CN108970083B - Golf hitting path planning method - Google Patents
Golf hitting path planning method Download PDFInfo
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- CN108970083B CN108970083B CN201810607857.8A CN201810607857A CN108970083B CN 108970083 B CN108970083 B CN 108970083B CN 201810607857 A CN201810607857 A CN 201810607857A CN 108970083 B CN108970083 B CN 108970083B
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B69/00—Training appliances or apparatus for special sports
- A63B69/36—Training appliances or apparatus for special sports for golf
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Abstract
The invention discloses a golf hitting path planning method, which comprises the following steps: initializing GPS information of a court and a hole, and initializing historical score data of a user; a user selects a ball hole to be planned, and the standard pole of the ball hole and corresponding field data are obtained; and planning a batting path according to the historical achievement data of the user, the standard club of the hole and the field data and pushing the batting path to the front end. The batting path planning in the invention generates the feasibility scheme list based on the GPS information of the court and the hole and the historical score data of the user, and then selects and presents the optimal path through the scheme selection algorithm, thereby ensuring that the user can obtain the personalized path planning scheme matched with the self ability and the field, and effectively helping the user to improve the batting score.
Description
Technical Field
The invention belongs to the technical field of path planning, and particularly relates to a golf hitting path planning method.
Background
Golf is currently being regarded as a recreational activity in China and is not fully developed. Path planning for a player's play is largely empirical, aided by non-specialized equipment or software such as rangefinders to improve play performance. No software or hardware methods or devices for actively planning a batting path based on the historical performance of the user exist in the industry. Meanwhile, software and hardware equipment such as a distance meter can only measure the linear distance between two visible points, and the distance measuring hardware equipment is relatively large in size and inconvenient to carry.
Disclosure of Invention
The invention aims to: the method solves the defects in the prior art, provides a golf hitting path planning method, provides a personalized path planning scheme for matching the self ability and the field for the user, and effectively helps the user to improve the hitting performance.
In order to achieve the purpose, the invention adopts the technical scheme that:
a golf stroke path planning method, comprising the steps of:
the method comprises the following steps: initializing GPS information of a court and a hole, and initializing historical score data of a user;
step two: a user selects a ball hole to be planned, and the standard pole of the ball hole and corresponding field data are obtained;
step three: and planning a batting path according to the historical achievement data of the user, the standard club of the hole and the field data and pushing the batting path to the front end.
Further, the historical achievement data of the user in the first step comprises the average difference point and the realization probability of each hitting distance range of the user.
Further, the field data in the second step includes continuous or discrete longitude and latitude coordinate data of the boundary, the lane, the green, the obstacle and the hole.
Further, the third step is specifically:
step 101: generating a batting feasibility scheme list according to the historical score data of the user, the standard club of the ball hole and the field data;
step 102: sequencing the feasibility schemes through a scheme selection algorithm to obtain the feasibility scheme with the maximum realization probability;
step 103: and pushing the feasibility scheme with the maximum realization probability to the front end for display.
Further, the step 101 specifically includes the following steps:
step 201: acquiring the number x of standard poles of the current hole and the total distance l of a fairway;
step 202: calculating the number x of push rodstIf x is less than or equal to 4, xtIf x is greater than 4, x is 1t＝2；
Step 203: calculating the number x of swinghThe calculation formula is as follows: x is the number ofh＝x-xt；
Step 204: combining in a cyclic recursive manner according to the realization probability of each batting distance range in the user data from high to low to form a stroke range not exceeding xtList of all possibilities for the total distance l to be reached by the secondary stroke;
step 205: and according to the field data, the feasibility scheme of the drop point in the obstacle area is removed, and a batting feasibility scheme list is obtained.
Further, in step 204, when the user has no historical result data and provides the standard deviation point, the system compares the historical result data of the users with similar standard deviation points, and combines the historical result data in a cyclic recursive manner to form a result that x is not more thantList of all possibilities for the total distance l to be reached by the secondary stroke; if the user has no history data andand if no standard deviation point exists or the system is in a cold start state, the system automatically generates a default built-in path planning scheme.
Further, the step 102 specifically includes the following steps for each hitting possibility in the hitting possibility list:
step 301: obtaining the distance x between the landing points from the hitting feasibility plan1To xnWherein n is the total number of the falling points, x1The distance from the first drop point to the serving table;
step 302: obtaining x from historical performance data1To xnCorresponding hit ball realization probability p1To pm；:
Step 303: calculating x1To xnCorresponding system default upper interval tuAnd the system shortage lower interval tlBy default, the system upper interval tuThe sum of the distance between the boundary on the court and the corresponding drop point, the system missing interval tlThe difference between the corresponding distance between the falling points and the lower boundary of the ball field;
step 304: the system traverses the target distance at tl,tu]All realization probabilities p withinxAfter a maximum and a minimum value are eliminated, a maximum realization probability value p is obtainedbAnd a minimum realization probability value pw；
Step 305: calculating the planning probability corresponding to the distance between the falling points
Step 306: according to the planning probability pf1To pfnCalculating the realization probability p of the planning scheme, wherein the calculation formula is as follows: p ═ pi pfn;
further, in the third step, the user may actively modify the hitting path, where the actively modifying the hitting path includes: deleting any drop point; dragging any drop point to adjust the drop point position; clicking any non-drop point area to insert a new drop point, the system calculates the relationship between the new drop point and the existing drop point and re-plans the batting path.
A manual golf shot path planning method comprises the following steps:
step 401: initializing GPS information of a court and a hole, and initializing historical score data of a user;
step 402: the system acquires the current geographic position through a GPS, then acquires the hole number selected by a user and displays the top view of the hole;
step 403: the user sets the positions of all the falling points at one time in a multi-point touch mode, or sets the positions of all the falling points in sequence by clicking a screen;
step 404: the system calculates the distance between the falling points according to the positions of the falling points and sends the distance to the front end;
step 405: the system calculates the realization probability corresponding to the distance between the falling points according to the historical achievement data of the user and the distance between the falling points and sends the realization probability to the front end;
step 406: the user selects to confirm the batting scheme or returns to step 403 according to the distance between the landing points and the corresponding realization probability.
Due to the adoption of the technical scheme, the invention has the beneficial effects that:
the batting path planning in the invention generates a feasibility scheme list based on GPS information of a court and a hole and historical score data of a user, and then selects and presents an optimal path through a scheme selection algorithm, so that the user can obtain an individualized path planning scheme matched with self ability and a field, and the user is effectively helped to improve the batting score;
the invention can automatically plan an individualized path scheme according to historical data and plan a batting path according to manual operation of a user, the user can realize the functions of deleting, adding, moving and the like of path points by clicking each planned path point, and the system automatically dynamically calculates and displays batting times, drop point positions, distances among points and other data according to an interaction result.
Drawings
Fig. 1 is a schematic flow chart of the batting path planning of the present invention.
Fig. 2 is a schematic diagram of an automatic path planning process according to the present invention.
Fig. 3 is a schematic flow chart of the manual path planning of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail with reference to the accompanying drawings 1 to 3.
A golf stroke path planning method, comprising the steps of:
the method comprises the following steps: initializing GPS information of a court and a hole, and initializing historical score data of a user;
step two: a user selects a ball hole to be planned, and the standard pole of the ball hole and corresponding field data are obtained;
step three: and planning a batting path according to the historical achievement data of the user, the standard club of the hole and the field data and pushing the batting path to the front end.
Further, the historical achievement data of the user in the first step comprises the average difference point and the realization probability of each hitting distance range of the user.
Further, the field data in the second step includes continuous or discrete longitude and latitude coordinate data of the boundary, the lane, the green, the obstacle and the hole.
Further, the third step is specifically:
step 101: generating a batting feasibility scheme list according to the historical score data of the user, the standard club of the ball hole and the field data;
step 102: sequencing the feasibility schemes through a scheme selection algorithm to obtain the feasibility scheme with the maximum realization probability;
step 103: and pushing the feasibility scheme with the maximum realization probability to the front end for display.
Further, the step 101 specifically includes the following steps:
step 201: acquiring the number x of standard poles of the current hole and the total distance l of a fairway;
step 202: calculating the number x of push rodstIf x is less than or equal to 4, xtIf x is greater than 4, x is 1t＝2；
Step 203: calculating the number x of swinghThe calculation formula is as follows: x is the number ofh＝x-xt；
Step 204: combining in a cyclic recursive manner according to the realization probability of each batting distance range in the user data from high to low to form a stroke range not exceeding xtList of all possibilities for the total distance l to be reached by the secondary stroke;
step 205: and according to the field data, the feasibility scheme of the drop point in the obstacle area is removed, and a batting feasibility scheme list is obtained.
Further, in step 204, when the user has no historical result data and provides the standard deviation point, the system compares the historical result data of the users with similar standard deviation points, and combines the historical result data in a cyclic recursive manner to form a result that x is not more thantList of all possibilities for the total distance l to be reached by the secondary stroke; if the user has no historical data and no standard deviation point, or the system is in a cold start state, the system automatically generates a default built-in path planning scheme, wherein the cold start state refers to an original state when the system is used for the first time.
Further, the step 102 specifically includes the following steps for each hitting possibility in the hitting possibility list:
step 301: obtaining the distance x between the landing points from the hitting feasibility plan1To xnWherein n is the total number of the falling points, x1The distance from the first drop point to the serving table;
step 302: obtaining x from historical performance data1To xnCorresponding hit ball realization probability p1To pm；:
Step 303: calculating x1To xnCorresponding system default upper interval tuAnd the system shortage lower interval tlBy default, the system upper interval tuThe sum of the distance between the boundary on the court and the corresponding drop point, the system missing interval tlThe difference between the corresponding distance between the falling points and the lower boundary of the ball field;
step 304: the system traverses the target distance at tl,tu]All realization probabilities p withinxAfter a maximum and a minimum value are eliminated, a maximum realization probability value p is obtainedbAnd a minimum realization probability value pw；
Step 305: calculating the planning probability corresponding to the distance between the falling points
Step 306: according to the planning probability pf1To pfnCalculating the realization probability p of the planning scheme, wherein the calculation formula is as follows: p ═ pi pfn;
further, in the third step, the user may actively modify the hitting path, where the actively modifying the hitting path includes: deleting any drop point; dragging any drop point to adjust the drop point position; clicking any non-drop point area to insert a new drop point, the system calculates the relationship between the new drop point and the existing drop point and re-plans the batting path.
A manual golf shot path planning method comprises the following steps:
step 401: initializing GPS information of a court and a hole, and initializing historical score data of a user;
step 402: the system acquires the current geographic position through a GPS, then acquires the hole number selected by a user and displays the top view of the hole;
step 403: the user sets the positions of all the falling points at one time in a multi-point touch mode, or sets the positions of all the falling points in sequence by clicking a screen;
step 404: the system calculates the distance between the falling points according to the positions of the falling points and sends the distance to the front end;
step 405: the system calculates the realization probability corresponding to the distance between the falling points according to the historical achievement data of the user and the distance between the falling points and sends the realization probability to the front end;
step 406: the user selects to confirm the batting scheme or returns to step 403 according to the distance between the landing points and the corresponding realization probability.
In this embodiment, boundaries, lanes, putting green, holes, obstacles and the like in the geographic information of the ball hole in the court are converted into continuous or discrete longitude and latitude coordinates based on GIS data and recorded in a database for later use. Wherein the obstacle datamation attribute options are sand and water obstacles.
In this embodiment, the front end is displayed through a mobile phone in an APP or H5 page manner, and the user can obtain necessary information about path planning, including the number of times of hitting a ball, the position of a drop point, and the distance between points.
When the user is not satisfied with the automatic planning content, the operation is as follows:
a) clicking any drop point in the front-end page, and deleting the drop point;
b) dragging any drop point, and adjusting the position of the drop point;
c) clicking any non-drop point area, automatically calculating the relation with the existing drop point by the system, and inserting a new drop point;
d) automatically calculating the distance between the falling points and the realization probability;
e) and displaying the distance between the falling points and the realization probability.
The batting path planning in the invention generates a feasibility scheme list based on GPS information of a court and a hole and historical score data of a user, and then selects and presents an optimal path through a scheme selection algorithm, so that the user can obtain an individualized path planning scheme matched with self ability and a field, and the user is effectively helped to improve the batting score;
the invention can automatically plan an individualized path scheme according to historical data and plan a batting path according to manual operation of a user, the user can realize the functions of deleting, adding, moving and the like of path points by clicking each planned path point, and the system automatically dynamically calculates and displays batting times, drop point positions, distances among points and other data according to an interaction result.
Claims (5)
1. A method of planning a route for a golf shot, comprising the steps of:
the method comprises the following steps: initializing GPS information of a court and a hole, and initializing historical score data of a user;
step two: a user selects a ball hole to be planned, and the standard pole of the ball hole and corresponding field data are obtained;
step three: planning a batting path according to the historical score data of the user, the standard club of the ball hole and the field data and pushing the batting path to the front end;
the historical achievement data of the user in the first step comprises average difference points and the realization probability of each ball hitting distance range of the user;
the third step is specifically as follows:
step 101: generating a batting feasibility scheme list according to the historical score data of the user, the standard club of the ball hole and the field data;
step 102: sequencing the feasibility schemes through a scheme selection algorithm to obtain the feasibility scheme with the maximum realization probability;
step 103: pushing the feasibility scheme with the maximum probability to the front end for display;
the step 101 specifically comprises the following steps:
step 201: acquiring the number x of standard poles of the current hole and the total distance l of a fairway;
step 202: calculating the number x of push rodstIf x is less than or equal to 4, xtIf x is greater than 4, x is 1t＝2；
Step 203: calculating the number x of swinghThe calculation formula is as follows: x is the number ofh＝x-xt；
Step 204: combining in a cyclic recursive manner according to the realization probability of each batting distance range in the user data from high to low to form a stroke range not exceeding xtList of all possibilities for the total distance l to be reached by the secondary stroke;
step 205: and according to the field data, the feasibility scheme of the drop point in the obstacle area is removed, and a batting feasibility scheme list is obtained.
2. A golf stroke path planning method according to claim 1, wherein: and the field data in the second step comprises continuous or discrete longitude and latitude coordinate data of the boundary, the lane, the green, the obstacle and the hole.
3. A golf stroke path planning method according to claim 1, wherein: said step 204, when the user has no historical result data and provides standard deviation points, comparing the historical result data of the user with similar standard deviation points by the system, and combining in a circulating recursion mode to form a result that the number of the historical result data does not exceed xtList of all possibilities for the total distance l to be reached by the secondary stroke; and if the user has no historical data and no standard deviation point, or the system is in a cold start state, automatically generating a default built-in path planning scheme by the system.
4. A golf stroke path planning method according to claim 1, wherein: the step 102 is embodied as performing the following steps for each of the hit feasibility plans in the hit feasibility plan list:
step 301: obtaining the distance x between the landing points from the hitting feasibility plan1To xnWherein n is the total number of the falling points, x1The distance from the first drop point to the serving table;
step 302: obtaining x from historical performance data1To xnCorresponding hit ball realization probability p1To pm；
Step 303: calculating x1To xnCorresponding system default upper interval tuAnd the system shortage lower interval tlBy default, the system upper interval tuThe sum of the distance between the boundary on the court and the corresponding drop point, the system missing interval tlThe difference between the corresponding distance between the falling points and the lower boundary of the ball field;
step 304: the system traverses the target distance at tl,tu]All realization probabilities p withinxAfter a maximum and a minimum value are eliminated, a maximum realization probability value p is obtainedbAnd a minimum realization probability value pw；
Step 305: calculating the planning probability corresponding to the distance between the falling points
Step 306: according to the planning probability pf1To pfnCalculating the realization probability p of the batting feasibility schemeThe calculation formula is as follows: p ═ pfn.
5. A golf stroke path planning method according to claim 1, wherein: in the third step, the user may actively modify the hitting path, where the actively modifying the hitting path includes: deleting any drop point; dragging any drop point to adjust the drop point position; clicking any non-drop point area to insert a new drop point, the system calculates the relationship between the new drop point and the existing drop point and re-plans the batting path.
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| US9486669B2 (en) * | 2008-02-20 | 2016-11-08 | Nike, Inc. | Systems and methods for storing and analyzing golf data, including community and individual golf data collection and storage at a central hub |
| CN101318068A (en) * | 2008-06-23 | 2008-12-10 | 柯文生 | Method for establishing performance data base of golf ball player with global positioning system |
| CN103252070B (en) * | 2012-02-15 | 2016-08-03 | 幻音科技(深圳)有限公司 | Householder method in clock-golf and system |
| GB2551535A (en) * | 2016-06-21 | 2017-12-27 | Alexander Borrie John | A golf swing analyser |
| CN107050813A (en) * | 2017-01-03 | 2017-08-18 | 深圳市酷高网络科技有限公司 | The householder method of golf |
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