CN110319837A - Indoor complex condition path planning method for service robot - Google Patents
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Abstract
The invention provides a method for planning complex situation paths in a service robot room, which comprises the following steps: determining coordinate values of a starting point and a target point based on a grid map represented by a two-dimensional array, creating and initializing an OPEN list and a CLOSE list, and placing the starting point in the OPEN list; detecting an OPEN list, judging whether the path is searched successfully or not, and if not, carrying out the next step; alternative paths are searched by adopting a jumping point expansion rule, so that the expansion of invalid alternative points is reduced, and the path searching speed is accelerated; detecting connectivity among the path points, and removing useless path points; and adding information of steering judgment and required rotation angle for each path point based on the vector cross product and the vector dot product. The invention simultaneously detects the connectivity among the interval path points to remove redundant points in the path points, and reduces the stay of the robot at unnecessary path points to shorten the total path length. And the vector dot product and the vector cross product are used for carrying out steering judgment and corner calculation at the path point, so that the pose of the robot can be automatically adjusted at the path point.
Description
Technical field
The invention belongs to service robot Path Planning Technique fields, and in particular to complicated shape in a kind of service robot room
Condition paths planning method.
Background technique
In recent years, with the further change of the rapid development of robot technology and social demand, in robot field, phase
The research of pass technology is gradually extended from large-scale industrial robot to indoor service robot.Robot indoors in environment from
The mobile premise of leading boat is to complete path planning according to target point and algorithm, is then transported according to the path point planned
Dynamic walking.The path planning algorithm of high efficient and reliable is the key technology of Indoor Robot autonomous, while being also that robot is complete
At the important foundation of service role.At present in global path planning algorithm, But most of algorithms is all using A* algorithm or to be based on
The innovatory algorithm of A*, in large scene scale map, algorithm is limited to fixed neighbour's expansion strategy, so that pathfinding algorithm memory
Space consuming is big, operation time is longer and requires operational performance high.Which results in them to be applied to service robot
The requirement such as practicability, real-time is not able to satisfy when indoor path planning.Such as the Swamps algorithm that Pochter is proposed, using pre-
Grating map is decomposed into a series of adjacent regions by processing mode, then passes through the region in identification marking map without exploring
Achieve the purpose that reduce and expands useless alternative path point to accelerate search speed, although this successor path point expansion strategy is on road
Strength planning speed is risen, but algorithm arithmetic speed improving performance is limited.The TDHs algorithm that Sturtevant is proposed uses
The mode for improving the heuristic function accuracy of guiding search carrys out the speed of boosting algorithm, and algorithm would generally be precalculated and be saved
The distance between some key nodes in region.Although their speed quickly and also obtained solution be it is optimal, usually
Excessive memory can be consumed.
Described in summary, existing global path planning algorithm is had the drawback that
1. being limited to intrinsic neighbour's expansion strategy, a large amount of invalid alternative path point is expanded, algorithm operation is reduced
Performance；
2. needing to store the letter of a large amount of alternative path point when screening successor path point in fairly large map environment
Breath, needs certain storage performance；
3. planning that there are more redundant path points in the path completed；
4. path planning algorithm only gives critical path point, so that robot exists in the true application scenarios of robot
It can not be from main modulation pose at path point.
Summary of the invention
The object of the present invention is to provide complicated state paths planning methods in a kind of service robot room, while detecting interval
Redundant points do removal processing in connectivity pair path point between path point, reduce stop of the robot at unnecessary path point with
Shorten total path length.And carry out turning to judgement and corner calculating at path point with dot product and vector cross product, make
Robot can be from main modulation pose at path point.
The present invention provides complicated state paths planning methods in a kind of service robot room, include the following steps:
Step 1, the coordinate value of starting point and target point is determined based on the grid map indicated with two-dimensional array, is created and first
Beginningization OPEN list and CLOSE list, starting point is placed in OPEN list；Wherein, OPEN list has been opened up for storing
The path point opened up and do not investigated, CLOSE list is for recording the path point accessed；
Step 2, OPEN list is detected, judges whether path searches for success, if it is not, carrying out step 3；
Step 3, rule is expanded using jump point and finds alternative path, to reduce the expansion alternatively put in vain, accelerated path and search
Suo Sudu；
Step 4, the connectivity between path point is detected, useless path point is removed；
It step 5, is that the addition of each path point turns to judgement and required rotation angle based on vector cross product and dot product
Information.
Further, the step 2 includes:
Whether detection OPEN list is sky, if list is empty by OPEN, then it represents that route searching is not found unsuccessfully can walking along the street
Diameter；If OPEN list be not it is empty, the smallest path point of evaluation function value is chosen from the list, then by the path point from OPEN
It takes out, is placed into CLOSE list in list；
Check whether the path point is corresponding with the coordinate value of target point, if it is indicates route searching success, exit, if
Coordinate value does not correspond to, and carries out step 3.
Further, the evaluation function indicates are as follows:
F (n)=g (n)+h (n)；
Wherein, f (n), which refers to from initial path point by intermediate path point n to the cost estimation for reaching target point, g (n), is
In state space from initial point to intermediate path point n actual cost value, h (n) be from intermediate path point reach target point
The estimate cost value of optimal path.
Further, the step 3 includes:
Set the expansion rule of jump point；The expansion rule are as follows: if y is with the smallest value k so thatAnd
Meet one of following condition, then path point y is the jump point from path point x on the direction d: 1., path point y is target to condition
Point；2., when linearly expanding jump point, y path point contains is forced neighbours to condition；Condition 3., when diagonally opening up
When opening up jump point, the jump point z expanded via y path point along straight line or diagonal there are one, i.e. jump point z pass through y
Path point and meet condition 2.；
In the process of expansion, the expansion rule according to jump point is whole by the corresponding alternative path point in eight directions of path point
Expansion comes out, it is assumed that alternative point is indicated with m, then calculates the evaluation function value of each alternative point m, is chosen in alternative point and is evaluated letter
The smallest path point of numerical value is next specific item punctuate, then repeatedly step 2 and step 3, the target when path point found
Point obtains initial path Pn, otherwise algorithm search fails.
Further, the step 4 includes:
Since starting point, to resulting initial path point set PnIt is smoothed, judges current path point P one by onei
Preceding path point Pi-1With rear path point Pi+1Whether there are obstacles in direct-connected situation between two path points, if clear exists
Then by redundant path point PiIt deletes, barrier then continues to handle next path point judgement if it exists, until having traversed all
Path point until.
Further, the method packet that whether there are obstacles in direct-connected situation between two path points is judged described in step 4
It includes:
The slope value k of line between the coordinate value and two o'clock of two path points is inputted, point three kinds of situations are handled:
The case where one is line slope is not present between two o'clock, the i.e. straight line are perpendicular to X-axis, the opposite position of two path points
It sets in same vertical line；
Second situation is the case where slope of straight line is zero, i.e., straight line exists perpendicular to Y-axis, the relative position of two path points
In same horizontal line；
The third situation be when slope exists and the case where be not zero, two path point relative positions in the diagonal directions,
It first determines whether slope is greater than 1, determines and check starting according to direction, followed by according to the function f of straight line or inverse function f-1Meter
Another corresponding coordinate value is calculated, then gradually checks each point, completes whether the judgement containing barrier operates.
Further, the method that judgement is turned to described in step 5 includes:
If a=(ax,ay,az), b=(bx,by,bz) then the determinant expressions of vector product it is as follows:
Coordinate expressions are as follows:
A × b=(aybz-azbz)i+(azbx-axbz)j+(axby-aybx)k；
Decision rule:
As a × b > 0, for counterclockwise, i.e., vector b is in the left side of vector a；
As a × b < 0, for clockwise, i.e., vector b is on the right side of vector a；
As a × b=0, direction is constant, i.e. vector b and vector a are in same direction.
Further, the calculation method of rotation angle described in step 5 includes:
It is calculated based on vector angle, obtains rotation angle, the calculation formula of vector angle are as follows:
Wherein, a and b is two vectors of vector product.
Compared with prior art the beneficial effects of the present invention are:
1) alternative path is expanded mode and is replaced traditional neighbour expansion side by the way of jump point search strategy in the present invention
Formula is effectively reduced the expansion of invalid alternative path point, reduces requirement of the algorithm to storge quality, and make algorithm pair
The number of operations of OPEN list and CLOSE list substantially reduces, and is finally reached the purpose of boosting algorithm pathfinding speed.
2) present invention optimizes processing to the resulting initial path of algorithm, by using connection between detection interval path point
The mode of property, eliminates the path point of redundancy, effectively shortens total path length, smooth to a certain extent path,
Simultaneously but also the accumulation turning angle of robot greatly reduces, reduce time of the robot at path point for rotation.
3) present invention is that algorithm uses vector cross product and dot product to be added to steering for the path point in gained path and sentence
The information such as disconnected and rotation angle, are conducive to robot at path point from main modulation pose and action, meet robot motion's
Real-time.
Detailed description of the invention
Fig. 1 is the flow chart of the connectivity between present invention detection path point.
Specific embodiment
The present invention is described in detail for each embodiment shown in reference to the accompanying drawing, but it should be stated that, these
Embodiment is not limitation of the present invention, those of ordinary skill in the art according to these embodiments made by function, method,
Or equivalent transformation or substitution in structure, all belong to the scope of protection of the present invention within.
Complicated state paths planning method in a kind of service robot room is present embodiments provided, is broadly divided into following
Step:
One, algorithm initialization；
Two, OPEN list is detected；
Three, the expansion of alternative path point is carried out using jump point search strategy；
Four, the connectivity between path point is detected；
Five, the information of corner judgement and rotation angle is added for path point.
Algorithm initialization process in step 1 is as follows:
The map being applicable in by this algorithm is grating map, so the initialization of algorithm can be with firstly the need of setting one
The grating map indicated with two-dimensional array respectively indicates in map " impassabitity " in map with " 1 " and " 0 " and " can lead to
Row ", followed by determine two inputs of algorithm, the i.e. coordinate value of starting point S and target point E, it is finally to create and initialize
OPEN list and CLOSE list (cohort design completion can be used in two lists), wherein OPEN list has been opened up for storing
The path point opened up and do not investigated, CLOSE list is for recording the path point accessed.Finally starting point S is placed in
In OPEN list.
Detection OPEN list process in step 2 is as follows:
The main mesh of detection OPEN list is whether detection OPEN list is sky, if list is empty by OPEN, then it represents that path
Feasible path is not found in search unsuccessfully；If OPEN list is not empty, selection evaluation function f (n) value most size from the list
Path point n, path point n is taken out from OPEN list then, is then placed into CLOSE list.Then path is checked
Whether point n is corresponding with the coordinate value of target point E, if it is indicates route searching success, algorithm is exited, if coordinate value is not right
It answers, continues next step.Wherein evaluation function f (n) is indicated are as follows:
F (n)=g (n)+h (n)；
Here f (n) refers to from initial path point by intermediate path point n to the cost estimation for reaching target point, g (n)
It is the actual cost value of the point n from initial point to intermediate path in state space, h (n) is to reach target point from intermediate path point
Optimal path estimate cost value.The selection of h (n) evaluation function value generally has manhatton distance, Euclidean distance and Qie Bixue
Husband's distance etc., the present invention mainly uses Euclidean distance D.
The process alternatively put using the expansion of jump point search strategy in step 3 is as follows:
It mainly uses jump point to expand rule with jump point search strategy and finds alternative path, the purpose for the arrangement is that reducing nothing
The expansion alternatively put is imitated to accelerate route searching speed.The expansion rule of jump point is as follows: if y is with the smallest value k so thatOne of and meet following condition, then path point y is the jump point from path point x on the direction d: 1. path
Point y is target point；2. y path point, which contains, is forced neighbours when linearly expanding jump point；3. when diagonally expanding
When jump point, there can be a jump point z expanded via y path point along straight line or diagonal, i.e. jump point z passes through y
Path point and meet condition 2..In the process of expansion, algorithm is corresponding by eight directions of path point n according to the expansion rule of jump point
Alternative path point all expand out, it is assumed that alternative point is indicated with m, then calculates the evaluation function value of each alternative point m, select
Taking the smallest path point of evaluation function value in alternative point is next specific item punctuate, then repeatedly step 2 and step 3, until looking for
Target point E when the path point arrived, then algorithm obtains initial path Pn.Otherwise algorithm search fails.
The method of the connectivity between detection path point in step 4 is as follows:
For in path, there are redundant path points, and algorithm is between detecting path point to useless path by the way of connectivity
Point is removed.Since starting point S, to according to the resulting initial path point set P of algorithmnIt is smoothed operation, by
One judges current path point PiPreceding path point Pi-1With rear path point Pi+1With the presence or absence of barrier in direct-connected situation between two path points
Hinder object, by redundant path point P if clear existsiIt deletes, barrier then continues to judge next path point if it exists
Processing, until having traversed all path points.Detailed process is as shown in Figure 1.
In order to judge whether with the presence of barrier between path point, using algorithm 1, it is desirable that the coordinate of two path points of input
The case where slope value k of line between value and two o'clock, point three kinds of situation processing, one is line slope is not present between two o'clock,
I.e. the straight line is perpendicular to X-axis, and the relative position of two path points is in same vertical line；Second situation is that the slope of straight line is zero
The case where, i.e., straight line is perpendicular to Y-axis, and the relative position of two path points is in the same horizontal line；The third situation is when slope is deposited
And the case where be not zero, two path point relative positions in the diagonal directions, need to first determine whether slope is greater than 1, because
Inspection starting is decide according to direction, followed by according to the function f of straight line or inverse function f for whether slope is greater than 1-1It calculates and corresponds to
Another coordinate value, then gradually check each point, complete whether the judgement operation containing barrier.
The method that steering judgement and corner in step 5 calculate is as follows:
The judgement result in path point direction is left-hand rotation, right-hand rotation or keeps one in former direction, it is assumed that robot is protected always
Holding left-hand rotation movement then can be considered that robot is doing inverse time rotation, can be considered that robot exists if robot is always maintained at right-hand rotation movement
It rotates clockwise, i.e., the judgement of left-hand rotation right-hand rotation both direction, which can be converted at inflection point, rotates clockwise direction of rotation counterclockwise
The problem of judgement.Here judge between two vectors to be clockwise relationship using the vector product of vector herein or close counterclockwise
System.
If a=(ax,ay,az), b=(bx,by,bz) then the determinant expressions of vector product it is as follows:
Coordinate expressions are as follows:
A × b=(aybz-azbz)i+(azbx-axbz)j+(axby-aybx)k；
Decision rule:
As a × b > 0, for counterclockwise, i.e., vector b is in the left side of vector a；
As a × b < 0, for clockwise, i.e., vector b is on the right side of vector a；
As a × b=0, direction is constant, i.e. vector b and vector a are in same direction.
The rotation angle (0 ° to 180 °) of calculating robot is just needed after obtaining the direction of rotation at a certain path point,
The computational problem of rotation angle can also be converted into the problem of vector angle calculates.It is to calculate two vectors of a and b of vector product
Example, the calculation formula of vector angle are as follows:
The present invention has the following technical effect that.
1) alternative path is expanded mode and is replaced traditional neighbour expansion side by the way of jump point search strategy in the present invention
Formula is effectively reduced the expansion of invalid alternative path point, reduces requirement of the algorithm to storge quality, and make algorithm pair
The number of operations of OPEN list and CLOSE list substantially reduces, and is finally reached the purpose of boosting algorithm pathfinding speed.
2) present invention optimizes processing to the resulting initial path of algorithm, by using connection between detection interval path point
The mode of property, eliminates the path point of redundancy, effectively shortens total path length, smooth to a certain extent path,
Simultaneously but also the accumulation turning angle of robot greatly reduces, reduce time of the robot at path point for rotation.
3) present invention is that algorithm uses vector cross product and dot product to be added to steering for the path point in gained path and sentence
The information such as disconnected and rotation angle, are conducive to robot at path point from main modulation pose and action, meet robot motion's
Real-time.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included within the present invention.
Claims (8)
1. complicated state paths planning method in a kind of service robot room, which comprises the steps of:
Step 1, the coordinate value that starting point and target point are determined based on the grid map indicated with two-dimensional array, is created and is initialized
OPEN list and CLOSE list, starting point is placed in OPEN list；Wherein, OPEN list for store expanded and
The path point that do not investigate, CLOSE list is for recording the path point accessed；
Step 2, OPEN list is detected, judges whether path searches for success, if it is not, carrying out step 3；
Step 3, rule is expanded using jump point and finds alternative path, to reduce the expansion alternatively put in vain, accelerate route searching speed
Degree；
Step 4, the connectivity between path point is detected, useless path point is removed；
It step 5, is that the addition of each path point turns to the letter judged with required rotation angle based on vector cross product and dot product
Breath.
2. complicated state paths planning method in service robot room according to claim 1, which is characterized in that the step
Rapid 2 include:
Whether detection OPEN list is sky, if list is empty by OPEN, then it represents that route searching does not find feasible path unsuccessfully；If
OPEN list be not it is empty, the smallest path point of evaluation function value is chosen from the list, then by the path point from OPEN list
In take out, be placed into CLOSE list；
Check whether the path point is corresponding with the coordinate value of target point, if it is indicates route searching success, exit, if coordinate
Value does not correspond to, and carries out step 3.
3. complicated state paths planning method in service robot room according to claim 2, which is characterized in that described to estimate
Valence function representation are as follows:
F (n)=g (n)+h (n)；
Wherein, f (n) refers to from initial path point that by intermediate path point n, g (n) is in shape to the cost estimation for reaching target point
In state space from initial point to intermediate path point n actual cost value, h (n) be from intermediate path point reach target point it is best
The estimate cost value in path.
4. complicated state paths planning method in service robot room according to claim 3, which is characterized in that the step
Rapid 3 include:
Set the expansion rule of jump point；The expansion rule are as follows: if y is with the smallest value k so thatAnd meet
One of following condition, then path point y is the jump point from path point x on the direction d: 1., path point y is target point to condition；Item
2., when linearly expanding jump point, y path point contains is forced neighbours to part；Condition 3., when diagonally expanding jump point
When, the jump point z expanded via y path point along straight line or diagonal there are one, i.e. jump point z pass through y path point
And meet condition 2.；
In the process of expansion, the expansion rule according to jump point all expands the corresponding alternative path point in eight directions of path point
Out, it is assumed that alternative point is indicated with m, then calculates the evaluation function value of each alternative point m, chooses evaluation function value in alternative point
The smallest path point is next specific item punctuate, and then repeatedly step 2 and step 3, the target point when path point found obtain
To initial path Pn, otherwise algorithm search fails.
5. complicated state paths planning method in service robot room according to claim 4, which is characterized in that the step
Rapid 4 include:
Since starting point, to resulting initial path point set PnIt is smoothed, judges current path point P one by oneiBefore
Path point Pi-1With rear path point Pi+1Whether there are obstacles in direct-connected situation between two path points, will if clear exists
Redundant path point PiIt deletes, barrier then continues to handle next path point judgement if it exists, until having traversed all roads
Until diameter point.
6. complicated state paths planning method in service robot room according to claim 5, which is characterized in that step 4
Described in judge that whether there are obstacles in direct-connected situation between two path points method include:
The slope value k of line between the coordinate value and two o'clock of two path points is inputted, point three kinds of situations are handled:
The case where one is line slope is not present between two o'clock, the i.e. straight line exist perpendicular to X-axis, the relative position of two path points
In same vertical line；
Second situation is the case where slope of straight line is zero, i.e., straight line is perpendicular to Y-axis, and the relative position of two path points is same
On horizontal line；
The third situation be when slope exists and the case where be not zero, two path point relative positions in the diagonal directions, first
Judge whether slope is greater than 1, determines and check starting according to direction, followed by according to the function f of straight line or inverse function f-1Calculating pair
Then another coordinate value answered gradually checks each point, complete whether the judgement containing barrier operates.
7. complicated state paths planning method in service robot room according to claim 6, which is characterized in that step 5
Described in turn to the method for judgement and include:
If a=(ax,ay,az), b=(bx,by,bz) then the determinant expressions of vector product it is as follows:
Coordinate expressions are as follows:
A × b=(aybz-azbz)i+(azbx-axbz)j+(axby-aybx)k；
Decision rule:
As a × b > 0, for counterclockwise, i.e., vector b is in the left side of vector a；
As a × b < 0, for clockwise, i.e., vector b is on the right side of vector a；
As a × b=0, direction is constant, i.e. vector b and vector a are in same direction.
8. complicated state paths planning method in service robot room according to claim 7, which is characterized in that step 5
Described in rotation angle calculation method include:
It is calculated based on vector angle, obtains rotation angle, the calculation formula of vector angle are as follows:
Wherein, a and b is two vectors of vector product.
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| CN110967015A (en) * | 2019-11-20 | 2020-04-07 | 中国人民解放军国防科技大学 | Path planning method and system |
| CN110975288A (en) * | 2019-11-20 | 2020-04-10 | 中国人民解放军国防科技大学 | Geometric container data compression method and system based on jumping point path search |
| CN111412920A (en) * | 2020-04-08 | 2020-07-14 | 广东博智林机器人有限公司 | Method and device for processing mobile equipment towards turning path |
| CN112068551A (en) * | 2020-08-17 | 2020-12-11 | 盐城工学院 | RTB-based autonomous navigation and path planning method for drive-by-wire chassis |
| CN112129298A (en) * | 2020-09-28 | 2020-12-25 | 广州极飞科技有限公司 | Method, device and equipment for determining unmanned aerial vehicle air route and storage medium |
| CN112229419A (en) * | 2020-09-30 | 2021-01-15 | 隶元科技发展(山东)有限公司 | Dynamic path planning navigation method and system |
| CN112697161A (en) * | 2020-12-15 | 2021-04-23 | 上海电机学院 | AGV path planning method, storage medium and terminal |
| CN112947475A (en) * | 2021-03-22 | 2021-06-11 | 山东大学 | Laser navigation forklift type AGV vehicle-mounted system and method |
| CN113124849A (en) * | 2019-12-30 | 2021-07-16 | 广东博智林机器人有限公司 | Indoor path planning method and device, electronic equipment and storage medium |
| CN113607181A (en) * | 2021-08-05 | 2021-11-05 | 国网上海市电力公司 | Optimization method of jumping point search algorithm |
| CN114199266A (en) * | 2021-11-25 | 2022-03-18 | 江苏集萃智能制造技术研究所有限公司 | Path planning method for occupied target based on diagnosis guide service robot |
| CN115597621A (en) * | 2022-11-08 | 2023-01-13 | 广东嘉腾机器人自动化有限公司（Cn） | AGV path optimization and efficiency improvement path generation method |
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| CN110975288B (en) * | 2019-11-20 | 2023-08-29 | 中国人民解放军国防科技大学 | Geometric container data compression method and system based on jump point path search |
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| CN113124849B (en) * | 2019-12-30 | 2023-11-14 | 广东博智林机器人有限公司 | Indoor path planning method and device, electronic equipment and storage medium |
| CN111412920A (en) * | 2020-04-08 | 2020-07-14 | 广东博智林机器人有限公司 | Method and device for processing mobile equipment towards turning path |
| CN112068551B (en) * | 2020-08-17 | 2023-01-20 | 盐城工学院 | RTB-based autonomous navigation and path planning method for drive-by-wire chassis |
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| CN112129298A (en) * | 2020-09-28 | 2020-12-25 | 广州极飞科技有限公司 | Method, device and equipment for determining unmanned aerial vehicle air route and storage medium |
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| CN112697161A (en) * | 2020-12-15 | 2021-04-23 | 上海电机学院 | AGV path planning method, storage medium and terminal |
| CN112947475A (en) * | 2021-03-22 | 2021-06-11 | 山东大学 | Laser navigation forklift type AGV vehicle-mounted system and method |
| CN113607181A (en) * | 2021-08-05 | 2021-11-05 | 国网上海市电力公司 | Optimization method of jumping point search algorithm |
| CN114199266A (en) * | 2021-11-25 | 2022-03-18 | 江苏集萃智能制造技术研究所有限公司 | Path planning method for occupied target based on diagnosis guide service robot |
| CN115597621A (en) * | 2022-11-08 | 2023-01-13 | 广东嘉腾机器人自动化有限公司（Cn） | AGV path optimization and efficiency improvement path generation method |
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Application publication date: 20191011 |