CN116185023A - Source searching path planning method, device and storage medium for improving artificial potential field - Google Patents
Source searching path planning method, device and storage medium for improving artificial potential field Download PDFInfo
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Abstract
The invention provides a source searching path planning method, a device and a storage medium for improving an artificial potential field, wherein the method comprises the steps of constructing an initial multi-source radiation field, reconstructing the initial multi-source radiation field, constructing an artificial potential field model, moving a robot according to the direction of the planned source searching path, measuring signals of radiation sources along the way, and adding an additional potential field at the position of the robot to obtain a new artificial potential field model if a plurality of radiation sources are detected to have radiation intensity maximum points, and obtaining the direction of the new source searching path through the new artificial potential field model to search the next radiation source; the invention converts the influence of the 'exploring hot spot' on the artificial potential field from attractive force to repulsive force, and adds the additional potential field at the position of the robot to obtain a new artificial potential field model, thereby leading the new artificial potential field model to guide the robot to smoothly leave the current radioactive source and start the search of the next radioactive source, and solving the problem that the traditional artificial potential field method can sink into potential field traps in a multi-source environment.
Description
Technical Field
The invention mainly relates to the technical field of radioactive source detection, in particular to a source searching path planning method, a source searching path planning device and a storage medium for improving an artificial potential field.
Background
The radioactive source makes an important contribution to promoting the economic development and social progress of China, but in the process of using, storing and transporting the radioactive source, some radioactive accidents caused by losing control due to loss, theft and illegal transfer of the radioactive source occur, and if the radioactive accidents cannot be effectively treated in time, the radioactive accidents bring great risks to public health. Under the conditions of safety accidents such as loss, stolen radioactive sources and the like, how to quickly invert the position information of the radioactive sources and give out the distribution information of a radiation field according to the data of a plurality of detectors is a key link for quickly searching, positioning and safely removing scattered radioactive sources, is an important means for guaranteeing the safe and efficient utilization of nuclear technology, and has great practical significance for a nuclear safety emergency response strategy.
At present, the method aims at source searching in a multi-source radiation environment, is mostly aimed at an open and simple scene, and rarely considers the influence of obstacles on source searching. However, in a real radioactive accident, a plurality of radioactive sources exist simultaneously due to radioactive substance leakage and other reasons, the environment where the radioactive sources are located is very complex, obstacles such as buildings, office facilities and sundries exist, the influence of the obstacles on a source distribution probability density function is not considered in the existing multi-source radiation field reconstruction method based on particle filtering, when a new obstacle appears, the original source distribution probability density function and the actual distribution have great difference, the real radiation field cannot be represented, and the traditional path planning based on the artificial potential field method cannot be used for planning a subsequent path after finding a 'detection hot spot' when a plurality of radioactive sources exist, so that the effect is not ideal.
Disclosure of Invention
The invention aims to solve the technical problem of providing a source searching path planning method, a source searching path planning device and a storage medium for improving an artificial potential field aiming at the defects of the prior art.
The technical scheme for solving the technical problems is as follows: a source-seeking path planning method for improving an artificial potential field, comprising the steps of:
arranging a plurality of particles in a radiation area, using the plurality of particles as a plurality of radiation sources, detecting signals of the radiation sources in the radiation area through a preset robot to obtain parameter information of the plurality of radiation sources, and constructing an initial multi-source radiation field through the parameter information of the plurality of radiation sources;
reconstructing an initial multi-source radiation field, establishing an artificial potential field model in the reconstructed multi-source radiation field, and obtaining the direction of the source searching path of the current radioactive source through the artificial potential field model;
and the robot moves according to the direction of the planned source searching path and performs signal measurement of the radiation source along the way, if the radiation intensity maximum points exist in a plurality of radiation sources, an additional potential field is added at the position of the robot to obtain a new artificial potential field model, and the new direction of the source searching path is obtained through the new artificial potential field model so as to perform next radiation source searching.
The other technical scheme for solving the technical problems is as follows: a source-seeking path planning apparatus for improving an artificial potential field, comprising:
the multi-source radiation field construction module is used for arranging a plurality of particles in a radiation area, taking the particles as a plurality of radiation sources, detecting signals of the radiation sources in the radiation area through a preset robot to obtain parameter information of the plurality of radiation sources, and constructing an initial multi-source radiation field through the parameter information of the plurality of radiation sources;
the radiation field reconstruction and artificial potential field model establishment module is used for carrying out radiation field reconstruction on an initial multi-source radiation field, establishing an artificial potential field model in the reconstructed multi-source radiation field, and obtaining the direction of the source searching path of the current radiation source through the artificial potential field model;
and the artificial potential field model updating module is used for moving the robot according to the direction of the planned source searching path and measuring signals of the radiation sources along the way, and if the radiation intensity maximum points exist in the plurality of radiation sources, adding an additional potential field at the position of the robot to obtain a new artificial potential field model, and obtaining the direction of the new source searching path through the new artificial potential field model to search the next radiation source.
The other technical scheme for solving the technical problems is as follows: a source-seeking path planning apparatus for improving an artificial potential field, comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that the source-seeking path planning method for improving an artificial potential field as described above is implemented when said computer program is executed by said processor.
The other technical scheme for solving the technical problems is as follows: a computer readable storage medium storing a computer program, characterized in that a source-seeking path planning method of improving an artificial potential field as described above is implemented when the computer program is executed by a processor.
The beneficial effects of the invention are as follows: the invention realizes the radiation field reconstruction under the multi-source complex environment, establishes the artificial potential field model, converts the influence of the 'finding hot spot' on the artificial potential field from attractive force to repulsive force, and adds the additional potential field at the position of the robot to obtain a new artificial potential field model, thereby leading the new artificial potential field model to guide the robot to smoothly leave the current radioactive source and start the search of the next radioactive source, and solving the problem that the traditional artificial potential field method can sink into potential field traps under the multi-source environment.
Drawings
FIG. 1 is a flow chart of a method for planning a source-seeking path for improving an artificial potential field according to an embodiment of the present invention;
fig. 2 is a block diagram of a source-seeking path planning apparatus for improving an artificial potential field according to an embodiment of the present invention.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
Example 1:
as shown in fig. 1, a source-seeking path planning method for improving an artificial potential field includes the following steps:
arranging a plurality of particles in a radiation area, using the plurality of particles as a plurality of radiation sources, detecting signals of the radiation sources in the radiation area through a preset robot to obtain parameter information of the plurality of radiation sources, and constructing an initial multi-source radiation field through the parameter information of the plurality of radiation sources;
reconstructing an initial multi-source radiation field, establishing an artificial potential field model in the reconstructed multi-source radiation field, and obtaining the direction of the source searching path of the current radioactive source through the artificial potential field model;
and the robot moves according to the direction of the planned source searching path and performs signal measurement of the radiation source along the way, if the radiation intensity maximum points exist in a plurality of radiation sources, an additional potential field is added at the position of the robot to obtain a new artificial potential field model, and the new direction of the source searching path is obtained through the new artificial potential field model so as to perform next radiation source searching.
In the embodiment, the radiation field reconstruction under the multi-source complex environment is realized, the artificial potential field model is built, the influence of the 'finding hot spot' on the artificial potential field is converted into repulsive force from attractive force, and the additional potential field is added at the position of the robot to obtain a new artificial potential field model, so that the new artificial potential field model can guide the robot to smoothly leave the current radiation source and start the search of the next radiation source, and the problem that the traditional artificial potential field method can sink into potential field traps under the multi-source environment is solved.
Specifically, the constructing an initial multi-source radiation field by the parameter information of the plurality of radiation sources specifically includes:
using a plurality of particles as a plurality of radioactive sources, detecting signals of the radioactive sources in the radiation area through a preset robot, setting each particle to have own weight, wherein the weight is a specific gravity value of the radioactive sources in the radiation area, and the parameter information of the plurality of radioactive sources comprises the following steps of using { X } i,0,k ，Y i,0,k ，I i,0,k ，w i,0,k All particle sets, where X i,0,k and Yi,0,k Indicating the position of the source, I i,0,k Indicating the source intensity, w of the radioactive source i,0,k The weight of particles is represented, the sum of weight values of all particles after the kth detection is 1, the initial multi-source radiation field is a multi-source radiation field with an obstacle, a point-nuclear calculation formula of a multi-layer medium is adopted, and after final convergence, the initial multi-source radiation field is obtained by the following steps:
wherein delta represents the dirac function, a 0:k Representing a radiation count value calculated from the current radiation source term,
wherein B represents the accumulation factor of the multilayer medium in the radiation field, mu j Represents the attenuation coefficient, t, of a medium j j Representing the distance across the medium j, F (E) is the selected flux-to-dose conversion factor.
Specifically, the radiation field reconstruction of the initial multi-source radiation field is specifically:
s1.1: and (3) carrying out importance sampling of particles:
by means of an importance probability density function q (A 0:k |z 1:k ) A sampling of the initial sample is performed,
wherein ,
by a sequential importance sampling method, the importance weight of the next observation point is only related to the last importance weight, and w i,k (A 0:k )＝w i,k-1 (A 0:k )·p(z k |A i,k ) The method comprises the steps of carrying out a first treatment on the surface of the In the step S1.1, a sequential importance sampling method is introduced, so that the importance weight of the next observation point is only associated with the last importance weight, and the problems of waste of calculation resources and high calculation difficulty are solved.
S1.2: resampling based on real-time probe information:
repeating the step S1.1 to re-sample the importance of the particles when the robot obtains new detection information, copying the particles with high weight values, discarding the particles with low weight values, and enabling the number of the copied particles to be equal to the number of the discarded particles;
s1.3: radiation source parameter estimation:
based on the position and source intensity of the radiation field source item obtained by the current robot, calculating a radiation dose field by using a particle transport calculation tool to obtain a radiation dose value detected by the current detection point,
performing linear fitting on the radiation dose values to obtain a linear fitting equation
Wherein (1)>
Calculating standard deviation of linear fitting
Uncertainty->
wherein ,
representing the error caused by the estimated source strength at the mth detection point,
the goodness of fit R2 is calculated,
wherein RSS represents the total sum of squares and TSS represents the sum of squares of residuals，
Calculating a figure of merit
Stopping iteration when the quality factor meets the preset precision requirement, otherwise calculating a weighting function, weighting the original equation set to obtain WAx =wb, and repeatedly solving a least square solution to calculate a weighted initial source strength, wherein the weighting function is as follows:
and carrying out iteration on the weighted initialization source intensity brought into the equation set, and finally obtaining the reconstructed multi-source radiation field.
Aiming at source searching path planning under a multi-source scene, after a certain radioactive source is searched, deleting the part of the source contributing to the gravitation function in the artificial potential field, defining the position as a negative source so as to add a repulsive force item in the repulsive force function, thereby leading the artificial potential field to guide the robot to smoothly leave the radioactive source and start searching of the next radioactive source. When the source falls into a "false hot spot", an additional potential field is added at that location to allow the robot to escape the "false hot spot" trap. How to add an additional potential field is described in detail below.
Establishing an artificial potential field model in the reconstructed multi-source radiation field, and obtaining a source searching path of the current radiation source through the artificial potential field model, wherein the artificial potential field model specifically comprises the following steps:
s2.1: establishing a gravitation potential field function of a radiation source to be detected, wherein the gravitation potential field function of the radiation source to be detected is as follows:
wherein ζ represents an attractive scale factor, d (x, x) t ) Representing the current position (x) of the robot and the position (x) of the radiation source to be ascertained t ) Is used for the distance of (a),
calculating the attraction force received by the robot through the negative gradient of the attraction potential field, wherein the attraction force is expressed as:
when the object is relatively far from the target point, the attractive force will become particularly large, and the relatively small repulsive force may encounter obstacles in the path of the object, even if it is negligible.
And, introduce the correction gravitation function in the above formula, avoid because too far away from the goal point and lead to the gravitation to be too big.
It will be appreciated that the equation (3) increases the range limit compared to the equation (1), i.e. a threshold is given that defines the effective distance d of the gravitational field between the target and the object att 。
The gravitational force correction received by the robot is as follows:
s2.2: establishing a repulsive potential field function of an obstacle, wherein the repulsive potential field function of the obstacle is as follows:
wherein eta represents the repulsive force scale factor, d (x, x) b ) Representing the current position (x) of the object and the position (x) of the obstacle b ) Distance d of (d) req Representing the radius of influence of each obstacle. When the robot leaves the obstacle at a certain distance, the obstacle has no repulsive force effect on the object.
The gradient of the repulsive field corresponding to the repulsive force is as follows:
if the obstacle is near the target point, the repulsive force is larger than the attractive force, so that the target is not reachable, therefore, the invention aims to introduce a new repulsive force function, when the robot approaches the target point, the repulsive force is reduced while the attractive force is reduced until the robot reaches the target point, and the attractive force and the repulsive force are reduced to 0 at the same time, thereby solving the problem that the target is not reachable due to the fact that the obstacle is too close to the target point.
wherein ,
n is an integer, typically taking n=2,
the influence of the distance between the target and the object is added on the basis of the original repulsive field (n is an integer, and n=2 is usually taken). When an object approaches a target, although the repulsive field is increased, the distance is reduced, so that the repulsive field can be dragged to a certain extent.
The corresponding repulsive force becomes:
wherein ,
specifically, adding an additional potential field at the position of the robot to obtain a new artificial potential field model, and obtaining the direction of a new source searching path through the new artificial potential field model to search for the next radioactive source, specifically:
s3.1: establishing a repulsive potential field function of the ascertained radioactive source at the position of the robot, wherein the ascertained repulsive potential field function of the radioactive source is as follows:
wherein d (x, x ps ) Representing the current position (x) of the object and the ascertained radiation source (x b ) Is a distance of (2); d, d ps Representing a given threshold defining an effective distance of the gravitational field between the radiation source and the robot has been ascertained; when the robot leaves a certain distance from the ascertained radioactive source, the ascertained radioactive source has no repulsive force influence on the object.
The gradient of the repulsive field corresponding to the repulsive force is as follows:
s3.2: under a multi-source complex environment, a resultant force model is constructed according to superposition of all repulsive fields, all gravitational fields and the ascertained repulsive fields of the radioactive sources of the total potential field of the robot, the resultant force model is used as a new artificial potential field model, and the resultant force model is:
U(x)＝∑U att,i (x)+∑U req,j (x)+∑U req-ps,k (x)。
specifically, the direction of the new source-seeking path is obtained through the new artificial potential field model to perform the next radioactive source search, specifically:
obtaining a resultant force according to the resultant force model, and obtaining the direction of a new source searching path through the resultant force so as to perform next radioactive source searching, wherein the resultant force is as follows:
the robot will look for radiation sources based on the direction of the resultant force.
Example 2:
as shown in fig. 2, a source-seeking path planning apparatus for improving an artificial potential field, comprising:
the multi-source radiation field construction module is used for arranging a plurality of particles in a radiation area, taking the particles as a plurality of radiation sources, detecting signals of the radiation sources in the radiation area through a preset robot to obtain parameter information of the plurality of radiation sources, and constructing an initial multi-source radiation field through the parameter information of the plurality of radiation sources;
the radiation field reconstruction and artificial potential field model establishment module is used for carrying out radiation field reconstruction on an initial multi-source radiation field, establishing an artificial potential field model in the reconstructed multi-source radiation field, and obtaining the direction of the source searching path of the current radiation source through the artificial potential field model;
and the artificial potential field model updating module is used for moving the robot according to the direction of the planned source searching path and measuring signals of the radiation sources along the way, and if the radiation intensity maximum points exist in the plurality of radiation sources, adding an additional potential field at the position of the robot to obtain a new artificial potential field model, and obtaining the direction of the new source searching path through the new artificial potential field model to search the next radiation source.
Specifically, in the multi-source radiation field construction module, an initial multi-source radiation field is constructed through parameter information of a plurality of radiation sources, specifically:
using a plurality of particles as a plurality of radioactive sources, detecting signals of the radioactive sources in the radiation area through a preset robot, setting each particle to have own weight, wherein the weight is a specific gravity value of the radioactive sources in the radiation area, and the parameter information of the plurality of radioactive sources comprises the following steps of using { X } i,0,k ，Y i,0,k ，I i,0,k ，w i,0,k All particle sets, where X i,0,k and Yi,0,k Indicating the position of the source, I i,0,k Indicating the source intensity, w of the radioactive source i,0,k Representing the weight of the particles, and the sum of the weight values of all the particles after the kth detection is 1, the initialThe multi-source radiation field is a multi-source radiation field with barriers, a point-core calculation formula of a multi-layer medium is adopted, and the initial multi-source radiation field is obtained by the following steps:
wherein delta represents the dirac function, a 0:k Representing a radiation count value calculated from the current radiation source term,
wherein B represents the accumulation factor of the multilayer medium in the radiation field, mu j Represents the attenuation coefficient, t, of a medium j j Representing the distance across the medium j, F (E) is the selected flux-to-dose conversion factor.
Example 3:
a source-seeking path planning apparatus for improving an artificial potential field comprising a memory, a processor and a computer program stored in said memory and executable on said processor, which when executed by said processor implements a source-seeking path planning method for improving an artificial potential field as described above.
Example 4:
a computer readable storage medium storing a computer program which, when executed by a processor, implements a method of improving a source-seeking path planning for an artificial potential field as described above.
The invention has the advantages that an improved artificial potential field method taking the "finding hot spot" as the "virtual repulsive force" is provided, and the problem of potential field subsidence of the "finding hot spot" is solved. In the conventional path planning based on the artificial potential field method, when a plurality of radioactive sources exist, a subsequent path cannot be planned to find other sources after finding a 'hot spot'. In the project, a new repulsive force function is introduced into the artificial potential field, so that the influence of a 'exploring hot spot' on the artificial potential field is changed from attractive force to repulsive force, and the problem that the traditional artificial potential field method can sink into a potential field trap in a multi-source environment is solved.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present invention.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (10)
1. A method of source-seeking path planning for improving an artificial potential field, comprising the steps of:
arranging a plurality of particles in a radiation area, using the plurality of particles as a plurality of radiation sources, detecting signals of the radiation sources in the radiation area through a preset robot to obtain parameter information of the plurality of radiation sources, and constructing an initial multi-source radiation field through the parameter information of the plurality of radiation sources;
reconstructing an initial multi-source radiation field, establishing an artificial potential field model in the reconstructed multi-source radiation field, and obtaining the direction of the source searching path of the current radioactive source through the artificial potential field model;
and the robot moves according to the direction of the planned source searching path and performs signal measurement of the radiation source along the way, if the radiation intensity maximum points exist in a plurality of radiation sources, an additional potential field is added at the position of the robot to obtain a new artificial potential field model, and the new direction of the source searching path is obtained through the new artificial potential field model so as to perform next radiation source searching.
2. The method according to claim 1, wherein the constructing an initial multi-source radiation field from parameter information of a plurality of radiation sources, specifically:
using a plurality of particles as a plurality of radioactive sources, detecting signals of the radioactive sources in the radiation area through a preset robot, setting each particle to have own weight, wherein the weight is a specific gravity value of the radioactive sources in the radiation area, and the parameter information of the plurality of radioactive sources comprises the following steps of using { X } i,0,k ，Y i,0,k ，I i,0,k ，w i,0,k All particle sets, where X i,0,k and Yi,0,k Indicating the position of the source, I i,0,k Indicating the source intensity, w of the radioactive source i,0,k The weight of the particles is represented, the sum of weight values of all the particles after the kth detection is 1, the initial multi-source radiation field is a multi-source radiation field with an obstacle, a point-core calculation formula of a multi-layer medium is adopted, and the initial multi-source radiation field is obtained by the following steps:
wherein delta represents the dirac function, a 0:k Representing a radiation count value calculated from the current radiation source term,
wherein B represents the accumulation factor of the multilayer medium in the radiation field, mu j Represents the attenuation coefficient, t, of a medium j j Representing the distance across the medium j, F (E) is the selected flux-to-dose conversion factor.
3. The source-seeking path planning method according to claim 2, wherein the radiation field reconstruction of the initial multi-source radiation field is performed, in particular:
s1.1: and (3) carrying out importance sampling of particles:
by means of an importance probability density function q (A 0:k |z 1:k ) A sampling of the initial sample is performed,
wherein ,
by a sequential importance sampling method, the importance weight of the next observation point is only related to the last importance weight, and w i,k (A 0:k )＝w i,k-1 (A 0:k )·p(z k |A i,k )；
S1.2: resampling based on real-time probe information:
repeating the step S1.1 to re-sample the importance of the particles when the robot obtains new detection information, copying the particles with high weight values, discarding the particles with low weight values, and enabling the number of the copied particles to be equal to the number of the discarded particles;
s1.3: radiation source parameter estimation:
based on the position and source intensity of the radiation field source item obtained by the current robot, calculating a radiation dose field by using a particle transport calculation tool to obtain a radiation dose value detected by the current detection point,
performing linear fitting on the radiation dose values to obtain a linear fitting equation
wherein ,
calculating standard deviation of linear fitting
Uncertainty->
wherein ,
representing the error caused by the estimated source strength at the mth detection point,
calculating the goodness of fit R 2 ，
Where RSS represents the sum of the overall squares, TSS represents the sum of the residual squares,
calculating a figure of merit
Stopping iteration when the quality factor meets the preset precision requirement, otherwise calculating a weighting function, weighting the original equation set to obtain WAx =wb, and repeatedly solving a least square solution to calculate a weighted initial source strength, wherein the weighting function is as follows:
and carrying out iteration on the weighted initialization source intensity brought into the equation set, and finally obtaining the reconstructed multi-source radiation field.
4. A source-seeking path planning method according to claim 3, wherein an artificial potential field model is established in the reconstructed multi-source radiation field, and the source-seeking path of the current radiation source is obtained through the artificial potential field model, specifically:
s2.1: establishing a gravitation potential field function of a radiation source to be detected, wherein the gravitation potential field function of the radiation source to be detected is as follows:
wherein ζ represents an attractive scale factor, d (x, x) t ) Representing the current position (x) of the robot and the position (x) of the radiation source to be ascertained t ) Is used for the distance of (a),
calculating the attraction force received by the robot through the negative gradient of the attraction potential field, wherein the attraction force is expressed as:
and introduces a modified gravitational function into the equation above,
the gravitational force correction received by the robot is as follows:
s2.2: establishing a repulsive potential field function of an obstacle, wherein the repulsive potential field function of the obstacle is as follows:
wherein eta represents the repulsive force scale factor, d (x, x) b ) Representing the current position (x) of the object and the position (x) of the obstacle b ) Distance d of (d) req Representing the radius of influence of each obstacle;
the gradient of the repulsive field corresponding to the repulsive force is as follows:
wherein ,
n is an integer number, and is a number,
the corresponding repulsive force becomes:
wherein ,
5. the method of claim 4, wherein adding an additional potential field at the position of the robot to obtain a new artificial potential field model, and obtaining a new direction of the source-seeking path through the new artificial potential field model to perform a next radiation source search, specifically:
s3.1: establishing a repulsive potential field function of the ascertained radioactive source at the position of the robot, wherein the ascertained repulsive potential field function of the radioactive source is as follows:
wherein d (x, x ps ) Representing the current position (x) of the object and the ascertained radiation source (x b ) Is a distance of (2); d, d ps Representing a given threshold defining an effective distance of the gravitational field between the radiation source and the robot has been ascertained;
the gradient of the repulsive field corresponding to the repulsive force is as follows:
s3.2: constructing a resultant force model according to the superposition of all repulsive fields, all gravitational fields and the repulsive fields of the ascertained radioactive source of the total potential field of the position of the robot, and taking the resultant force model as a new artificial potential field model, wherein the resultant force model is as follows:
U(x)＝∑U att,i (x)+∑U req,j (x)+∑U req-ps,k (x)。
6. the method according to claim 5, wherein the obtaining the direction of the new source-seeking path by the new artificial potential field model is used for the next source search, specifically:
obtaining a resultant force according to the resultant force model, and obtaining the direction of a new source searching path through the resultant force so as to perform next radioactive source searching, wherein the resultant force is as follows:
F(x)＝-▽U(x)＝∑F att,i (x)+∑F req,j (x)+∑F req-ps,k (x)。
7. a source-seeking path planning apparatus for improving an artificial potential field, comprising:
the multi-source radiation field construction module is used for arranging a plurality of particles in a radiation area, taking the particles as a plurality of radiation sources, detecting signals of the radiation sources in the radiation area through a preset robot to obtain parameter information of the plurality of radiation sources, and constructing an initial multi-source radiation field through the parameter information of the plurality of radiation sources;
the radiation field reconstruction and artificial potential field model establishment module is used for carrying out radiation field reconstruction on an initial multi-source radiation field, establishing an artificial potential field model in the reconstructed multi-source radiation field, and obtaining the direction of the source searching path of the current radiation source through the artificial potential field model;
and the artificial potential field model updating module is used for moving the robot according to the direction of the planned source searching path and measuring signals of the radiation sources along the way, and if the radiation intensity maximum points exist in the plurality of radiation sources, adding an additional potential field at the position of the robot to obtain a new artificial potential field model, and obtaining the direction of the new source searching path through the new artificial potential field model to search the next radiation source.
8. The source-seeking path planning device according to claim 7, wherein in the multi-source radiation field construction module, an initial multi-source radiation field is constructed by parameter information of a plurality of radiation sources, specifically:
using a plurality of particles as a plurality of radioactive sources, detecting signals of the radioactive sources in the radiation area through a preset robot, setting each particle to have own weight, wherein the weight is a specific gravity value of the radioactive sources in the radiation area, and the parameter information of the plurality of radioactive sources comprises the following steps of using { X } i,0,k ，Y i,0,k ，I i,0,k ，w i,0,k All particle sets, where X i,0,k and Yi,0,k Indicating the position of the source, I i,0,k Indicating the source intensity, w of the radioactive source i,0,k Representing the weight of the particles, and the weight value of all particles after the kth detectionThe initial multi-source radiation field is a multi-source radiation field with an obstacle, and a point nuclear calculation formula of a multi-layer medium is adopted to obtain the initial multi-source radiation field as follows:
wherein delta represents the dirac function, a 0:k Representing a radiation count value calculated from the current radiation source term,
wherein B represents the accumulation factor of the multilayer medium in the radiation field, mu j Represents the attenuation coefficient, t, of a medium j j Representing the distance across the medium j, F (E) is the selected flux-to-dose conversion factor.
9. A source-seeking path planning apparatus for improving an artificial potential field comprising a memory, a processor and a computer program stored in said memory and executable on said processor, wherein the source-seeking path planning method for improving an artificial potential field according to any one of claims 1 to 6 is implemented when said computer program is executed by said processor.
10. A computer readable storage medium storing a computer program, characterized in that the method of source-seeking path planning for an improved artificial potential field according to any of claims 1 to 6 is implemented when the computer program is executed by a processor.
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