CN108827309A - A kind of robot path planning method and the dust catcher with it - Google Patents
A kind of robot path planning method and the dust catcher with it Download PDFInfo
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- 238000010408 sweeping Methods 0.000 abstract description 8
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- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
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Abstract
The present invention provides a kind of robot path planning method and with its dust catcher, including extracting the effective coverage that robot can walk in 2D map, and the step of carrying out rasterizing division to effective coverage；Grid midpoint, spanning tree path are connected, robot carries out the step of walking without target walking or Objective according to tree path.Robot path planning method of the invention enables to robot to go through quickly, comprehensively all over entire effective coverage in no target, additionally it is possible to which quick, accurate calculation goes out the shortest path of robot to target when there is steps target.When this paths planning method is applied to sweeping robot, sweeping robot can be quickly allowed to sweep complete effective coverage, and the Objective for realizing sweeping robot cleans.
Description
Technical field
The present invention relates to field in intelligent robotics, and in particular to a kind of robot path planning method and the dust suction with it
Device.
Background technique
Path planning is one of the key technology for realizing walking robot control.The purpose is in certain environmental condition and
Under performance indicator requires, optimal or suboptimum a safe collisionless path from initial position to target position is found.For
Robot path planning, domestic and foreign scholars propose many planing methods, wherein mainly having Artificial Potential Field Method, neural network adaptive
Answer law of planning, genetic algorithm, ant group algorithm, particle swarm algorithm etc..In recent years, more and more scholars are to path planning problem
More focus on multi-intelligence algorithm when research to combine, to improve algorithm performance.Such as ImenChaari* is by genetic algorithm and ant colony
Algorithm combines, and the last stage generates initial information element with genetic algorithm and is distributed, and the rear stage asks optimal solution, Neng Gouyou with ant group algorithm
Effect combines the advantages of two algorithms, improves the search efficiency of ant colony, but may fall into local optimum；X Wang et al. proposes a kind of base
In particle group optimizing (Particle Swarm Optimization, PSO) and ant group optimization (Ant colony
Optimization, ACO) algorithm novel paths planning method, the algorithm utilize population environmental modeling method, generate from
Starting point is to the path of target point, the path profile pheromones generated before being then based on, finally, using improved optimization ant colony
Optimal path is found, this method can shorten search time, but, bad adaptability higher to environmental requirement；T Zhu, G Dong
Deng the algorithm that ant group algorithm is used in combination with Artificial Potential Field Method for proposition, algorithm potential field method initializes overall path, optimization
The paths ordering of every generation ant, and according to the ranking replacement pheromones in ant path, meanwhile, in the pheromones of elitist ants
Under help, using mould because of the intersection and mutation operation of algorithm on each generation path, which improves convergence rate and steady
It is qualitative, but potential field method itself is easily trapped into local deadlock, so the algorithm is easily trapped into local optimum when initially finding path.
Application No. is 201310604565.6 Chinese patent, disclose in a kind of wireless sensor network based on positive six side
The mobile anchor node path planing method of shape, the network include multiple static unknown nodes and a mobile anchor node,
Its step includes：Anchor node of walking is mobile with constant speed v, and every time interval t, using position this moment as the center of circle, R is logical
Believe radius, broadcast beacon message, beacon message includes position and the beacon ID of moment walking anchor node, the row for anchor node of walking
Path is walked to be positive hexagon.In fields of communication technology such as walking cellular network, ZigBee-networks, exist this with regular hexagon
For the path planning algorithm of most basic grid.
Application No. is 201410497805.1 Chinese patents to disclose a kind of robot static path planning method, packet
It includes：It sets target point and establishes Artificial Potential Field in body of a map or chart using target point as terminal；Particle swarm algorithm is introduced, in robot
Starting point be equipped with the population that quantity is m, the flying speed that i-th of particle walk in t is according to Artificial Potential Field and in conjunction with particle
Group's algorithm carries out Walk Simulation, during Walk Simulation, each particle shape from the path of origin-to-destination to each particle
At respective motion profile；Convergence is gathered in a track of most of particle gradually into a plurality of track, and then in body of a map or chart
Inside obtain the optimal walking path from origin-to-destination；Robot finally according to optimal walking path, is completed from origin-to-destination
Motion process.It combines potential field method, Grid Method and particle swarm optimization, but its algorithm is complicated, and path planning low efficiency is compeled
Being essential will be improved.
Summary of the invention
To solve the above problems, the present invention provides a kind of robot path planning method and with its dust catcher.This
The robot path planning method of invention enables to robot to go through quickly, comprehensively all over entire effective coverage, also in no target
Can when there is steps target quickly, accurate calculation go out the shortest path of robot to target.This paths planning method is applied to
When sweeping robot, sweeping robot can be quickly allowed to sweep complete effective coverage, and realize the target of sweeping robot
Property clean.
To realize the technical purpose, the technical scheme is that：A kind of robot path planning method, including it is following
Step：
S1：The effective coverage that robot can walk in 2D map is extracted, and rasterizing division is carried out to effective coverage；
S2：Grid midpoint, spanning tree path are connected, robot is carried out according to tree path without target walking or Objective row
It walks.
Further, the method for the effective coverage that robot can walk in 2D map being extracted in the step S1 includes following step
Suddenly：
T1：Robot establishes the 3D model of environment using depth camera using the entire environment of obstacle avoidance algorithm walking；
T2：3D model bottom surface in extraction step T1 is as effective coverage；
Preferably, the method that effective coverage is extracted in the step S1 includes the following steps：
E1：Robot utilizes depth camera disturbance in judgement, lights from starting, prolongs side close to obstacle and walks, and with starting
Point is target, is eventually returned to starting point, and mark track route and obstacle；
E2：The closure section of track route in step E1 is calculated, and removes the closure section at label obstacle, is obtained effectively
Region.
Further, the method that track route is closed section is calculated in the step E3 is：The second order for calculating track route is led
Number, and calculates its continuity in entire section, if second dervative continuously if track route be closed.
Further, the method that rasterizing divides in the step S1 is, to generate starting regular hexagon at robot place,
In effective coverage, to the regular hexagon that adjoins one another of starting regular hexagon outgrowth.
Preferably, the starting regular hexagon is identical with the regular hexagon size, and no more than circumferential direction outside robot
Circumscribed circle.
Further, the method without target walking in the step S2 includes the following steps：
P1：Grade classification is carried out to the tree path generated in step S2, with external positive six side of the starting regular hexagon
Shape is as level-one tree path, and the regular hexagon external using level-one tree path is as second level tree path, until being divided to the tree road
Diameter end；
P2：It walks forward from originating regular hexagon, walking is gone through all over every grade of tree path every time.
Further, the method that Objective is walked in the step S2 includes the following steps；
D1：To originate regular hexagon center as starting point, hexagonal centre where doing starting regular hexagon center to target
Primary vector；
D2：Judge whether primary vector is completely in effective coverage, the machine if effective coverage completely includes primary vector
Device people's straight line runs to target, and otherwise primary vector and effective coverage at least have two intersection points, and carry out step D3；
D3：Closer first intersection point in distance starting regular hexagon center, another intersection point are calculated as the second intersection point, robot
Straight line runs to the regular hexagon center of the first near intersections, and the tree path among the first intersection point to the second intersection point runs to
After two intersection points, straight line runs to target.
Further, the tree path in the step D3 among the first intersection point to the second intersection point runs to the side of the second intersection point
Method is：
The secondary vector to each adjacent regular hexagon center is done at the regular hexagon center of the first near intersections；Judgement
The angle of secondary vector and primary vector selects the lesser vector of angle to run to the second intersection position；
Or, the first intersection point is enumerated to trees all between the second intersection point path in advance in robot, and shortest tree path is calculated,
The shortest tree path of Robot runs to the second intersection point.
A kind of dust catcher, including the robot path planning method are carried out using this method without target cleaning or target
Property clean.
The beneficial effects of the present invention are：
Robot of the invention passes through the effective coverage for calculating robot ambulation that depth camera can be fast and reliable,
And regular hexagon rasterizing is utilized, it is further ensured based on grid midpoint line spanning tree path in conjunction with the precision of rasterizing
When carrying out without Objective walking, path can cover entire effective coverage for robot.Secondly, based on tree path and its grade classification
Method, robot of the invention can be enumerated method by angle or path, quickly calculate the shortest path of robot to target
Diameter.
To sum up, robot path planning method of the invention enables to robot to go through time quickly, comprehensively in no target
Entire effective coverage, additionally it is possible to which quick, accurate calculation goes out the shortest path of robot to target when there is steps target.This path
When planing method is applied to sweeping robot, sweeping robot can be quickly allowed to sweep complete effective coverage, and realize and sweep
The Objective of floor-washing robot cleans.
Detailed description of the invention
Fig. 1 is the flow chart of robot path planning method of the invention；
Fig. 2 is the method schematic diagram of spanning tree path of the present invention and grade classification；
Fig. 3 is robot of the invention without target walking method schematic diagram；
Fig. 4 is one of the implementation method of robot target walking of the invention；
Fig. 5 is the two of the implementation method of robot target walking of the invention.
Specific embodiment
Technical solution of the present invention will be clearly and completely described below.
It should be noted that the "inner" in the present invention refers to against robot starting point, "outside" refers to rises far from robot
The positional terms such as initial point and " periphery " of the invention are for absolutely proving paths planning method of the invention, can not manage
Solution is limitation of the invention.
As shown in Figure 1, a kind of robot path planning method, includes the following steps：
S1：The effective coverage that robot 1 can walk in 2D map is extracted, and rasterizing division is carried out to effective coverage；
S2：Grid midpoint, spanning tree path are connected, robot is carried out according to tree path without target walking or Objective row
It walks.
Further, the method for the effective coverage that robot can walk in 2D map being extracted in the step S1 includes following step
Suddenly：
T1：Robot 1 establishes the 3D model of environment using depth camera using the entire environment of obstacle avoidance algorithm walking；Its
Middle obstacle avoidance algorithm is the general technology means that those skilled in the art are easy to get, and this will not be repeated here.
T2：3D model bottom surface in extraction step T1 is as effective coverage；It should be noted that for there are the ground of obstacle
Side, robot can only establish the 3D rendering of obstacle, can not scan to ground, therefore depth camera establishes the 3D model of environment
In, can scan to above ground portion is 3D model bottom surface, and robot is using bottom surface as its walking effective coverage.Or by step T1
In 3D model to ground project, in projection reject obstacle projection section be effective coverage.
Preferably, the method that effective coverage is extracted in the step S1 includes the following steps：
E1：Robot utilizes depth camera disturbance in judgement, lights from starting, prolongs side close to obstacle and walks, and with starting
Point is target, is eventually returned to starting point, and mark track route and obstacle；
E2：The closure section of track route in step E1 is calculated, and removes the closure section at label obstacle, is obtained effectively
Region.That is, in embodiment, if robot can obstacle formation in one week be closed section, after removing the closure section
Closure section, then the maximum effective coverage that can be walked for robot, and the effective coverage be robot ambulation route side
Inside edge region.Using the calculated effective coverage of the present embodiment institute, have calculating speed fast, the advantages of high reliablity.
Further, the method that track route is closed section is calculated in the step E3 is：The second order for calculating track route is led
Number, and calculates its continuity in entire section, if second dervative continuously if track route be closed.
Further, the method that rasterizing divides in the step S1 is to generate starting regular hexagon 2 at place with robot 1
In effective coverage, to the regular hexagon that adjoins one another of starting regular hexagon outgrowth.As shown in Fig. 2, in starting regular hexagon 2
Six sides outside grow first lap regular hexagon respectively, regular hexagon is enclosed in the outer continued growth second of first lap regular hexagon, if positive six
Side shape then stops the growth for changing direction, until effective region is completely covered in regular hexagon in the imbricate of the effective coverage.
Specifically, being a kind of a kind of schematic diagram of effective coverage dissolved using regular hexagon grid as in Figure 3-5.
Preferably, the starting regular hexagon is identical with the regular hexagon size, and no more than circumferential direction outside robot
Circumscribed circle establishes the precision of rasterizing further in the case where ensuring that robot path can cover entire effective coverage.
Further, the method without target walking in the step S2 includes the following steps：
P1：Grade classification is carried out to the tree path generated in step S2, with external positive six side of the starting regular hexagon
Shape is as level-one tree path, and the regular hexagon external using level-one tree path is as second level tree path, until being divided to the tree road
Diameter end；
P2：It walks forward from originating regular hexagon, walking is gone through all over every grade of tree path every time.Rasterizing as shown in Figure 3
Region in, all regular hexagons that the first circular arc 5 passes through are from positive six side of first lap that grows out of starting regular hexagon 2
Shape, therefore answering robot to first lap regular hexagon center is level-one tree path, similarly, the second circular arc 6 is being passed through the second circle just
Hexagon, therefore it is second level tree path that robot is enclosed from first lap regular hexagon center to second.Robot 1 is lighted from starting, first
It first goes through along the first circular arc 5 all over level-one tree path, then run to second level tree path and goes through time, times that completion is walked without target
Business.It should be noted that robot of the invention can also be lighted from starting, the extraction effective coverage in step S1 is carried out on one side
With rasterizing partiting step, the tree path generated after each stepping in an edge is advanced, thus as a kind of new obstacle avoidance algorithm.Or
Person says that robot of the invention can further calculate effective coverage, and in depth camera according to depth camera disturbance in judgement
Propagating Tree path in head visual range further such that robot avoids obstacle, and is quickly gone through all over entire effective coverage.
Further, the method that Objective is walked in the step S2 includes the following steps；
D1：To originate 2 center of regular hexagon as starting point, starting regular hexagon center is done to 9 place hexagonal centre of target
Primary vector 7；
D2：Judge whether primary vector 7 is completely in effective coverage, as shown in figure 4, if effective coverage completely includes
Then robot straight line runs to target to one vector, and otherwise primary vector and effective coverage at least have two intersection points, and are walked
Rapid D3；
D3：Closer first intersection point in distance starting regular hexagon center, another intersection point are calculated as the second intersection point, robot
Straight line runs to the regular hexagon center of the first near intersections, and the tree path among the first intersection point to the second intersection point runs to
After two intersection points, straight line runs to target.In other words, robot of the invention can not straight line reach target when, first straight line reach
Effective coverage edge (the first intersection point) recycles regular hexagon rasterizing, and spanning tree path simultaneously carries out grade classification, judges target
Or second the path of tree where intersection point grade, robot reaches target or second according to rank difference n, along tree path walking n step
Intersection point.
Further, the tree path in the step D3 among the first intersection point to the second intersection point runs to the side of the second intersection point
Method is：
As shown in figure 5, doing to each adjacent regular hexagon center at the regular hexagon center of the first near intersections
Two vectors 8；Judge the angle of secondary vector 8 Yu primary vector 7, the lesser vector of angle is selected to run to the second intersection position；
In other words, by judging the direction in the first intersection point next stage tree path and target, the nearest tree path of choice direction in the present invention
Advance, so that directive advance to target.
Or, the first intersection point is enumerated to trees all between the second intersection point path in advance in robot, and shortest tree path is calculated,
The shortest tree path of Robot runs to the second intersection point.Regardless of enumerating mode using vector angle mode or tree path, finally
Calculated shortest path is the shortest path of identical step number, and the planning path method of Objective of the present invention can be quickly found out
Robot to target point shortest path.
A kind of dust catcher, including the robot path planning method are carried out using this method without target cleaning or target
Property clean.
For those of ordinary skill in the art, without departing from the concept of the premise of the invention, it can also do
Several modifications and improvements out, these are all within the scope of protection of the present invention.
Claims (10)
1. a kind of robot path planning method, which is characterized in that include the following steps：
S1：The effective coverage that robot can walk in 2D map is extracted, and rasterizing division is carried out to effective coverage；
S2：Grid midpoint, spanning tree path are connected, robot is carried out according to tree path without target walking or Objective walking.
2. robot path planning method according to claim 1, which is characterized in that extract 2D map in the step S1
The method for the effective coverage that middle robot can walk includes the following steps：
T1：Robot establishes the 3D model of environment using depth camera using the entire environment of obstacle avoidance algorithm walking；
T2：3D model bottom surface in extraction step T1 is as effective coverage.
3. robot path planning method according to claim 1, which is characterized in that extract effective district in the step S1
The method in domain includes the following steps：
E1：Robot utilizes depth camera disturbance in judgement, lights from starting, prolongs side close to obstacle and walks, and is with starting point
Target is eventually returned to starting point, and marks track route and obstacle；
E2：The closure section of track route in step E1 is calculated, and removes the closure section at label obstacle, obtains effective district
Domain.
4. robot path planning method according to claim 3, which is characterized in that calculate walking road in the step E3
Line closure section method be：The second dervative of track route is calculated, and calculates its continuity in entire section, if second order
Continuously then track route is closed derivative.
5. robot path planning method according to claim 1, which is characterized in that rasterizing divides in the step S1
Method be that starting regular hexagon is generated with place where robot, in effective coverage, to originating regular hexagon outgrowth each other
The regular hexagon to connect.
6. robot path planning method according to claim 5, which is characterized in that the starting regular hexagon and described
Regular hexagon size is identical, and no more than circumscribed circle circumferential outside robot.
7. robot path planning method according to claim 5, which is characterized in that walk in the step S2 without target
Method include the following steps：
P1：Grade classification is carried out to the tree path generated in step S2, is made with the regular hexagon that the starting regular hexagon is external
For level-one tree path, the regular hexagon external using level-one tree path is as second level tree path, until being divided to the tree path end
End；
P2：It walks forward from originating regular hexagon, walking is gone through all over every grade of tree path every time.
8. robot path planning method according to claim 5, which is characterized in that Objective is walked in the step S2
Method include the following steps；
D1：To originate regular hexagon center as starting point, the first of hexagonal centre where doing starting regular hexagon center to target
Vector；
D2：Judge whether primary vector is completely in effective coverage, the robot if effective coverage completely includes primary vector
Straight line runs to target, and otherwise primary vector and effective coverage at least have two intersection points, and carry out step D3；
D3：Closer first intersection point in distance starting regular hexagon center, another intersection point are calculated as the second intersection point, robot straight line
The regular hexagon center for running to the first near intersections, the tree path among the first intersection point to the second intersection point run to the second friendship
After point, straight line runs to target.
9. robot path planning method according to claim 8, which is characterized in that along the first intersection point in the step D3
The method that tree path among to the second intersection point runs to the second intersection point is：
The secondary vector to each adjacent regular hexagon center is done at the regular hexagon center of the first near intersections；Judge second
The angle of vector and primary vector selects the lesser vector of angle to run to the second intersection position；
Or, the first intersection point is enumerated to trees all between the second intersection point path in advance in robot, and calculate shortest tree path, machine
People runs to the second intersection point along shortest tree path.
10. a kind of dust catcher, which is characterized in that including a kind of described in any item robot path planning sides claim 1-9
Method.
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| CN109516120A (en) * | 2019-01-14 | 2019-03-26 | 山东省科学院自动化研究所 | A kind of the omnidirectional's conveyer system and working method of three-wheel drive |
| CN109571482A (en) * | 2019-01-02 | 2019-04-05 | 京东方科技集团股份有限公司 | Sweeping robot paths planning method and related system, readable storage medium storing program for executing |
| CN110108292A (en) * | 2019-06-12 | 2019-08-09 | 山东师范大学 | Vehicle navigation path planing method, system, equipment and medium |
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