CN103092207A - Robot maze search method - Google Patents
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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 labyrinth searching method.
Background technology
The research that intelligent robot is applied to explore labyrinth and circumstances not known is 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 be according to the routing algorithm of drafting, select wherein one to continue to explore, until search terminal point.And this type of algorithm has individual drawback, does not take full advantage of information that robot searched the searching route of robot is optimized.When having branch road to select, according to the routing algorithm drafted, select wherein one to continue to explore, and whether this paths can reach terminal point, in advance not according to existing data analysis judgement, can only learn by actual search.And only be confined to the information of having explored is selected, these information effectively not to be expanded, these all will be with serving unnecessary search, and the accuracy that impact judges reduces search efficiency.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of robot labyrinth searching method, from rejecting invalid searching route and increasing effective information two aspects, substitute the robot mechanical movement speed of relative low speed with microcontroller arithmetic speed at a high speed, thereby improve the labyrinth search efficiency.
The technical solution adopted for the present invention to solve the technical problems is: a kind of robot labyrinth searching method is provided, comprises the following steps:
(1) information of known and robot being explored is expanded, and after the metope information of lattice, utilizes this metope information in searching maze lattice, and the part or all of information of the metope of its each lattice of surrounding is upgraded.Namely according to current maze lattice left to whether the road being arranged, whether the maze lattice right that draws its left has the road.In like manner can according under current maze lattice, whether right, upper direction have the road, draws the upper direction of its below maze lattice, whether the left of right-hand maze lattice has the road to the lower direction with the top maze lattice.Like this, although these four lattice were not searched for, even all metope information of part have been obtained, for judgement and the routing in later stage provides more valid data;
(2) when having branch road available, the branch road utilization " flood deduction method " that routing algorithm is selected is deduced in advance, reject infeasible path, after described " flood deduction method " namely chooses optimum branch road according to the 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 be deduced terminal point, this branch road is judged as and can advances; If deduce less than terminal point, be judged as and advance, and all maze lattices of can not advancing that will deduce are labeled as dead end, pick out the hunting zone, then deduce in advance according to next preferential branch road that the routing rule is selected, until till finding out the branch road that can advance.
Described step also comprises in (2): the path that routing algorithm is selected is once filtered, get rid of those unreachable paths, reduce the hunting zone; What get rid of is only those paths that do not have possibility to reach home, and all the other paths that might arrive are all kept.
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 the robot current location is labeled as peak, namely " flood " stream less than the place, prevent its " adverse current "; If can " trickle " to terminal point in this " flowing water " path, this road is judged as and can advances; If " trickling " is less than terminal point, be judged as and advance, and all grid that " flood " institute " is flow through " are labeled as dead end, pick out the hunting zone, then select next preferential branch road according to routing algorithm, and deduce, until till finding out the branch road of to advance.
The implementation method of the deduction described in described step (2) is carried out for the method for seeking optimal path based on the circle of equal altitudes method, according to the circle of equal altitudes of information work from the branch point to the terminal point that records in array, therefrom finds out the path that can reach home; Upgrade if completed the contour value of all coordinates, still could not enough upgrade the contour value of terminal point, judge that branch road is unreachable for this reason; The deduction process must be deduced to " front ", during contour value initialization, the contour value of current robot position is set to minimum value 0, and the contour value of starting point or branch point is set to 1, and the initial contour value of all the other points all is set to 0xff, can guarantee to deduce to " front ".
Beneficial effect
At first the present invention expands the information that known and robot explore, thereby draw more useful informations, can not only provide valid data for " the flood deduction method " that the present invention proposes, also can for robot selecting optimal path etc. that more data is provided, select more accurately or judgement thereby make." the flood deduction method " that propose can identify the dead end in the labyrinth, thereby reduces the hunting zone, with the microcontroller arithmetic speed substitute machine people at a high speed speed of " running " slowly,
Effectively improve search efficiency.
Description of drawings
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 of the present invention path schematic diagram.
Embodiment
Below in conjunction with specific embodiment, further set forth the present invention.Should be understood that these embodiment only to be used for explanation the present invention and be not used in and limit the scope of the invention.Should be understood that in addition those skilled in the art can make various changes or modifications the present invention after the content of having read the present invention's instruction, these equivalent form of values fall within the application's appended claims limited range equally.
Fig. 1 is data of the present invention expansion schematic diagram: MapBlock[x in figure] storage is the metope information that actual search goes out in [y], can expand these palace lattice information partly or completely of four palace lattice on every side according to this information, and the information that expands is stored in array LogBlock, thereby utilize the information of four maze lattices around these information updatings that expand, for subsequent searches or spurt provide more effective informations.
Fig. 2 is routing algorithm process flow diagram of the present invention: the path of selecting rule to select original route, deduced in advance before robot advances according to " flood deduction method " successively according to priority orders, and can reach the terminal point path until find.
Fig. 3 is robot labyrinth searching route schematic diagram: segment of curve is that robot searches the path of terminal point for the first time from starting point, and dash area represents the dead end that the searching period robot marks.Robot is explored to terminal point from starting point, according to the dead end robot of institute's mark in the routing rule figure of routine removal search before meeting all, and the algorithm after improving, can identify these dead ends according to " flood deduction method ", thereby reduce the hunting zone, with the microcontroller arithmetic speed substitute machine people at a high speed speed of " running " slowly, effectively improve search efficiency.
The present invention is divided into and is the two large divisions: expanded search information and the invalid searching route of rejecting, lower mask body narration.
1, expanded search information
The labyrinth environment of supposing the exploration of robot is the square two-dimentional labyrinth of 16*16, in practical application, can carry out different set according to the different application environment.
It was three steps that the specific implementation way is divided into:
The first step, the two-dimensional array MapBlock[x of two 16*16 of structure] [y] and LogBlock[x] [y], what MapBlock stored is the metope information that actual search goes out, and what LogBlock stored is not only the metope information that actual search goes out, and also comprises the metope information of deducing out.Wherein, x: horizontal ordinate, y: ordinate, bit3～bit0 position represents respectively whether the maze lattice left, down, right of current coordinate, upper direction have the road, 0: this direction is without the road, 1: this direction has the road, and whether the bit4 position is used for this maze lattice of mark truly searched for, and the surrounding that is used for the difference supposition has road and true surrounding that road (the metope information that namely obtains by actual search) is arranged entirely entirely;
Second step carries out initialization, MapBlock[x to above-mentioned two arrays] in [y] all elements be initialized as 0x00.LogBlock[x] in [y], the bit2 position of all elements of x=0 (bottom margin in whole labyrinth) all is set to 0; The bit0 position of all elements of x=16 (top margin in whole labyrinth) all is set to 0; Bit3 position (the left border in whole labyrinth) to all elements of y=0 all is set to 0; The bit1 position of all elements of y=16 (the right-hand border in whole labyrinth) all is set to 0, represents that there is wall on surrounding border, labyrinth, namely without the road.All the other bit3～bit0 position all is set to 1, supposes initially that namely the labyrinth is inner without any partition wall, addition portion dividing wall progressively in the exploration in later stage and deduction process; The bit7 of all elements～bit4 position all is set to 0;
The 3rd step, during robot searches, two arrays to be carried out synchronous maintenance and upgrade, the data that MapBlock preserves the robot actual search get final product; LogBlock not only copies the information that MapBlock records, and also comprises the extend information to MapBlock.Concrete extended method is as follows: for example, can be according to MapBlock[x] the bit2 position of [y] is that 0(represents (x, y) the lattice below is without the road), infer LogBlock[x] the bit0 position of [y-1] is that 0(represents (x, y-1) the lattice top is without the road), in like manner can get the spreading result of its excess-three direction, schematic diagram as shown in Figure 2;
After the metope information that searches lattice, can utilize this maze lattice metope information, the metope information of its each lattice of surrounding is upgraded, like this, although these four lattice were not searched for, even all metope information of part have been obtained, for judgement and the routing in later stage provides more valid data.
2, reject invalid searching route
(1) filtered search path
In the robot searches process, the path that routing algorithm is selected is once filtered.When having branch road available, the path to routing algorithm is selected before robot advances, utilizes " flood deduction method " to deduce in advance, and Ruo Keda advances; If unreachable, with this branch road and the path that can deduce out by this branch road, all be labeled as dead end.
The purpose of filtering is to get rid of those unreachable paths, reduces the hunting zone.What get rid of is only those paths that do not have possibility to reach home, and all the other paths that might arrive are all kept.So, reducing also can not omit any active path under the prerequisite of hunting zone.Filter the processor working time exhaust much smaller than the time of robot operation, can ignore.Even (do not get rid of any unreachable path) under the poorest situation, can not increase search time yet.
(2) flood is deduced method
Because whole deduction process is similar to the flood trickling, we are called " flood deduction method " visually at this.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 the robot current location is labeled as peak, namely " flood " stream less than the place, prevent its " adverse current ".If can " trickle " to terminal point in this " flowing water " path, this road is judged as and can advances; If " trickling " is less than terminal point, be judged as and can not advance, and will be just now all grid of " flowing through " of " flood " institute be labeled as dead end, pick out the hunting zone, then select next preferential branch road according to routing algorithm, and deduce, until till finding out the branch road of to advance.Its process flow diagram as shown in Figure 2.
The implementation method of deducing can be modified based on the method for circle of equal altitudes method searching optimal path, because can the result of deducing only need judge and reach home, so, as long as the information that records according to the LogBlock array is done from branch point (the crossing coordinate of the branch road that robot selects by routing algorithm, if this branch road judgement can reach, be the next position coordinate of robot) when arriving the circle of equal altitudes of terminal point, therefrom find out the path that can reach home and get final product, need not to find out optimal path.During program design, (initial contour value is maximal value: 0xff), immediately jump out circulation, carry out the driving function of robot as long as the contour value of terminal point has been updated; Upgrade if processor has been completed the contour value of all coordinates, still could not enough upgrade the contour value of terminal point, judge that branch road is unreachable for this reason.The deduction process should be noted and don't fail to deduce to " front ", the trend of namely deducing can not be passed by the coordinate of current robot, otherwise not only can strengthen the workload of deduction, and be not easy to the mark dead end, during contour value initialization, the contour value of current robot position is set to minimum value 0, the contour value of starting point (branch point) is set to 1, the initial contour value of all the other points all is set to 0xff, can guarantee to deduce to " front ".
Claims (4)
1. a robot labyrinth searching method, is characterized in that, comprises the following steps:
(1) information of known and robot being explored is expanded, in searching maze lattice after the metope information of lattice, utilize this metope information, the part or all of information of the metope of its each lattice of surrounding is upgraded, like this, although these four lattice were not searched for, even all metope information of part have been obtained, for judgement and the routing in later stage provides more valid data;
(2) when having branch road available, the branch road utilization " flood deduction method " that routing algorithm is selected is deduced in advance, reject infeasible path, after described " flood deduction method " namely chooses optimum branch road according to the 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 be deduced terminal point, this branch road is judged as and can advances; If deduce less than terminal point, be judged as and advance, and all maze lattices of can not advancing that will deduce are labeled as dead end, pick out the hunting zone, then deduce in advance according to next preferential branch road that the routing rule is selected, until till finding out the branch road that can advance.
2. a kind of robot according to claim 1 labyrinth searching method, is characterized in that, described step also comprises in (2): the path that routing algorithm is selected is once filtered, get rid of those unreachable paths, reduce the hunting zone; What get rid of is only those paths that do not have possibility to reach home, and all the other paths that might arrive are all kept.
3. a kind of robot according to claim 1 labyrinth searching method, it is characterized in that, in described step (2), " flood deduction method " is after routing algorithm chooses branch road, partition information according to the array record, along this branch road simulation " flowing water ", and the robot current location is labeled as peak, namely " flood " stream less than the place, prevent its " adverse current "; If can " trickle " to terminal point in this " flowing water " path, this road is judged as and can advances; If " trickling " is less than terminal point, be judged as and advance, and all grid that " flood " institute " is flow through " are labeled as dead end, pick out the hunting zone, then select next preferential branch road according to routing algorithm, and deduce, until till finding out the branch road of to advance.
4. a kind of robot according to claim 1 labyrinth searching method, it is characterized in that, the implementation method of the deduction in described step (2) is carried out for the method for seeking optimal path based on the circle of equal altitudes method, according to the circle of equal altitudes of information work from the branch point to the terminal point that records in array, therefrom find out the path that to reach home; Upgrade if completed the contour value of all coordinates, still could not enough upgrade the contour value of terminal point, judge that branch road is unreachable for this reason; The deduction process must be deduced to " front ", during contour value initialization, the contour value of current robot position is set to minimum value 0, and the contour value of starting point or branch point is set to 1, and the initial contour value of all the other points all is set to 0xff, can guarantee to deduce to " front ".
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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 |
| CN104462805A (en) * | 2014-12-02 | 2015-03-25 | 厦门飞游信息科技有限公司 | Map path-searching method and equipment based on A* algorithm and computing terminal |
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| 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 |
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| CN113325856A (en) * | 2021-05-31 | 2021-08-31 | 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 |
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Cited By (9)
| 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 |
| CN104462805A (en) * | 2014-12-02 | 2015-03-25 | 厦门飞游信息科技有限公司 | Map path-searching method and equipment based on A* algorithm and computing terminal |
| CN104462805B (en) * | 2014-12-02 | 2017-05-31 | 厦门飞游信息科技有限公司 | A kind of map road-seeking method based on A* algorithms, equipment and computing terminal |
| CN107423360A (en) * | 2017-06-19 | 2017-12-01 | 广东中冶地理信息股份有限公司 | A kind of labyrinth method for solving based on path center 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 |
| CN113325856A (en) * | 2021-05-31 | 2021-08-31 | 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 |
| 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 |
| CN114129263A (en) * | 2021-11-29 | 2022-03-04 | 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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