CN103092207B - Robot maze search method - Google Patents
Robot maze search method Download PDFInfo
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- CN103092207B CN103092207B CN201310062309.9A CN201310062309A CN103092207B CN 103092207 B CN103092207 B CN 103092207B CN 201310062309 A CN201310062309 A CN 201310062309A CN 103092207 B CN103092207 B CN 103092207B
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Abstract
The invention relates to a robot maze search method. When the robot searches a maze, metope information explored by the robot is expanded, and search path which is selected out through path selection principle is pre-deducted by a flood deduction method. The aim of the pre-deduction is that a plurality of paths which are unreachable to destination are eliminated before the robot walks, and so search time of the robot is reduced from two angels of eliminating invalid search paths and increasing effective information. According to the robot maze search method, mechanical operation speed of a robot with relative low speed is replaced by operation speed of a micro controller with high speed, and maze search efficiency is improved.
Description
Technical field
The invention belongs to field of artificial intelligence, particularly relate to a kind of robot maze search method.
Background technology
Intelligent robot is applied to the research exploring labyrinth and circumstances not known very universal, make a general survey of existing maze-searching algorithm, the way of the overwhelming majority is when robot has branch road to select, can according to the routing algorithm drafted, select wherein one carry out continuations exploration, until search terminal.And this type of algorithm has individual drawback, do not make full use of the searching route of information to robot that robot searched and be optimized.When there being branch road to select, then according to the routing algorithm drafted, select wherein one carry out continuations exploration, and whether this paths can reach terminal, does not judge according to existing data analysis in advance, can only be learnt by actual search.And the information be only confined to having explored is selected, and does not effectively expand these information, these all with serving unnecessary search, will affect the accuracy judged, and reduce search efficiency.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of robot maze search method, start with from the invalid searching route of rejecting and increase effective information two aspect, substitute robotic's travelling speed of relative low speeds with microcontroller arithmetic speed at a high speed, thus improve labyrinth search efficiency.
The technical solution adopted for the present invention to solve the technical problems is: provide a kind of robot maze search method, comprise the following steps:
(1) information that known and robot explore is expanded, when after the metope information searching lattice in maze lattice, utilize this metope information, the part or all of information of metope of each lattice of its surrounding is upgraded.Namely whether there is road according to current maze lattice left direction, show whether the maze lattice right direction of its left has road.In like manner can according under current maze lattice, whether right, upper direction have road, draw the upper direction of maze lattice below it, whether the lower direction of the left direction of right maze lattice and top maze lattice have road.Like this, although these four lattice were not searched for, obtained part even all metope information, for the judgement in later stage and routing provide more valid data;
(2) when there being branch road available, " flood deduction method " is utilized to deduce in advance to the branch road that routing algorithm is selected, reject infeasible path, after described " flood deduction method " namely chooses optimum branch road according to routing rule, before robot advances, deduce in advance along this branch road according to the information that Given information, robot explore and expand, if this branch road can deduce terminal, then this branch road is judged as advancing; If deduce less than terminal, then be judged as advancing, and all maze lattices of can not advancing of deducing are labeled as dead end, pick out hunting zone, then deduce in advance, till finding out the branch road that can advance according to next preferential branch road that routing rule is selected.
Also comprise in described step (2): the path that routing algorithm is selected once is filtered, gets rid of those infeasible paths, reduce hunting zone; What get rid of is only the path that those do not have possibility to reach home, and is all retained the path that all the other likely arrive.
In described step (2), " flood deduction method " is after routing algorithm chooses branch road, according to the partition information of array record, along this branch road simulation " flowing water ", and robot current location is labeled as peak, namely " flood " stream less than place, prevent its " adverse current "; If can " trickle " to terminal in this " flowing water " path, Ze Zhetiao road is judged as advancing; If " trickling " is less than terminal, then be judged as advancing, and all grid that " flood " institute " is flow through " are labeled as dead end, pick out hunting zone, then select next preferential branch road according to routing algorithm, and deduce, till finding out branch road of can advancing.
The implementation method of the described deduction described in step (2) is carry out based on the method for circle of equal altitudes method searching optimal path, makes the circle of equal altitudes from branch point to terminal, therefrom find out a path that can reach home according to the information recorded in array; If completed all coordinates etc. high level upgrade, still could not enough upgrade terminal etc. high level, then judge that branch road is unreachable for this reason; Deduction process must be deduced to " front ", etc. high level initialization time, by current robot position etc. high level be set to minimum value 0, starting point or branch point etc. high level be set to 1, the high level such as initial of all the other points is all set to 0xff, can ensure to deduce to " front ".
Beneficial effect
First the present invention expands the information that known and robot explore, thus draw more useful informations, " the flood deduction method " that can not only propose for the present invention provides valid data, also can provide more data for robot at selection optimal path etc., thus make selection more accurately or judge." the flood deduction method " that proposed can identify the dead end in labyrinth, thus reduces hunting zone, " to run " slowly speed with microcontroller arithmetic speed substitute machine people at a high speed,
Effective raising search efficiency.
Accompanying drawing explanation
Fig. 1 is Data expansion schematic diagram of the present invention.
Fig. 2 is routing algorithm process flow diagram of the present invention.
Fig. 3 is robot searches path schematic diagram of the present invention.
Embodiment
Below in conjunction with specific embodiment, set forth the present invention further.Should be understood that these embodiments are only not used in for illustration of the present invention to limit the scope of the invention.In addition should be understood that those skilled in the art can make various changes or modifications the present invention, and these equivalent form of values fall within the application's appended claims limited range equally after the content of having read the present invention's instruction.
Fig. 1 is Data expansion schematic diagram of the present invention: what store in MapBlock [x] [y] in figure is the metope information that actual search goes out, the information partly or completely of four palace lattice around these palace lattice is gone out according to this information easily extensible, and the information expanded is stored in array LogBlock, thus the information of four maze lattices around the information updating utilizing these to expand, for subsequent searches or spurt provide more effective informations.
Fig. 2 is routing algorithm process flow diagram of the present invention: the path selecting rule to select original route, deduces in advance successively, can reach terminal path until find according to priority orders according to " flood deduction method " before robot advances.
Fig. 3 is robot maze searching route schematic diagram: segment of curve is that robot searches the path of terminal from starting point first time, and dash area represents the dead end that searching period robot marks.Robot is explored from starting point to terminal, the dead end robot marked in routing rule figure is conveniently the front removal search of meeting all, and the algorithm after improving, then can identify these dead ends according to " flood deduction method ", thus reduction hunting zone, " to run " slowly speed with microcontroller arithmetic speed substitute machine people at a high speed, effectively improve search efficiency.
The present invention is divided into two large divisions: expanded search information and the invalid searching route of rejecting, lower mask body describes.
1, expanded search information
Assuming that the labyrinth environment of the exploration of robot is the square two dimension labyrinth of 16*16, in practical application, different set can be carried out according to different application environment.
Specific implementation way is divided into three steps:
The first step, two-dimensional array MapBlock [x] [y] and LogBlock [x] [y] of structure two 16*16, what MapBlock stored is the metope information that actual search goes out, what LogBlock stored is not only the metope information that actual search goes out, and also comprises the metope information deduced out.Wherein, x: horizontal ordinate, y: ordinate, bit3 ~ bit0 position represents the maze lattice left, down, right of changing coordinates respectively, whether upper direction has road, 0: this direction Wu Lu, 1: there is road in this direction, bit4 position is for marking this maze lattice whether actual search mistake, and for distinguishing supposition four thoroughly have road and true four thoroughly to have road (namely by metope information that actual search obtains);
Second step, carries out initialization to above-mentioned two arrays, and in MapBlock [x] [y], whole element is initialized as 0x00.In LogBlock [x] [y], the bit2 position (bottom margin in whole labyrinth) of all elements of x=0 is all set to 0; The bit0 position (top margin in whole labyrinth) of all elements of x=16 is all set to 0; All 0 is set to the bit3 position (border, left in whole labyrinth) of all elements of y=0; The bit1 position (border, right in whole labyrinth) of all elements of y=16 is all set to 0, represents that there is wall on surrounding border, labyrinth, Ji Wu road.All the other bit3 ~ bit0 positions are all set to 1, namely initially suppose that labyrinth is inner without any partition wall, progressively adding portion partition wall in the exploration and deduction process in later stage; Bit7 ~ bit4 position of all elements is all set to 0;
3rd step, carries out synchronous maintenance renewal to two arrays during robot searches, and MapBlock preserves the data of robot actual search; LogBlock not only copies the information that MapBlock records, and also comprises the extend information to MapBlock.Concrete extended method is as follows: such as, can be that 0(represents (x according to the bit2 position of MapBlock [x] [y], y) below lattice without road), infer that the bit0 position of LogBlock [x] [y-1] is that 0(represents (x, y-1) above lattice without road), in like manner can obtain the spreading result in its excess-three direction, schematic diagram as shown in Figure 2;
When after the metope information searching lattice, this maze lattice metope information can be utilized, the metope information of each lattice of its surrounding is upgraded, like this, although these four lattice were not searched for, obtained part even all metope information, for the judgement in later stage and routing provide more valid data.
2, invalid searching route is rejected
(1) filtered search path
In robot searches process, the path that routing algorithm is selected once is filtered.Whenever having branch road available, to the path that routing algorithm is selected, before robot advances, utilize " flood deduction method " to deduce in advance, Ruo Keda then advances; If unreachable, then by this branch road and the path that can be deduced out by this branch road, be all labeled as dead end.
The object of filtering gets rid of those infeasible paths, reduces hunting zone.What get rid of is only the path that those do not have possibility to reach home, and is all retained the path that all the other likely arrive.So, under the prerequisite reducing hunting zone, also can not omit any active path.Filter the time that the processor that exhausts runs much smaller than robot working time, negligible.Even if (do not get rid of any infeasible paths) the poorest when, also search time can not be increased.
(2) flood deduces method
Because whole deduction process is similar to flood trickling, at this, we are called " flood deduction method " visually.Its schematic diagram as shown in Figure 3, after routing algorithm chooses branch road, according to the partition information of LogBlock array record, along this branch road " trickling ", and note robot current location is labeled as peak, namely " flood " stream less than place, prevent its " adverse current ".If can " trickle " to terminal in this " flowing water " path, Ze Zhetiao road is judged as advancing; If " trickling " is less than terminal, then be judged as advancing, and all grid that " flood " institute " is flow through " by are just now labeled as dead end, pick out hunting zone, then select next preferential branch road according to routing algorithm, and deduce, till finding out branch road of can advancing.Its process flow diagram as shown in Figure 2.
The implementation method deduced can be modified based on the method for circle of equal altitudes method searching optimal path, because can the result deduced only need judgement reach home, so, as long as doing from branch point (the crossing coordinate of the branch road that robot is selected by routing algorithm according to the information recorded in LogBlock array, if this branch road judges to reach, be the next position coordinate of robot) to the circle of equal altitudes of terminal time, therefrom find out a path that can reach home, without the need to finding out optimal path.During program design, if terminal etc. high level be updated (initial etc. high level be maximal value: 0xff), immediately jump out circulation, perform the driving function of robot; If processor completed all coordinates etc. high level upgrade, still could not enough upgrade terminal etc. high level, then judge that branch road is unreachable for this reason.Deduction process should be noted don't fail to be deduced to " front ", namely the trend deduced can not pass by the coordinate of current robot, otherwise not only can strengthen the workload of deduction, and be not easy to mark dead end, during etc. high level initialization, by current robot position etc. high level be set to minimum value 0, starting point (branch point) etc. high level be set to 1, the high level such as initial of all the other points is all set to 0xff, can ensure to deduce to " front ".
Claims (3)
1. a robot maze search method, is characterized in that, comprises the following steps:
(1) information that known and robot explore is expanded, when after the metope information searching lattice in maze lattice, utilize this metope information, the part or all of information of metope of each lattice of its surrounding is upgraded, like this, although these four lattice were not searched for, obtained part even all metope information, for the judgement in later stage and routing provide more valid data;
(2) when there being branch road available, " flood deduction method " is utilized to deduce in advance to the branch road that routing algorithm is selected, reject infeasible path, after described " flood deduction method " namely chooses optimum branch road according to routing rule, before robot advances, deduce in advance along this branch road according to the information that Given information, robot explore and expand, if this branch road can deduce terminal, then this branch road is judged as advancing; If deduce less than terminal, then be judged as advancing, and all maze lattices of can not advancing of deducing are labeled as dead end, pick out hunting zone, then deduce in advance, till finding out the branch road that can advance according to next preferential branch road that routing rule is selected; In this step, " flood deduction method " is after routing algorithm chooses branch road, according to each lattice metope information of array record on this branch road, along this branch road simulation " flowing water ", and robot current location is labeled as peak, namely " flood " stream less than place, prevent its " adverse current "; If can " trickle " to terminal in this " flowing water " path, Ze Zhetiao road is judged as advancing; If " trickling " is less than terminal, then be judged as advancing, and all grid that " flood " institute " is flow through " are labeled as dead end, pick out hunting zone, then select next preferential branch road according to routing algorithm, and deduce, till finding out branch road of can advancing.
2. a kind of robot maze search method according to claim 1, is characterized in that, also comprises: once filter the path that routing algorithm is selected, get rid of those infeasible paths in described step (2), reduces hunting zone; What get rid of is only the path that those do not have possibility to reach home, and is all retained the path that all the other likely arrive.
3. a kind of robot maze search method according to claim 1, it is characterized in that, the implementation method of the deduction in described step (2) is carry out based on the method for circle of equal altitudes method searching optimal path, make the circle of equal altitudes from branch point to terminal according to the information recorded in array, therefrom find out a path that can reach home; If completed all coordinates etc. high level upgrade, still could not enough upgrade terminal etc. high level, then judge that branch road is unreachable for this reason; Deduction process must be deduced to " front ", etc. high level initialization time, by current robot position etc. high level be set to minimum value 0, starting point or branch point etc. high level be set to 1, the high level such as initial of all the other points is all set to 0xff, can ensure to deduce to " front ".
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104142684A (en) * | 2014-07-31 | 2014-11-12 | 哈尔滨工程大学 | Maze searching method for miniature micromouse robot |
| CN107292107A (en) * | 2014-12-02 | 2017-10-24 | 厦门飞游信息科技有限公司 | A kind of map road-seeking method, equipment and computing terminal |
| CN107423360B (en) * | 2017-06-19 | 2020-01-24 | 广东中冶地理信息股份有限公司 | Maze solving method based on path central line |
| CN108460500A (en) * | 2018-05-04 | 2018-08-28 | 成都信息工程大学 | Based on the optimum path planning method for improving Flood-Fill algorithms |
| CN110320920A (en) * | 2019-08-06 | 2019-10-11 | 北京中海远景科技有限公司 | A kind of double-movement robot maze paths planning method based on reduction algorithm |
| CN113325856B (en) * | 2021-05-31 | 2022-07-08 | 中国船舶工业集团公司第七0八研究所 | UUV optimal operation path planning method based on countercurrent approximation strategy |
| CN114129263B (en) * | 2021-11-29 | 2023-07-25 | 武汉联影智融医疗科技有限公司 | Surgical robot path planning method, system, equipment and storage medium |
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