermined angle towards counterclockwise, such as front nothing
Obstacle then takes a step forward, while detecting side whether there is or not occupy-places, has, moves on, not then direction of advance towards clockwise partially
Turn the second predetermined angle；
Step 5：Step 4 is executed until clearing the jumps, then rotate end；
Step 6：Continue recurrence and execute step 2, until reaching target point.
4. the fast path searching algorithm according to claim 3 based on intelligent cut-through, it is characterised in that：Described
One predetermined angle is 45 degree.
5. the fast path searching algorithm according to claim 3 based on intelligent cut-through, it is characterised in that：Described
Two predetermined angles are 45 degree.
6. the fast path searching algorithm according to claim 1 based on intelligent cut-through, it is characterised in that：It is described to force
The pseudocode of nearly function is as follows：
if(ptCur.x>PtEnd.x), ptCur.x=ptCur.x+1；
if(ptCur.y>PtEnd.y), ptCur.y=ptCur.y+1；
if(ptCur.x<PtEnd.x), ptCur.x=ptCur.x-1；
if(ptCur.y<PtEnd.y), ptCur.y=ptCur.y -1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810220237.9A CN108489501A (en) | 2018-03-16 | 2018-03-16 | A kind of fast path searching algorithm based on intelligent cut-through |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810220237.9A CN108489501A (en) | 2018-03-16 | 2018-03-16 | A kind of fast path searching algorithm based on intelligent cut-through |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108489501A true CN108489501A (en) | 2018-09-04 |
Family
ID=63339574
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810220237.9A Pending CN108489501A (en) | 2018-03-16 | 2018-03-16 | A kind of fast path searching algorithm based on intelligent cut-through |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108489501A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110262512A (en) * | 2019-07-12 | 2019-09-20 | 北京机械设备研究所 | A kind of mobile robot is detached from the barrier-avoiding method and system of U-shaped obstacle trap |
| CN110426053A (en) * | 2019-07-12 | 2019-11-08 | 深圳市银星智能科技股份有限公司 | A kind of paths planning method and mobile robot |
| CN112697161A (en) * | 2020-12-15 | 2021-04-23 | 上海电机学院 | AGV path planning method, storage medium and terminal |
| CN114035581A (en) * | 2021-11-15 | 2022-02-11 | 上海交通大学宁波人工智能研究院 | Traversal path planning method for flaw detection robot with concave obstacle map |
| CN114326796A (en) * | 2021-12-15 | 2022-04-12 | 中国航空工业集团公司成都飞机设计研究所 | Rectangular search method suitable for anti-dive in aviation patrol |
| CN114460968A (en) * | 2022-02-14 | 2022-05-10 | 江西理工大学 | Unmanned aerial vehicle path searching method and device, electronic equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100121516A1 (en) * | 2008-11-13 | 2010-05-13 | Micro-Star International Co., Ltd. | Moving route planning method and navigation method for avoiding dynamic hindrances for mobile robot device |
| CN101738195A (en) * | 2009-12-24 | 2010-06-16 | 厦门大学 | Method for planning path for mobile robot based on environmental modeling and self-adapting window |
| CN101769754A (en) * | 2010-01-19 | 2010-07-07 | 湖南大学 | Quasi three-dimensional map-based mobile robot global path planning method |
| CN103335658A (en) * | 2013-06-19 | 2013-10-02 | 华南农业大学 | Autonomous vehicle obstacle avoidance method based on arc path |
| CN104317292A (en) * | 2014-09-16 | 2015-01-28 | 哈尔滨恒誉名翔科技有限公司 | Method for planning collision avoidance path of robot with complicated shape |
| CN107024210A (en) * | 2017-03-09 | 2017-08-08 | 深圳市朗空亿科科技有限公司 | A kind of Indoor Robot barrier-avoiding method, device and navigation system |
| US20170344007A1 (en) * | 2016-05-26 | 2017-11-30 | Korea University Research And Business Foundation | Method for controlling mobile robot based on bayesian network learning |
-
2018
- 2018-03-16 CN CN201810220237.9A patent/CN108489501A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100121516A1 (en) * | 2008-11-13 | 2010-05-13 | Micro-Star International Co., Ltd. | Moving route planning method and navigation method for avoiding dynamic hindrances for mobile robot device |
| CN101738195A (en) * | 2009-12-24 | 2010-06-16 | 厦门大学 | Method for planning path for mobile robot based on environmental modeling and self-adapting window |
| CN101769754A (en) * | 2010-01-19 | 2010-07-07 | 湖南大学 | Quasi three-dimensional map-based mobile robot global path planning method |
| CN103335658A (en) * | 2013-06-19 | 2013-10-02 | 华南农业大学 | Autonomous vehicle obstacle avoidance method based on arc path |
| CN104317292A (en) * | 2014-09-16 | 2015-01-28 | 哈尔滨恒誉名翔科技有限公司 | Method for planning collision avoidance path of robot with complicated shape |
| US20170344007A1 (en) * | 2016-05-26 | 2017-11-30 | Korea University Research And Business Foundation | Method for controlling mobile robot based on bayesian network learning |
| CN107024210A (en) * | 2017-03-09 | 2017-08-08 | 深圳市朗空亿科科技有限公司 | A kind of Indoor Robot barrier-avoiding method, device and navigation system |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110262512A (en) * | 2019-07-12 | 2019-09-20 | 北京机械设备研究所 | A kind of mobile robot is detached from the barrier-avoiding method and system of U-shaped obstacle trap |
| CN110426053A (en) * | 2019-07-12 | 2019-11-08 | 深圳市银星智能科技股份有限公司 | A kind of paths planning method and mobile robot |
| CN110262512B (en) * | 2019-07-12 | 2022-03-29 | 北京机械设备研究所 | Obstacle avoidance method and system for moving robot to separate from U-shaped obstacle trap |
| CN112697161A (en) * | 2020-12-15 | 2021-04-23 | 上海电机学院 | AGV path planning method, storage medium and terminal |
| CN114035581A (en) * | 2021-11-15 | 2022-02-11 | 上海交通大学宁波人工智能研究院 | Traversal path planning method for flaw detection robot with concave obstacle map |
| CN114326796A (en) * | 2021-12-15 | 2022-04-12 | 中国航空工业集团公司成都飞机设计研究所 | Rectangular search method suitable for anti-dive in aviation patrol |
| CN114326796B (en) * | 2021-12-15 | 2023-07-21 | 中国航空工业集团公司成都飞机设计研究所 | Rectangular search method suitable for aviation patrol anti-diving |
| CN114460968A (en) * | 2022-02-14 | 2022-05-10 | 江西理工大学 | Unmanned aerial vehicle path searching method and device, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108489501A (en) | A kind of fast path searching algorithm based on intelligent cut-through | |
| CN108444482B (en) | Unmanned aerial vehicle autonomous road finding and obstacle avoiding method and system | |
| CN110006430B (en) | Optimization method of track planning algorithm | |
| CN104077326B (en) | A kind of processing method and processing device of road data | |
| CN111289005B (en) | Path finding method based on A star optimization algorithm | |
| CN103017757B (en) | Engineering machinery entering path planning method and path planning apparatus | |
| CN109945873A (en) | A kind of mixed path planing method for indoor mobile robot motion control | |
| CN108775902A (en) | The adjoint robot path planning method and system virtually expanded based on barrier | |
| CN110220521B (en) | High-precision map generation method and device | |
| CN110006429A (en) | A kind of unmanned boat path planning method based on depth optimization | |
| CN107744663B (en) | Path finding method and device for artificial intelligence AI unit | |
| CN111338359A (en) | Mobile robot path planning method based on distance judgment and angle deflection | |
| CN106873630A (en) | A kind of flight control method and device, perform equipment | |
| CN106582023A (en) | Game path-searching method and apparatus | |
| CN114510056A (en) | Stable moving global path planning method for indoor mobile robot | |
| CN109240290A (en) | A kind of electric inspection process robot makes a return voyage determining method of path | |
| CN113359718B (en) | Method and equipment for fusing global path planning and local path planning of mobile robot | |
| CN108268042A (en) | A kind of path planning algorithm based on improvement Visual Graph construction | |
| CN115164907B (en) | Forest operation robot path planning method based on A-algorithm of dynamic weight | |
| WO2023125512A1 (en) | Navigation path planning method and apparatus, and storage medium | |
| CN104992466A (en) | Instant route-finding method for three-dimensional scene | |
| CN111337047B (en) | Unstructured road macroscopic path planning method based on multi-task point constraint | |
| CN108663050A (en) | A kind of paths planning method guiding RRT algorithms based on simulation of plant growth | |
| CN116501064A (en) | Path planning and obstacle avoidance method for photovoltaic power station cleaning robot | |
| CN111426328A (en) | Robot path planning method for static scene |
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 |