CN104268420A - A star path finding method and system based on binary heap node sorting - Google Patents
A star path finding method and system based on binary heap node sorting Download PDFInfo
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Abstract
The invention discloses an A star path finding method and system based on binary heap node sorting. The A star path finding method includes: conducting initialization; judging whether a node n in an OPEN graph is a target solution A, if not, unfolding all follow-up nodes of the node n to form directly correlated sub nodes, putting the judged node n in a CLOSE graph, calculating the appraisal value of each follow-up node of the node n, conducting heat sorting on the OPEN graph according to the appraisal value, putting the node with the smallest appraisal value at the graph head of the OPEN graph, and repeating the steps until all the nodes are sorted. The A star path finding method introduces heat sorting in the normal A star algorithm so that the execution efficiency of the A star algorithm is greatly improved. The A star path finding method overcomes the defects of the traditional A star algorithm of frequently maintaining the OPEN graph and the CLOSE graph, causing long calculating time as the nodes in the OPEN graph have to be sorted each time, and being incapable of meeting high game timeliness requirements.
Description
Technical field
The present invention relates to a kind of game technical field, particularly a kind of A star method for searching based on Binary Heap node sequencing and system.
Background technology
Game is in the industry cycle called as the 9th art, and successful game more can be subject to global player and praise highly.Along with development of Mobile Internet technology application and and the business such as China Mobile network 3G, 4G increment develop rapidly, mobile phone games demonstrate cutting edge.In Games Software, artificial intelligence is an important and complicated module, and pathfinding algorithm is artificial intelligence applies to one of most basic problem in electronic game.Object moves it according to the mode of certain named place of destination and just requires that program must can find an optimal path from starting point to impact point, this paths should be to bypass barrier and arrive the shortest path of destination, and completing the most frequently used algorithm of this task is exactly A star algorithm.A star as a kind of high performance-price ratio pathfinding algorithm always widely use by game industry, the pathfinding algorithm in the game of a lot of client and large-scale web game all based on A star algorithm as: heroic alliance, World of Warcraft, illusion flies celestial being etc.But due to reasons such as mobile phone games operating software condition and hardware are not good, traditional A star algorithm is also badly in need of improving, and improves pathfinding efficiency with this.Tradition A star algorithm needs frequent maintenance OPEN and CLOSE table, and all need to sort to the node in OPEN table at every turn, and complexity averaging time adopting the A star algorithm of bubble sort is O (n^2), suitable slow of efficiency performed, particularly when map is larger, repeatedly search for so large list and seriously can drag slow whole process.This obviously cannot meet the higher feature of game requirement of real-time.
Summary of the invention
In view of this, technical matters to be solved by this invention is to provide a kind of A star method for searching based on Binary Heap node sequencing and system.
An object of the present invention proposes a kind of A star method for searching based on Binary Heap node sequencing; Two of object of the present invention proposes a kind of A star Pathfinding system based on Binary Heap node sequencing.
An object of the present invention is achieved through the following technical solutions:
A star method for searching based on Binary Heap node sequencing provided by the invention, comprises the following steps:
S1: initialization OPEN table, CLOSE table and impact point A, put into OPEN table by start node S, sky put by CLOSE table;
S2: judge whether OPEN table is empty, if not, then get a node n from the gauge outfit of OPEN table; If so, then algorithmic procedure is terminated;
S3: judge whether node n is target solution A, if so, then output node n; If not, then step S4 is proceeded to; Described target solution is the impact point A that finally will find;
S4: launched to form direct correlation child nodes by all successor nodes of node n, judges child node whether in CLOSE table, if not, then child node is put into OPEN and show;
S5: the node n judged is put into CLOSE table, adopts the assessment values f ' (n) of each successor node of following formulae discovery node n simultaneously;
f′(n)＝g′(n)+h′(n)；
Wherein, f ' (n) is evaluation function, and g ' (n) is the shortest path value that start node arrives node n, and h ' (n) is the inspiration value of node n to the shortest path warp of target;
S6: OPEN table is carried out heapsort by assessment values f ' (x), node minimum for assessment values f ' (x) is placed on the gauge outfit of OPEN table, returns step S2 repetitive cycling.
Further, described OPEN table, for storing the next node for traversal;
Described CLOSE table, for storing the path found.
Further, described heapsort adopts Binary Heap to sort;
Described Binary Heap carries out in the following manner:
First the assessment values f ' (x) that OPEN shows interior joint is obtained, by node placement minimum for assessment values f ' (x) on heap top;
Then from remaining node, select two child nodes of the minimum and secondary little node of assessment values as a upper node;
Finally repeat respectively to be that two sub-sensor selection problem go out two child nodes of the minimum and secondary little node of assessment values as a upper node; Arrange until all OPEN are shown interior joint.
Further, described heapsort adopts Binary Heap to sort; Described Binary Heap carries out in the following manner:
First obtain the assessment values f ' (x) that OPEN shows interior joint, node minimum for assessment values f ' (x) is stored in first element memory address of one-dimension array; Then node minimum for the assessment values f ' (x) in remaining node is stored in second element memory address of one-dimension array, last until complete the sequence of all nodes in OPEN table.
Two of object of the present invention is achieved through the following technical solutions:
A star Pathfinding system based on Binary Heap node sequencing provided by the invention, comprises initialization module, OPEN table judge module, node judge module, association child node module, node assessment values computing module, heapsort module;
Described initialization module, for initialization OPEN table, CLOSE table and impact point A, start node S is put into OPEN table, sky put by CLOSE table;
Described OPEN shows judge module, for judging whether OPEN table is empty, if not, then gets a node n from the gauge outfit of OPEN table; If so, then algorithmic procedure is terminated;
Described node judge module, for judging whether node n is target solution A, if so, then output node n; If not, then step S4 is proceeded to; Described target solution is the impact point A that finally will find, and namely finds a paths to arrive impact point from starting point;
Described association child node module, for being launched to form direct correlation child nodes by all successor nodes of node n, judging child node whether in CLOSE table, if not, then child node being put into OPEN and show;
Described node assessment values computing module, for the node n judged being put into CLOSE table, adopts the assessment values f ' (n) of each successor node of following formulae discovery node n simultaneously;
f′(n)＝g′(n)+h′(n)；
Wherein, f ' (n) is evaluation function, and g ' (n) is the shortest path value that start node arrives node n, and h ' (n) is the inspiration value of node n to the shortest path warp of target;
Described heapsort module, for OPEN table is carried out heapsort by assessment values f ' (x), is placed on the gauge outfit of OPEN table by node minimum for assessment values f ' (x).
Further, described OPEN table, for storing the next node for traversal;
Described CLOSE table, for storing the path found.
Further, the heapsort in described heapsort module adopts Binary Heap to sort;
Described Binary Heap carries out in the following manner:
First the assessment values f ' (x) that OPEN shows interior joint is obtained, by node placement minimum for assessment values f ' (x) on heap top;
Then from remaining node, select two child nodes of the minimum and secondary little node of assessment values as a upper node;
Finally repeat respectively to be that two sub-sensor selection problem go out two child nodes of the minimum and secondary little node of assessment values as a upper node; Arrange until all OPEN are shown interior joint.
Further, the heapsort in described heapsort module adopts Binary Heap to sort; Described Binary Heap carries out in the following manner:
First obtain the assessment values f ' (x) that OPEN shows interior joint, node minimum for assessment values f ' (x) is stored in first element memory address of one-dimension array; Then node minimum for the assessment values f ' (x) in remaining node is stored in second element memory address of one-dimension array, last until complete the sequence of all nodes in OPEN table
Beneficial effect of the present invention is: the present invention introduces heapsort in common A star algorithm, significantly improves A star algorithm execution efficiency with this.Overcome traditional A star algorithm and need frequent maintenance OPEN and CLOSE table, and all need the shortcoming that to sort computing time caused long of the node in OPEN table at every turn, and the higher feature of game requirement of real-time cannot be met.
Accompanying drawing explanation
In order to make the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail, wherein:
The A star method for searching process flow diagram based on Binary Heap node sequencing that Fig. 1 provides for the embodiment of the present invention;
The A star Pathfinding system figure based on Binary Heap node sequencing that Fig. 2 provides for the embodiment of the present invention.
Embodiment
Hereinafter with reference to accompanying drawing, the preferred embodiments of the present invention are described in detail.Should be appreciated that preferred embodiment only in order to the present invention is described, instead of in order to limit the scope of the invention.
Embodiment 1
The A star method for searching process flow diagram based on Binary Heap node sequencing that Fig. 1 provides for the embodiment of the present invention, as shown in the figure: the A star method for searching based on Binary Heap node sequencing provided by the invention, comprises the following steps:
S1: initialization OPEN table, CLOSE table and impact point A, put into OPEN table by start node S, sky put by CLOSE table;
S2: judge whether OPEN table is empty, if not, then get a node n from the gauge outfit of OPEN table; If so, then algorithmic procedure is terminated;
S3: judge whether node n is target solution A, if so, then output node n; If not, then step S4 is proceeded to; Described target solution is the impact point A that finally will find, and namely finds a paths to arrive impact point from starting point;
S4: launched to form direct correlation child nodes by all successor nodes of node n, judges child node whether in CLOSE table, if not, then child node is put into OPEN and show;
S5: the node n judged is put into CLOSE table, adopts the assessment values f ' (n) of each successor node of following formulae discovery node n simultaneously;
f′(n)＝g′(n)+h′(n)；
Wherein, f ' (n) is evaluation function, and g ' (n) is the shortest path value that start node arrives node n, and h ' (n) is the inspiration value of node n to the shortest path warp of target;
S6: OPEN table is carried out heapsort by assessment values f ' (x), node minimum for assessment values f ' (x) is placed on the gauge outfit of OPEN table, returns step S2 repetitive cycling.
Described OPEN table, for storing the next node for traversal;
Described CLOSE table, for storing the path found.
Described heapsort adopts Binary Heap to sort;
Described Binary Heap carries out in the following manner:
First the assessment values f ' (x) that OPEN shows interior joint is obtained, by node placement minimum for assessment values f ' (x) on heap top;
Then from remaining node, select two child nodes of the minimum and secondary little node of assessment values as a upper node;
Finally repeat respectively to be that two sub-sensor selection problem go out two child nodes of the minimum and secondary little node of assessment values as a upper node; Arrange until all OPEN are shown interior joint.
Described heapsort adopts Binary Heap to sort; Described Binary Heap carries out in the following manner:
First obtain the assessment values f ' (x) that OPEN shows interior joint, node minimum for assessment values f ' (x) is stored in first element memory address of one-dimension array; Then node minimum for the assessment values f ' (x) in remaining node is stored in second element memory address of one-dimension array, last until complete the sequence of all nodes in OPEN table.
The A star Pathfinding system figure based on Binary Heap node sequencing that Fig. 2 provides for the embodiment of the present invention, as shown in the figure, the present embodiment additionally provides a kind of A star Pathfinding system based on Binary Heap node sequencing, comprises initialization module, OPEN table judge module, node judge module, association child node module, node assessment values computing module, heapsort module;
Described initialization module, for initialization OPEN table, CLOSE table and impact point A, start node S is put into OPEN table, sky put by CLOSE table;
Described OPEN shows judge module, for judging whether OPEN table is empty, if not, then gets a node n from the gauge outfit of OPEN table; If so, then algorithmic procedure is terminated;
Described node judge module, for judging whether node n is target solution A, if so, then output node n; If not, then step S4 is proceeded to; Described target solution is the impact point A that finally will find, and namely finds a paths to arrive impact point from starting point;
Described association child node module, for being launched to form direct correlation child nodes by all successor nodes of node n, judging child node whether in CLOSE table, if not, then child node being put into OPEN and show;
Described node assessment values computing module, for the node n judged being put into CLOSE table, adopts the assessment values f ' (n) of each successor node of following formulae discovery node n simultaneously;
f′(n)＝g′(n)+h′(n)；
Wherein, f ' (n) is evaluation function, and g ' (n) is the shortest path value that start node arrives node n, and h ' (n) is the inspiration value of node n to the shortest path warp of target;
Described heapsort module, for OPEN table is carried out heapsort by assessment values f ' (x), is placed on the gauge outfit of OPEN table by node minimum for assessment values f ' (x).
Described OPEN table, for storing the next node for traversal;
Described CLOSE table, for storing the path found.
Heapsort in described heapsort module adopts Binary Heap to sort;
Described Binary Heap carries out in the following manner:
First the assessment values f ' (x) that OPEN shows interior joint is obtained, by node placement minimum for assessment values f ' (x) on heap top;
Then from remaining node, select two child nodes of the minimum and secondary little node of assessment values as a upper node;
Finally repeat respectively to be that two sub-sensor selection problem go out two child nodes of the minimum and secondary little node of assessment values as a upper node; Arrange until all OPEN are shown interior joint.
Heapsort in described heapsort module adopts Binary Heap to sort; Described Binary Heap carries out in the following manner:
First obtain the assessment values f ' (x) that OPEN shows interior joint, node minimum for assessment values f ' (x) is stored in first element memory address of one-dimension array; Then node minimum for the assessment values f ' (x) in remaining node is stored in second element memory address of one-dimension array, last until complete the sequence of all nodes in OPEN table.
Embodiment 2
The difference of the present embodiment and embodiment 1 is only:
The present embodiment states the A star method for searching based on Binary Heap node sequencing in detail, and the method that the present embodiment provides is in A star algorithm, introduce the sequence that Binary Heap carries out node, thus improves the efficiency of algorithm, and detailed process is as follows:
1, initialization OPEN table (for storing the next node for traversal), CLOSE shows (for storing the path found), start node S is put into OPEN table, and sky put by CLOSE table;
If 2 OPEN tables are not empty, get a node n from gauge outfit, if be the failure of empty algorithm;
3, judge that node n is target solution, if so, find a solution (continuation searching, or termination algorithm); If not proceeding to step 4;
4, the 4th step is divided into following step
4.1, all successor nodes of node n are launched, are exactly can the node (child node) of direct correlation from node n, if not in CLOSE table, just they are put into OPEN and show,
4.2 and S put into CLOSE table, calculate the assessment values f ' (n) of each successor node simultaneously.
(f ' (n)=g ' (n)+h ' (n), f ' (n) is evaluation function, g ' (n) is the shortest path value of starting point to node n, and h ' (n) is the inspiration value that n arrives the shortest path warp of target.
4.3, OPEN table is carried out heapsort by f (x), minimum is placed on gauge outfit, and repeating algorithm proceeds to step 2
What finally illustrate is, above embodiment is only in order to illustrate technical scheme of the present invention and unrestricted, although by referring to the preferred embodiments of the present invention, invention has been described, but those of ordinary skill in the art is to be understood that, various change can be made to it in the form and details, and not depart from the spirit and scope of the present invention that appended claims limits.
Claims (8)
1., based on the A star method for searching of Binary Heap node sequencing, it is characterized in that: comprise the following steps:
S1: initialization OPEN table, CLOSE table and impact point A, put into OPEN table by start node S, sky put by CLOSE table;
S2: judge whether OPEN table is empty, if not, then get a node n from the gauge outfit of OPEN table; If so, then algorithmic procedure is terminated;
S3: judge whether node n is target solution A, if so, then terminates algorithm, if not, then proceeds to step S4; Described target solution is the impact point A that finally will find;
S4: launched to form direct correlation child nodes by all successor nodes of node n, judges child node whether in CLOSE table, if not, then child node is put into OPEN and show;
S5: the node n judged is put into CLOSE table, adopts the assessment values f ' (n) of each successor node of following formulae discovery node n simultaneously;
f′(n)＝g′(n)+h′(n)；
Wherein, f ' (n) is evaluation function, and g ' (n) is the shortest path value that start node arrives node n, and h ' (n) is the inspiration value of node n to the shortest path warp of target;
S6: OPEN table is carried out heapsort by assessment values f ' (x), node minimum for assessment values f ' (x) is placed on the gauge outfit of OPEN table, returns step S2 repetitive cycling.
2. the A star method for searching based on Binary Heap node sequencing according to claim 1, is characterized in that: described OPEN table, for storing the next node for traversal; Described CLOSE table, for storing the path found.
3. the A star method for searching based on Binary Heap node sequencing according to claim 1, is characterized in that: described heapsort adopts Binary Heap to sort;
Described Binary Heap carries out in the following manner:
First the assessment values f ' (x) that OPEN shows interior joint is obtained, by node placement minimum for assessment values f ' (x) on heap top;
Then from remaining node, select two child nodes of the minimum and secondary little node of assessment values as a upper node;
Finally repeat respectively to be that two sub-sensor selection problem go out two child nodes of the minimum and secondary little node of assessment values as a upper node; Arrange until all OPEN are shown interior joint.
4. the A star method for searching based on Binary Heap node sequencing according to claim 1, is characterized in that: described heapsort adopts Binary Heap to sort; Described Binary Heap carries out in the following manner:
First obtain the assessment values f ' (x) that OPEN shows interior joint, node minimum for assessment values f ' (x) is stored in first element memory address of one-dimension array; Then node minimum for the assessment values f ' (x) in remaining node is stored in second element memory address of one-dimension array, last until complete the sequence of all nodes in OPEN table.
5. based on the A star Pathfinding system of Binary Heap node sequencing, it is characterized in that: comprise initialization module, OPEN table judge module, node judge module, association child node module, node assessment values computing module, heapsort module;
Described initialization module, for initialization OPEN table, CLOSE table and impact point A, start node S is put into OPEN table, sky put by CLOSE table;
Described OPEN shows judge module, for judging whether OPEN table is empty, if not, then gets a node n from the gauge outfit of OPEN table; If so, then algorithmic procedure is terminated;
Described node judge module, for judging whether node n is target solution A, if so, then output node n, and return step S2 and get another node from the gauge outfit that OPEN shows; If not, then step S4 is proceeded to; Described target solution is the impact point A that finally will find, and namely finds a paths to arrive impact point from starting point;
Described association child node module, for being launched to form direct correlation child nodes by all successor nodes of node n, judging child node whether in CLOSE table, if not, then child node being put into OPEN and show;
Described node assessment values computing module, for the node n judged being put into CLOSE table, adopts the assessment values f ' (n) of each successor node of following formulae discovery node n simultaneously;
f′(n)＝g′(n)+h′(n)；
Wherein, f ' (n) is evaluation function, and g ' (n) is the shortest path value that start node arrives node n, and h ' (n) is the inspiration value of node n to the shortest path warp of target;
Described heapsort module, for OPEN table is carried out heapsort by assessment values f ' (x), is placed on the gauge outfit of OPEN table by node minimum for assessment values f ' (x).
6. the A star Pathfinding system based on Binary Heap node sequencing according to claim 1, is characterized in that: described OPEN table, for storing the next node for traversal;
Described CLOSE table, for storing the path found.
7. the A star Pathfinding system based on Binary Heap node sequencing according to claim 1, is characterized in that: the heapsort in described heapsort module adopts Binary Heap to sort;
Described Binary Heap carries out in the following manner:
First the assessment values f ' (x) that OPEN shows interior joint is obtained, by node placement minimum for assessment values f ' (x) on heap top;
Then from remaining node, select two child nodes of the minimum and secondary little node of assessment values as a upper node;
Finally repeat respectively to be that two sub-sensor selection problem go out two child nodes of the minimum and secondary little node of assessment values as a upper node; Arrange until all OPEN are shown interior joint.
8. the A star Pathfinding system based on Binary Heap node sequencing according to claim 1, is characterized in that: the heapsort in described heapsort module adopts Binary Heap to sort; Described Binary Heap carries out in the following manner:
First obtain the assessment values f ' (x) that OPEN shows interior joint, node minimum for assessment values f ' (x) is stored in first element memory address of one-dimension array; Then node minimum for the assessment values f ' (x) in remaining node is stored in second element memory address of one-dimension array, last until complete the sequence of all nodes in OPEN table.
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