CN108592912A - A kind of autonomous heuristic approach of indoor mobile robot based on laser radar - Google Patents
A kind of autonomous heuristic approach of indoor mobile robot based on laser radar Download PDFInfo
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- CN108592912A CN108592912A CN201810248228.0A CN201810248228A CN108592912A CN 108592912 A CN108592912 A CN 108592912A CN 201810248228 A CN201810248228 A CN 201810248228A CN 108592912 A CN108592912 A CN 108592912A
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- 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
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
Abstract
The invention discloses a kind of autonomous heuristic approach of the indoor mobile robot based on laser radar, establish topological node.It is extracted according to goal seeking point as a result, generating a topological map node and the node being added in topological map.Redundant topology node processing.Detection has all topological nodes under topological map, rejects the topological node of redundancy.Topological map closed-loop process.It detects present topology node and whether there is closed loop with remaining all topological node.If it is present adding corresponding side on topological map completes closed loop.When the node that do not explore is not present in environment, then terminate independently to explore.The method needs not rely on grating map extraction forward position target point, but extracts goal seeking point by laser data, and the Stability and veracity of extraction result is ensure that while substantially reducing extraction algorithm complexity；Redundant node rejecting and closed loop detection are carried out for topological map, substantially increase the efficiency that indoor mobile robot is independently explored.
Description
Technical field
The invention belongs to robot navigation and motion control field more particularly to a kind of indoor movings based on laser radar
The control method of robot autonomous exploration.
Background technology
Along with the development of science and technology, the research of autonomous mobile robot is increasingly by the concern and approval of society.
Autonomous mobile robot has been widely applied among agricultural, industry, military, medical treatment and daily life.It is indoor unknown
Autonomous exploration under environment is one of key function of Indoor Robot, and during autonomous explore, robot need to perceive ring
Border obtains a series of localized target point, and then guidance machine people traverses environment.Strategy is explored by almost all of robot
One can be reduced to generate best goal seeking point and move to the process of the target point.
Topological approach is a kind of effective ways for solving the autonomous search problem of indoor mobile robot, and this method mainly faces two
A problem：The extraction of goal seeking point and the foundation and maintenance of topological map.Extraction for goal seeking point, existing research
In, it usually borrows digital image processing techniques and identifies front porch area on grating map.However with the increase of environment scale,
The calculation amount of leading edge detection is carried out on grating map to increase severely, and then causing robot to explore efficiency significantly reduces, while by
It cannot be effectively ensured in the accuracy that the resolution problem forward position of grid is extracted；Foundation and maintenance for topological map,
The topological map of the structure storage heuristic process of generally use " tree ".The mode of " tree " describes topological map, from data structure
Level results in the closed loop characteristic that environment cannot be effectively described for annular scene, especially larger, with cyclic structure
It can greatly influence to explore efficiency under environment.Meanwhile the redundant topology node on topological map is imitated in the presence of that can substantially reduce exploration
Rate.The present invention is made that corresponding improvement for disadvantages described above.
Invention content
For the current autonomous search problem of indoor mobile robot, the present invention proposes a kind of interior based on laser radar
The autonomous heuristic approach of mobile robot, it is proposed that the goal seeking point extraction based on laser radar is tactful and based on " weighting is undirected
The topological map of figure " is established and maintenance strategy.The method needs not rely on grating map extraction forward position target point, but by swashing
Light data extracts goal seeking point, and the accuracy of extraction result and steady is ensure that while substantially reducing extraction algorithm complexity
It is qualitative；On the other hand, redundant node rejecting is carried out for topological map and closed loop detects, substantially increase indoor mobile robot
The efficiency independently explored.
It is using the applicable robot system of this method：It is equipped with the indoor mobile robot of laser radar.One kind is based on sharp
The autonomous heuristic approach of indoor mobile robot of optical radar, includes the following steps：
Step 1：Goal seeking point is extracted by laser radar data.Extracting method is by forward position breakpoint method and can traffic areas
Method is constituted.
Step 2：Establish topological node.According to the goal seeking point extraction in step 1 as a result, generating a topological map section
Simultaneously the node is added in topological map for point.
Step 3：Redundant topology node processing.Detection has all topological nodes under topological map, rejects opening up for redundancy
Flutter node.
Step 4:Topological map closed-loop process.Detection present topology node whether there is with remaining all topological node to be closed
Ring.If it is present adding corresponding side on topological map completes closed loop.
Step 5：When the node that do not explore is not present in environment, then terminate independently to explore.
Compared with the autonomous heuristic approach of indoor mobile robot compare, advantage of the invention is as follows：
1, present invention uses the goal seeking point extracting method based on laser radar data, calculation amount is low, and accuracy rate is high,
Strong robustness.
2, the topological map redundant node that the present invention uses rejects algorithm and topological map closed loop detection algorithm, improves machine
The autonomous exploration efficiency of device people.
3, requirement of the present invention for robot operation platform reduces.
Description of the drawings
Fig. 1 is that forward position breakpoint method extracts goal seeking point schematic diagram；
Fig. 2 is can FOH domain method extraction goal seeking point schematic diagram；
Fig. 3 is that goal seeking point extracts overall flow figure；
Fig. 4 is closed loop detects schematic diagram；
Fig. 5 is that indoor mobile robot independently explores global procedures flow chart；
Specific implementation mode
It elaborates with reference to the accompanying drawings and detailed description to the present invention.
1) forward position breakpoint method；
Laser forward position is divided into two class of A, B using forward position breakpoint method：A classes forward position is at sensor maximum range, and arc length
More than the width of mobile robot；B classes forward position adjacent two laser number at the breakpoint for being blocked by barrier and being generated, the breakpoint
According to range information difference absolute value be more than a secure threshold.Forward position breakpoint method generates candidate at the two class forward position A, B
Goal seeking point.Fig. 1 simply illustrates the principle that forward position breakpoint method extracts 2 class goal seeking points.
The geometrical rule for generating A class candidate goal seeking points is as follows：
A, the midpoint of forward position arc is connected with the center of laser radar；
B, take the point on line less than sensor maximum range as initial candidate goal seeking point, such as Fig. 1 (a) institutes
Show.
The geometrical rule for generating B class initial candidate target points is as follows：
A, the both ends in B classes forward position are respectively labeled as N, L；
B, a point M is taken on NL line segments, makes MN=Bd, BdFor the length of MN；
C, the circular arc arc of one section of passing point M is drawn using the center of laser range finder as the center of circle；
D, N points are crossed and make a straight line perpendicular to NL, and take a point Q on vertical line, make line segment NQ=safe_dis, and point
Q is in free space；
E, make the ray that point Q is directed toward at a center by laser radar, the intersection point as candidate of ray and circular arc arc explores
Target point, as shown in Fig. 1 (b).
It 2) can FOH domain method
Can FOH domain method extraction goal seeking point method it is as follows：
It a, can traffic areas according to current laser data extraction (see corresponding region in Fig. 2)；
B, with this can traffic areas centerline direction distalmost end be first candidate target point position, along first wait
The line of target point and vehicle body is selected, spacing distance d generates another candidate target point until robot current location.
C, calculating can on the center line of traffic areas all candidate goal seeking points information gain.
3) whole goal seeking point extraction strategy；
Goal seeking point is extracted using forward position breakpoint method first, if extraction failure, using can the continuation of FOH domain method
Extraction, detailed process are as shown in Figure 3.
4) definition of topological node；
If robot has successfully extracted goal seeking point in some position, current robot location will be confirmed as one
A topological node.Need to include robot pose pose, node ID index, the candidate of present node in a topological node
Sets of target points T.
5) topological map redundant node rejects strategy；
The topological node of topological map contains environmental information of the robot in heuristic process, a valuable topology
Node should effectively guidance machine people navigate, and height refines cartographic information.This method is main for the rejecting strategy of redundant node
It is divided into two rules：
Rule one：Topological map origin is set as start node a, all sections that detection is connected directly with start node a
Point B, B={ b1,b2,b3..., for each element { b in Bi, it calculates and each element { biRemoving of being connected directly
All nodes outside start node a are denoted as Cbi={ c1,c2,c3……}.On grating map, C is detectedbiIn each element
{ciWith the connectivity of start node a, detection method ray-traversal.If { ciWith start node a can not straight line be connected to,
Then { biNode will be saved.After all elements detection finishes in B, it sets start node to next node, continues
Iteration；
Rule two：If there is the goal seeking point not reached under certain node, the node is preserved.
For the ungratified node of above two rule, it is defined as redundant node, which is deleted from topological map
It removes.
6) topological map closed loop inspection policies；
For there are the scene of closed loop, needing to carry out closed loop detection for topological map, more reasonably opened up to establish
Fall to the ground figure, and best guidance path is obtained for subsequent navigation work.The closed loop detection of topological map is determined according to following three rule：
Rule one：The difference of the id serial numbers of node A and node B is more than a secure threshold.
Rule two：Node A and node B can straight line reach, distance is denoted as D (A, B), shown in the dotted line in Fig. 4.
Rule three：Node A and node B is according to calculated one reachable and shortest topological road of existing topological map
Diameter, length is T (A, B) (shown in the black color dots horizontal line in Fig. 4), and meets D (A, B)<K*T (A, B), k are proportionality coefficient.
After above three rule meets, you can add a line between node A and node B, topological map completes one
Secondary closed loop.
7) overall flow；
This method introduces two kinds and explores strategy, respectively explores pattern (exploration mode) and trace back mode
(backtrack mode), both patterns automatically switch during mobile robot is independently explored.Autonomous heuristic algorithm
Flow is as shown in Figure 5.
For present node there are when goal seeking point, robot is operated in exploration pattern to explore circumstances not known.Selection evaluation
Optimal goal seeking point is as current target point, heuristic algorithm flow left side frame part as shown in Figure 5.In the process of exploration
In, it often advances at a fixed step size or arrival target point, acquires new laser data, then start to explore next time.
If present node does not have goal seeking point and arrived the target point that last moment selects, then system will be switched to
Trace back mode is to traverse circumstances not known, and detailed process is as shown in Fig. 5 right side frames.It is not explored if existing in Global Topological map
The node nearest and containing non-goal seeking point apart from robot is then set as destination node, otherwise by start node by target point
It is set as destination node.Backtracking path is obtained using Dijkstra's algorithms on current existing topological map, is being worked as one
The shortest path of arrival destination node on preceding existing topological map.
Claims (2)
1. a kind of autonomous heuristic approach of indoor mobile robot based on laser radar, it is characterised in that：Include the following steps：
Step 1：Goal seeking point is extracted by laser radar data；Extracting method is by forward position breakpoint method and can FOH domain method structure
At；
Step 2：Establish topological node；According to the goal seeking point extraction in step 1 as a result, generating a topological map node simultaneously
The node is added in topological map；
Step 3：Redundant topology node processing；Detection has all topological nodes under topological map, rejects the topology section of redundancy
Point；
Step 4:Topological map closed-loop process；It detects present topology node and whether there is closed loop with remaining all topological node；Such as
Fruit exists, then adds corresponding side on topological map and complete closed loop；
Step 5：When the node that do not explore is not present in environment, then terminate independently to explore.
2. the autonomous heuristic approach of a kind of indoor mobile robot based on laser radar according to claim 1, feature
It is：
1) forward position breakpoint method；
Laser forward position is divided into two class of A, B using forward position breakpoint method：A classes forward position is at sensor maximum range, and arc length is more than
The width of mobile robot；B classes forward position adjacent two laser data at the breakpoint for being blocked by barrier and being generated, the breakpoint
The absolute value of range information difference is more than a secure threshold；Forward position breakpoint method generates candidate explore at the two class forward position A, B
Target point；
The geometrical rule for generating A class candidate goal seeking points is as follows：
A, the midpoint of forward position arc is connected with the center of laser radar；
B, take the point on line less than sensor maximum range as initial candidate goal seeking point；
The geometrical rule for generating B class initial candidate target points is as follows：
A, the both ends in B classes forward position are respectively labeled as N, L；
B, a point M is taken on NL line segments, makes MN=Bd, BdFor the length of MN；
C, the circular arc arc of one section of passing point M is drawn using the center of laser range finder as the center of circle；
D, N points are crossed and make a straight line perpendicular to NL, and take a point Q on vertical line, make line segment NQ=safe_dis, and point Q exists
In free space；
E, make the ray that point Q is directed toward at a center by laser radar, the as candidate goal seeking of intersection point of ray and circular arc arc
Point；
It 2) can FOH domain method
Can FOH domain method extraction goal seeking point method it is as follows：
It a, can traffic areas according to current laser data extraction；
B, with this can traffic areas centerline direction distalmost end for first candidate target point position, along first candidate mesh
The line of punctuate and vehicle body, spacing distance d generates another candidate target point until robot current location；
C, calculating can on the center line of traffic areas all candidate goal seeking points information gain；
3) whole goal seeking point extraction strategy；
First use forward position breakpoint method extract goal seeking point, if extraction failure, using can FOH domain method continue to extract；
4) definition of topological node；
If robot has successfully extracted goal seeking point in some position, current robot location will be confirmed as one and open up
Flutter node；Need to include robot pose pose, node ID index, the candidate target of present node in a topological node
Point set T；
5) topological map redundant node rejects strategy；
The topological node of topological map contains environmental information of the robot in heuristic process, a valuable topological node
It should effectively guidance machine people navigate, height refines cartographic information；This method is broadly divided into the rejecting strategy of redundant node
Two rules：
Rule one：Topological map origin is set as start node a, all the node B, B that detection is connected directly with start node a
={ b1,b2,b3..., for each element { b in Bi, it calculates and each element { biBe connected directly except starting section
All nodes outside point a are denoted as Cbi={ c1,c2,c3……}；On grating map, C is detectedbiIn each element { ciAnd rise
The connectivity of beginning node a, detection method ray-traversal；If { ciWith start node a can not straight line be connected to, then { biSection
Point will be saved；After all elements detection finishes in B, sets start node to next node, continue iteration；
Rule two：If there is the goal seeking point not reached under certain node, the node is preserved；
For the ungratified node of above two rule, it is defined as redundant node, which is deleted from topological map；
6) topological map closed loop inspection policies；
For there are the scene of closed loop, needing to carry out closed loop detection for topological map, to establish more rational topology ground
Figure obtains best guidance path for subsequent navigation work；The closed loop detection of topological map is determined according to following three rule：
Rule one：The difference of the id serial numbers of node A and node B is more than a secure threshold；
Rule two：Node A and node B can straight line reach, distance is denoted as D (A, B)；
Rule three：Node A and node B is long according to calculated one reachable and shortest topological path of existing topological map
Degree is T (A, B), and meets D (A, B)<K*T (A, B), k are proportionality coefficient；
After above three rule meets, you can add a line between node A and node B, topological map completion is once closed
Ring；
7) overall flow；
This method introduces two kinds and explores strategy, respectively explores pattern and trace back mode, both patterns mobile robot from
Automatically switch during main exploration；For present node there are when goal seeking point, robot is operated in exploration pattern to explore not
Know environment；Select to evaluate optimal goal seeking point as current target point；During exploration, often advance a fixed step size or
Person reaches at target point, acquires new laser data, then starts to explore next time；
If present node does not have goal seeking point and arrived the target point that last moment selects, then system will be switched to backtracking
Pattern is to traverse circumstances not known；If there is the target point that do not explore in Global Topological map, recently and will contain apart from robot
There is the node of non-goal seeking point to be set as destination node, otherwise sets start node to destination node；Recall path to utilize
Dijkstra's algorithms obtain on current existing topological map, are an arrival target section on current existing topological map
The shortest path of point.
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| CN111291140A (en) * | 2018-12-06 | 2020-06-16 | 北京欣奕华科技有限公司 | Method, device, equipment and medium for identifying topological nodes |
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| CN111035930B (en) * | 2019-12-06 | 2024-04-19 | 珠海海鸟科技有限公司 | Map data processing method and device |
| CN111368760B (en) * | 2020-03-09 | 2023-09-01 | 阿波罗智能技术(北京)有限公司 | Obstacle detection method and device, electronic equipment and storage medium |
| CN111368760A (en) * | 2020-03-09 | 2020-07-03 | 北京百度网讯科技有限公司 | Obstacle detection method and device, electronic equipment and storage medium |
| CN111158384A (en) * | 2020-04-08 | 2020-05-15 | 炬星科技（深圳）有限公司 | Robot mapping method, device and storage medium |
| CN112828883A (en) * | 2020-12-25 | 2021-05-25 | 香港中文大学深圳研究院 | Robot environment exploration method and system in unknown environment |
| CN113342002B (en) * | 2021-07-05 | 2022-05-20 | 湖南大学 | Multi-mobile-robot scheduling method and system based on topological map |
| CN113342002A (en) * | 2021-07-05 | 2021-09-03 | 湖南大学 | Multi-mobile-robot scheduling method and system based on topological map |
| CN113670293A (en) * | 2021-08-11 | 2021-11-19 | 追觅创新科技(苏州)有限公司 | Map construction method and device |
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