CN113344265A - Track closure judging method and device, computer equipment and storage medium - Google Patents

Track closure judging method and device, computer equipment and storage medium Download PDF

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CN113344265A
CN113344265A CN202110595017.6A CN202110595017A CN113344265A CN 113344265 A CN113344265 A CN 113344265A CN 202110595017 A CN202110595017 A CN 202110595017A CN 113344265 A CN113344265 A CN 113344265A
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CN113344265B (en
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高杰
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Shenzhen Water World Co Ltd
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Abstract

The invention relates to a track closing judgment method, a track closing judgment device, computer equipment and a storage medium, wherein a to-be-determined closing point is found by judging whether a distance value between a historical position before the current time and the position at the current time is smaller than a first judgment distance or not, a calculation starting point is obtained, the similarity of a first mutual position relation among a plurality of historical positions and a second mutual position relation among a plurality of subsequent positions is compared, and the comparison result is used for verifying whether the to-be-determined closing point is true or not, so that the track closing is accurately judged, and the condition of misjudgment caused by environment similarity when environmental pictures are compared is avoided.

Description

Track closure judging method and device, computer equipment and storage medium
Technical Field
The invention relates to the field of intelligent equipment operation rules, in particular to a track closure judgment method and device, computer equipment and a storage medium.
Background
For some intelligent devices with a walking function, it is necessary to determine whether the track of the intelligent device is closed to guide the intelligent device to perform corresponding operations. Currently, it is generally determined whether the trajectory of the smart device is closed by finding whether there are historical location coordinates near the location coordinates where the smart device is currently located. If the intelligent device is not accurate enough or the target site is complex, it is impossible to accurately judge whether the track is closed.
Disclosure of Invention
The invention mainly aims to provide a method and a device for judging track closing, computer equipment and a storage medium, and aims to solve the problem that whether a track is closed by intelligent equipment is easy to misjudge.
In order to achieve the above object, the present invention provides a trajectory closure determination method, which is applied to an intelligent device, and includes:
acquiring parameters of the intelligent equipment at the position of the current time every preset interval;
if the distance value between a historical position before the current time and the position at the current time is smaller than a first judgment distance, judging that the position at the current time is a to-be-determined closing point of the track of the intelligent equipment, and judging that the historical position is a calculation starting point;
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point and a plurality of subsequent positions of the intelligent equipment after the closing point to be determined according to a preset rule, wherein the plurality of subsequent positions are in one-to-one correspondence with the plurality of selected historical positions;
obtaining a first mutual position relation among a plurality of historical positions and a second mutual position relation among a plurality of subsequent positions according to a preset mutual position relation matching method;
comparing the similarity of the first mutual position relation and the second mutual position relation;
and judging whether the track of the intelligent equipment is closed at the to-be-determined closing point or not according to the similarity comparison result.
Further, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point, connecting the calculation starting point with the historical positions respectively to form a plurality of historical position vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting the closing point to be determined with the subsequent positions respectively to form a plurality of subsequent position vectors;
and when the conditions meet that the included angle between one subsequent position vector and the first subsequent position vector exceeds a first preset judgment angle, the included angle between one historical position vector and the first historical position vector exceeds the first preset judgment angle or the number of the selected historical positions reaches a first preset number, stopping the selection process of the historical positions.
Further, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point, connecting the calculation starting point with the historical positions respectively to form a plurality of historical position vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting the closing point to be determined with the subsequent positions respectively to form a plurality of subsequent position vectors;
and stopping the selection process of the historical positions when the conditions meet any one of the accumulated values of the included angles between all the subsequent position vectors and the first subsequent position vector, the accumulated values of the included angles between all the historical position vectors and the first historical position vector exceeding a second preset judgment angle or the number of the selected historical positions reaching a first preset number.
Further, the step of obtaining a first mutual position relationship among the plurality of historical positions and a second mutual position relationship among the plurality of subsequent positions according to a preset mutual position relationship matching method includes:
acquiring all the historical position vectors and defining the historical position vectors as a first mutual position relation among a plurality of historical positions; and acquiring all the subsequent position vectors and defining the subsequent position vectors as a second mutual position relation among a plurality of the subsequent positions.
Further, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the starting point is calculated, connecting every two adjacent historical positions to form a plurality of historical interval vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting every two adjacent subsequent positions to form a plurality of subsequent interval vectors;
and when the conditions meet that the included angle between one subsequent interval vector and the first subsequent interval vector exceeds a third preset judgment angle, the included angle between one historical interval vector and the first historical interval vector exceeds the third preset judgment angle or the number of the selected historical positions reaches any one of the first preset number, stopping the selection process of the historical positions.
Further, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the starting point is calculated, connecting every two adjacent historical positions to form a plurality of historical interval vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting every two adjacent subsequent positions to form a plurality of subsequent interval vectors;
and when the conditions meet that the accumulated value of included angles between all adjacent historical interval vectors exceeds a fourth preset judgment angle, the accumulated value of included angles between all adjacent subsequent interval vectors exceeds the fourth preset judgment angle or the number of the selected historical positions reaches any one of a first preset number, stopping the selection process of the historical positions.
Further, the step of obtaining a first mutual position relationship among the plurality of historical positions and a second mutual position relationship among the plurality of subsequent positions according to a preset mutual position relationship matching method includes:
acquiring all the historical interval vectors and defining the historical interval vectors as a first mutual position relation among a plurality of historical positions; all of the subsequent interval vectors are acquired and defined as a second mutual positional relationship between a plurality of the subsequent positions.
The invention also provides a device for executing the track closing judgment method, which comprises the following steps:
the first recording unit is used for acquiring parameters of the intelligent equipment at the position of the current time every preset interval;
the first comparison determination unit is used for determining that the current time position is a to-be-determined closing point of the track of the intelligent equipment and determining that the historical position is a calculation starting point if a distance value between a historical position before the current time and the current time position is smaller than a first determination distance;
the first obtaining unit is used for selecting a plurality of historical positions of the intelligent equipment after the calculation starting point and selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined according to a preset rule;
a second obtaining unit, configured to obtain a first mutual position relationship among the plurality of historical positions and a second mutual position relationship among the plurality of subsequent positions according to a preset mutual position relationship matching method;
a first comparing unit, configured to perform similarity comparison on the first mutual position relationship and the second mutual position relationship;
and the first confirming unit is used for judging whether the track of the intelligent equipment is closed at the point to be closed or not according to the result of the similarity comparison.
The invention also provides computer equipment which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the track closing judgment method when executing the computer program.
The invention also provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the above-mentioned trajectory closure determination method.
The invention provides a track closing judgment method, a track closing judgment device, computer equipment and a storage medium, wherein a to-be-determined closing point is found by judging whether a distance value between a historical position before the current time and the position at the current time is smaller than a first judgment distance or not, a calculation starting point is obtained, the similarity of a first mutual position relation between a plurality of historical positions and a second mutual position relation between a plurality of subsequent positions is compared, and whether the to-be-determined closing point is true or not is verified through a comparison result, so that the track closing is accurately judged, and the condition of misjudgment caused by environment similarity when environmental pictures are compared is avoided.
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Fig. 1 is a schematic flow chart of a trajectory closure determination method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating an application of the trajectory closure determination method according to an embodiment of the present invention;
FIG. 3 is a block diagram of an apparatus for performing a trajectory closure determination method according to an embodiment of the present invention;
fig. 4 is a block diagram schematically illustrating the structure of a computer apparatus according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As used herein, the singular forms "a", "an", "the" and "the" include plural referents unless the content clearly dictates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, units, modules, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, units, modules, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Referring to fig. 1, in an embodiment of the present invention, a trajectory closure determination method applied to a trajectory of an intelligent device includes:
s1, acquiring parameters of the intelligent equipment at the current time position every preset interval;
s2, if the distance value between a historical position before the current time and the position at the current time is smaller than a first judgment distance, judging that the position at the current time is a to-be-determined closing point of the track of the intelligent device, and judging that the historical position is a calculation starting point;
s3, selecting a plurality of historical positions of the intelligent device after the calculation starting point and a plurality of subsequent positions of the intelligent device after the closing point to be determined according to a preset rule, wherein the plurality of subsequent positions are in one-to-one correspondence with the plurality of selected historical positions;
s4, obtaining a first mutual position relation among a plurality of historical positions and a second mutual position relation among a plurality of subsequent positions according to a preset mutual position relation matching method;
s5, comparing the similarity of the first mutual position relation and the second mutual position relation;
and S6, judging whether the track of the intelligent equipment is closed at the point to be closed according to the similarity comparison result.
For some intelligent devices with a walking function, it is necessary to determine whether the track of the intelligent device is closed to guide the intelligent device to perform corresponding operations. In the step S1, in the track of the smart device, every time a preset interval elapses, the parameters of the smart device at the position of the current time are recorded, where the parameters at least include coordinate parameters (specifically, the speed and direction parameters of the smart device may also be included), so that a complete record is formed of the states of the smart device in the track of the whole smart device. The coordinate parameter of the position of the intelligent device at the current time can be realized by a position acquisition unit arranged on the intelligent device, such as data of visual/inertial navigation.
In the step S2, if the distance value between the previous history location and the current location is smaller than the first determination distance, the previous history location is determined as the calculation starting point (the calculation starting point is not necessarily the real starting point of the track of the smart device, and may be the history location of the previous cycle that is calculated by the smart device and is closer to the current location), and the current location is determined as the closing point to be determined of the track of the smart device. And after the undetermined closing point is selected, verifying the authenticity of the closing point in the subsequent step. The determination of the calculation starting point can exclude historical positions which are positioned in a plurality of preset intervals nearest before the current time, and the historical positions which are close to the position of the current time are very easy to meet the determination conditions and are determined as undetermined closing points, and in this case, the undetermined closing points are obviously false. The abnormal judgment of the undetermined closing point can be shielded to a great extent through the steps, so that the calculated amount is reduced.
If the number of preset intervals existing between the to-be-determined closing point and the starting point position of the track of the intelligent equipment is judged to be larger than a certain number; if so, maintaining the position of the current time as the judgment of the undetermined closing point of the track; if not, the position of the current time is judged to be the undetermined closing point of the track, and the track closing judgment method is executed again.
It should be noted that, when the smart device starts to walk, the possibility of finding the true "calculation starting point" is relatively low, but as the walking continues, the smart device gradually approaches the "calculation starting point", that is, the probability of finding the "calculation starting point" is relatively high as the second half is reached, and at this time, if the search for the history point is strengthened and the preliminary search condition (for example, the distance between the gradual search and the determination) is relaxed, it is more beneficial to not omit the true "calculation starting point". Therefore, before step S2, a first determination distance may be preferably obtained to make a determination or search for a history position. Here, a real-time decision distance is first constructed, which increases with time: dTWherein D isTAnd (a + bT), where a is a distance base and is expressed in unit of length, b is a distance increment coefficient and is expressed in unit of length/time, and T is a current running time in the edgewise walking process and is expressed in unit of time, and the real-time judgment distance may be used as the first judgment distance. Meanwhile, in consideration of the fact that the judgment distance is not infinitely enlarged, it is appropriate to control the judgment distance to an appropriate range, and therefore, a limit distance Dc is set here. In specific application, preferably, the real-time judgment distance D is takenTThe smaller value from Dc is the last first decision distance.
In the step of S3, a plurality of historical positions of the smart device after the calculation starting point and a plurality of subsequent positions of the smart device after the pending closing point are selected according to a preset rule, so as to obtain a historical position verification group and a subsequent position verification group, where the selection of the subsequent position verification group and the historical position verification group form a one-to-one correspondence. It should be noted that the selected plurality of historical positions and the plurality of subsequent positions are not necessarily continuous, and may also be jumping (e.g., separated by a plurality of preset intervals). In this embodiment, 60 historical positions after the calculation starting point are sequentially selected as a historical position verification group, and then a subsequent position verification group consisting of 60 subsequent positions is correspondingly selected and taken out after the undetermined closing point by using the historical position verification group as a reference. In subsequent steps, a first mutual positional relationship of the historical location validation set and a second mutual positional relationship of the subsequent location validation set are obtained and compared.
In the above-described steps of S4-S6, it is verified whether the closing point to be determined is true by the result of the similarity of the first mutual positional relationship formed between all the history positions in the history position verification group and the second mutual positional relationship formed between all the subsequent positions in the subsequent position verification group. The closer the mutual position relations among all the historical positions in the historical position verification group and the mutual position relations among all the subsequent positions in the subsequent position verification group are, the closer the first section of track trend corresponding to the historical position verification group and the second section of track trend corresponding to the subsequent position verification group are, and the closer the tracks can be judged to be closed. The first mutual position relationship reflects a trend formed by all historical positions in the historical position verification group, and the second mutual position relationship reflects a trend formed by all subsequent positions in the subsequent position verification group. For example, a vector can be formed by connecting two historical positions, and the length and direction of the vector reflect the mutual position relationship between the two historical positions, so that a first mutual position relationship (a first group of vectors) between all historical positions can be obtained in the same manner; similarly, a second mutual position relation (a second group of vectors) among all subsequent positions can be obtained in the vector mode; and comparing the data of the first group of vectors with the data of the second group of vectors to obtain a similarity comparison result.
In the scheme, the comparison and judgment are performed by adopting the first mutual position relation and the second mutual position relation, which can be the comparison and judgment among a plurality of vectors, and compared with a mode of judging whether the track is overlapped by calculating the distance/relative position difference between the historical position point and the subsequent position point, the scheme has better track fault tolerance rate (for example, when the intelligent equipment is likely to have larger deviation on the walking track due to slipping/environmental interference and the like, the distance between the position points can generate great difference, but the approximate tracks of the two-time running of the machine still have similarity, so that the scheme still can continuously judge whether a closed loop is really formed, namely the scheme has larger offset tolerance), and the comparison and judgment of the position points are more suitable for machine products with higher precision.
In summary, in the step of S2, a pending closing point is found, and from this point, the historical location verification set and the subsequent location verification set are obtained in sequence in the above manner, and the correctness of the determination of the pending closing point can be verified through the steps of S4-S6.
It should be noted that, when the trajectory of the smart device forms a loop, but the trajectories calculated by the smart device do not overlap (even two trajectories with a large distance are formed), only two trajectories with similar trends (parallel or spiral, etc.) are formed, and if the value of the first determination distance is small at this time, it is not possible to find a to-be-determined closing point in the step S2. At this time, although the value of the first determination distance is increased, it is likely to cause erroneous determination, it can be determined whether or not the track is closed by the steps of S4 to S6. Specifically, in the prior art, whether the current position of the smart device coincides with the starting point position of the trajectory of the smart device is generally compared in real time, the search range is generally between 5cm and 10cm, the first determination distance set in the embodiment may be larger than the conventional search range (for example, the first determination distance is 100cm to 200cm), and the probability of finding the undetermined closing point is greatly improved. And in step S2, not only the position of the current time and the position of the start point of the trajectory of the smart device (i.e., the calculation start point) are determined, but also the distances between the position of the current time and all historical positions can be compared and determined, so that the probability of finding the undetermined closing point can also be increased.
In summary, the track closing judgment method of the present invention determines whether the real-time distance is smaller than the first judgment distance to find the to-be-determined closing point, and verifies whether the to-be-determined closing point is true by the similarity result of the first mutual position relationship between all the historical positions in the historical position verification group and the second mutual position relationship between all the subsequent positions in the subsequent position verification group, so as to accurately judge whether the track is closed, and avoid the situation of misjudgment due to similar environments when comparing the environment images. The scheme realizes searching and confirming of the closing point, does not cause overlarge data processing amount due to calculation of a large number of pictures, and has more accurate result. In one embodiment, the preset interval is a distance interval or a time interval.
In implementation, when the distance interval is taken as a preset interval, the point group formed by the coordinates of the intelligent device at the position where the current time is recorded is very uniform. The distance interval may be represented by the number of turns the wheel of the smart device turns. When the time interval is a preset interval, the method is beneficial to the coordinate extraction of the intelligent device in a complex area. Because the movement of the intelligent device in the complex area has more turning or collision, the time consumption is more, and a plurality of coordinates can be extracted from the complex area by taking the time interval as the preset interval.
It is worth mentioning that the first mutual positional relationship and the second mutual positional relationship may be a history vector relationship between a plurality of history positions and a subsequent vector relationship between a plurality of subsequent positions, respectively.
In the step of selecting a plurality of historical positions and subsequent positions according to a preset rule, the preset rule may be set based on at least one or any combination of a historical vector relationship rule, a subsequent vector relationship rule, and a quantity rule.
As an example, assume the quantity rule is: presetting 60 number of position points; the historical vector relationship rule is: setting included angles among the plurality of historical vectors to reach a first preset value; the subsequent vector relationship rule is: and setting the included angle between a plurality of subsequent vectors to reach a first preset value. Then, after obtaining the calculation starting point or the undetermined closing point, sequentially selecting the position points, wherein in the process, any one/combination of the following conditions can be regarded as a 'preset rule': (1) sequentially obtaining a plurality of historical positions until the number of the historical positions is 60; (2) or sequentially obtaining the subsequent positions until the number is 60; (3) the included angle among the plurality of historical vectors reaches a first preset value; (4) the included angle between a plurality of subsequent vectors reaches a first preset value. A plurality of cases will be individually exemplified below.
In one embodiment, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
sequentially selecting a first preset number of historical positions of the intelligent equipment after the calculation starting point;
and sequentially selecting a first preset number of subsequent positions of the intelligent equipment behind the to-be-determined closing point corresponding to the historical positions.
The first preset number of historical positions are sequentially obtained after the starting point is calculated, so that the method for obtaining the historical position verification group is simple and direct and is convenient to execute. The first predetermined number of historical locations should be sufficient to characterize the trajectory of the segment of smart device.
Referring to fig. 2, in an embodiment, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point, connecting the calculation starting point with the historical positions respectively to form a plurality of historical position vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting the closing point to be determined with the subsequent positions respectively to form a plurality of subsequent position vectors;
and when the conditions meet that the included angle between one subsequent position vector and the first subsequent position vector exceeds a first preset judgment angle, the included angle between one historical position vector and the first historical position vector exceeds the first preset judgment angle or the number of the selected historical positions reaches a first preset number, stopping the selection process of the historical positions.
If the historical position verification group is obtained in a manner that the historical positions are sequentially obtained in the first preset number after the starting point is calculated, although the calculation is simple, the problem of redundancy exists, for example, in order to accurately judge the authenticity of the to-be-determined closing point, the value of the first preset number is selected to be large. In this embodiment, in the process of selecting the plurality of historical positions and the plurality of subsequent positions, the calculation starting point is connected with the historical positions to form a plurality of historical position vectors, the to-be-determined closing point is connected with the plurality of subsequent positions to form a plurality of subsequent position vectors, and when an included angle between one of the subsequent position vectors and the first subsequent position vector and/or an included angle between one of the historical position vectors and the first historical position vector exceeds a first preset determination angle, the track is determined to be complex, that is, the environment is characterized to be complex enough (for example, the environment may pass through a corner turn), and the track is enough to be used as a determination basis, so that the process of selecting the plurality of historical positions and the plurality of subsequent positions is ended in advance. Therefore, the true and false of the closing point to be determined is accurately judged, and the calculated amount of the intelligent equipment can be reduced. In fig. 2, the track of the smart device presents a curved curve from inside to outside, a trend similar to the initial section of the track is formed at the end section of the track (the historical position vector and the subsequent position vector are indicated in the figure by an acquisition method), and the similar trend can be identified by the method, so that the track closure is judged. Specifically, if the representations of the historical location verification group and the subsequent location verification group both pass through a complex environment (such as a corner), the number of location data that need to satisfy the "comparison requirement between the first mutual location relationship and the second mutual location relationship" in the historical location verification group and the subsequent location verification group may be relatively small, because if certain similar movement tracks/track trends exist in the complex environment, the probability that the "track closing has been completed and the process is proceeding along the historical track" is high, and the comparison of multiple sets of locations is not needed. In this embodiment, if the vector angle and the accumulation exceed the second preset determination angle and the selection process of the plurality of historical positions and the plurality of subsequent positions is ended in advance (for example, at this time, 30 sets of data are obtained), then the "comparison requirement between the requirements of the first mutual position relationship and the second mutual position relationship" can be achieved based on the 30 sets of data. It should be noted that, if the included angle cannot reach the first preset determination angle (the trajectory is gentle), the selection process of the historical positions is also stopped after the number of the selected historical positions reaches the first preset number. The first preset number can also meet the comparison requirement between the requirements of the first mutual position relation and the second mutual position relation on the historical position vectors and the subsequent position vectors, meanwhile, excessive selection of the historical positions is avoided, and the calculation amount is reduced.
In one embodiment, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point, connecting the calculation starting point with the historical positions respectively to form a plurality of historical position vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting the closing point to be determined with the subsequent positions respectively to form a plurality of subsequent position vectors;
and stopping the selection process of the historical positions when the conditions meet any one of the accumulated values of the included angles between all the subsequent position vectors and the first subsequent position vector, the accumulated values of the included angles between all the historical position vectors and the first historical position vector exceeding a second preset judgment angle or the number of the selected historical positions reaching a first preset number.
It should be noted that "all subsequent position vectors" refers to all subsequent vectors that have been/can be formed at present. Similarly, "all historical location vectors" refers to all historical vectors that have/can be formed at the present time. Hereinafter, all 'vectors' refer to: by requirement, all vectors that have/can be formed theoretically. The explanation is not repeated hereinafter.
In this embodiment, in the process of selecting a plurality of historical positions and a plurality of subsequent positions, the calculation starting point is connected with the historical positions to form a plurality of historical position vectors, the to-be-determined closing point is connected with the plurality of subsequent positions to form a plurality of vectors, and when the accumulated value of included angles between all vectors and the first vector and/or the accumulated value of included angles between all vectors and the first historical position vector exceed the second preset determination angle, the accumulated degree of the complexity of the track section is determined to be sufficient as a determination basis, so that the process of selecting the plurality of historical positions and the plurality of subsequent positions is ended in advance. Therefore, the true and false of the closing point to be determined is accurately judged, and the calculated amount of the intelligent equipment can be reduced. Through the selection rules of the plurality of historical positions and the plurality of subsequent positions, the track characteristics of the intelligent equipment with smoother track can be well identified. It should be noted that, if the accumulated value of the included angle cannot exceed the second preset determination angle (the track is gentle) all the time, the selection process of the historical positions is also stopped after the number of the selected historical positions reaches the first preset number. The first preset number can also meet the comparison requirement between the requirements of the first mutual position relation and the second mutual position relation on the historical position vectors and the subsequent position vectors, meanwhile, excessive selection of the historical positions is avoided, and the calculation amount is reduced.
In an embodiment, the step of obtaining a first mutual position relationship among a plurality of the historical positions and a second mutual position relationship among a plurality of the subsequent positions according to a preset mutual position relationship matching method includes:
acquiring all the historical position vectors and defining the historical position vectors as a first mutual position relation among a plurality of historical positions; and acquiring all the subsequent position vectors and defining the subsequent position vectors as a second mutual position relation among a plurality of the subsequent positions.
All the historical position vectors form a first mutual position relation, all the subsequent position vectors form a second mutual position relation, and the subsequent positions and the historical positions are in one-to-one correspondence, so that the subsequent position vectors and the historical position vectors are in one-to-one correspondence. Since the vectors include length and direction, then the entire historical position vector can represent the positional relationship between all of the historical positions in the historical position validation set, and the entire subsequent position vector can represent the positional relationship between all of the subsequent positions in the subsequent position validation set. In the subsequent step, the similarity comparison between the first mutual position relationship and the second mutual position relationship is performed, that is, the angle and/or length between the corresponding historical position vector and the vector is compared.
In one embodiment, the step of similarity comparing the first mutual positional relationship with the second mutual positional relationship comprises:
calculating an angular difference and/or a length difference between the subsequent position vector and the historical position vector corresponding to each group, one subsequent position vector and one historical position vector corresponding to each group being combined into one group.
And in the subsequent steps, comparing the value of each angle difference and/or the value of each length difference with a first preset judgment range, so that whether the track of the intelligent equipment is closed at the to-be-closed point or not can be judged. The first preset judgment range is an angle and/or length standard value. As long as the value and/or the length difference of the angle difference between a preset number of sets of subsequent position vectors and the historical position vector falls within a first preset determination range, the "first mutual position relationship is considered to be similar to the" second mutual position relationship ".
In one embodiment, the step of similarity comparing the first mutual positional relationship with the second mutual positional relationship comprises:
and calculating the angle difference between the subsequent position vector and the historical position vector corresponding to each group, acquiring a cumulative angle value and/or a length difference, and acquiring a cumulative length value, wherein one subsequent position vector and one historical position vector corresponding to each group are combined into one group.
And calculating the angle difference between the subsequent position vector and the historical position vector corresponding to each group, and acquiring a cumulative angle value and/or a length difference and acquiring a cumulative length value.
And in the subsequent step, comparing the accumulated angle value and/or the accumulated length value with a second preset judgment range, so that whether the track of the intelligent equipment is closed at the point to be closed can be judged. The second preset decision range is an angle and/or length criterion value. The second predetermined determination range may be a calculation value obtained by multiplying the first predetermined determination range by the magnitude of the subsequent position vector. In the step, the accumulated values are compared, so that the interference of a few abnormal points on the final judgment result is avoided.
In one embodiment, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the starting point is calculated, connecting every two adjacent historical positions to form a plurality of historical interval vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting every two adjacent subsequent positions to form a plurality of subsequent interval vectors;
and when the conditions meet that the included angle between one subsequent interval vector and the first subsequent interval vector exceeds a third preset judgment angle, the included angle between one historical interval vector and the first historical interval vector exceeds the third preset judgment angle or the number of the selected historical positions reaches any one of the first preset number, stopping the selection process of the historical positions.
In this embodiment, in the process of selecting the plurality of historical positions and the plurality of subsequent positions, each pair of two adjacent historical positions are connected to form a plurality of historical interval vectors, each pair of two adjacent subsequent positions are connected to form a plurality of subsequent interval vectors, and when an included angle between one subsequent position vector and the first subsequent position vector exceeds a third preset determination angle and/or an included angle between one historical position vector and the first historical position vector exceeds the third preset determination angle, the track corresponding to the historical position verification group is determined to be complex, that is, the environment is characterized to be sufficiently complex (for example, the environment may pass through a corner turn), and the track is sufficiently used as a determination basis, so that the process of selecting the plurality of historical positions and the plurality of subsequent positions is ended in advance. It should be noted that, if the angle always exceeds the third preset determination angle (the trajectory is gentle), the selection process of the historical positions is also stopped after the number of the selected historical positions reaches the first preset number. The first preset number of historical interval vectors and subsequent interval vectors can also meet the comparison requirement between the requirements of the first mutual position relationship and the second mutual position relationship, meanwhile, excessive selection of historical positions is avoided, and the calculation amount is reduced.
In one embodiment, the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule includes:
selecting a plurality of historical positions of the intelligent equipment after the starting point is calculated, connecting every two adjacent historical positions to form a plurality of historical interval vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting every two adjacent subsequent positions to form a plurality of subsequent interval vectors;
and when the conditions meet that the accumulated value of included angles between all adjacent historical interval vectors exceeds a fourth preset judgment angle, the accumulated value of included angles between all adjacent subsequent interval vectors exceeds the fourth preset judgment angle or the number of the selected historical positions reaches any one of a first preset number, stopping the selection process of the historical positions.
In this embodiment, in the process of selecting a plurality of historical positions and a plurality of subsequent positions, each pair of two adjacent historical positions are connected to form a plurality of historical interval vectors, each pair of two adjacent subsequent positions are connected to form a plurality of interval vectors, and when the cumulative value of included angles between all adjacent historical interval vectors exceeds a fourth preset determination angle and/or the cumulative value of included angles between all adjacent interval vectors exceeds a fourth preset determination angle, the track corresponding to the historical position verification group is determined to be complex and sufficient as a determination basis, so that the process of selecting a plurality of historical positions and a plurality of subsequent positions is ended in advance. Through the selection rules of the plurality of historical positions and the plurality of subsequent positions, the track characteristics of the intelligent equipment can be well identified. For example, the accumulated values of the included angles between all the interval vectors and the first interval vector and the accumulated values of the included angles between all the historical interval vectors and the first historical interval vector can accurately represent the situation that a certain section of track of the intelligent device does not have large steering (such as wave shape). Then the position data of the track of the intelligent device can meet the comparison requirement between the requirements of the first mutual position relation and the second mutual position relation. It should be noted that, if the accumulated value of the included angle cannot exceed the fourth preset determination angle (the track is gentle) all the time, the selection process of the historical positions is also stopped after the number of the selected historical positions reaches the first preset number. The first preset number of historical interval vectors and subsequent interval vectors can also meet the comparison requirement between the requirements of the first mutual position relationship and the second mutual position relationship, meanwhile, excessive selection of historical positions is avoided, and the calculation amount is reduced.
In an embodiment, the step of obtaining a first mutual position relationship among a plurality of the historical positions and a second mutual position relationship among a plurality of the subsequent positions according to a preset mutual position relationship matching method includes:
acquiring all the historical interval vectors and defining the historical interval vectors as a first mutual position relation among a plurality of historical positions; all of the subsequent interval vectors are acquired and defined as a second mutual positional relationship between a plurality of the subsequent positions.
All the historical interval vectors form a first mutual position relation, all the subsequent interval vectors form a second mutual position relation, and the subsequent interval vectors and the historical interval vectors are in one-to-one correspondence because the subsequent positions and the historical positions are in one-to-one correspondence. And comparing the similarity of the first mutual position relation and the second mutual position relation, namely comparing the angle and/or the length between the corresponding historical interval vector and the subsequent interval vector.
Embodiments of the first and second mutual positional relationships are characterized with respect to using the historical position vector and the subsequent position vector, respectively. In this embodiment, taking the historical interval vector as an example, the historical interval vector does not relate to the calculation starting point, but includes parameters of two adjacent historical position points, so that the historical interval vector can represent the trend of the track corresponding to the historical position verification group, and similarity comparison can be performed conveniently; and history positions are connected to the calculation starting point relative to the history position vector, and the history interval history is obtained between the adjacent history positions, so that the accumulation of errors can be avoided.
Referring to fig. 3, the present invention further provides a device for executing a trajectory closure determination method, including:
the first recording unit 10 is configured to obtain parameters of the intelligent device at a current time position every time a preset interval elapses;
a first comparison determining unit 20, if a distance value between a historical position before the current time and the position at the current time is smaller than a first determination distance, the first comparison determining unit 20 determines that the position at the current time is a to-be-determined closing point of the track of the intelligent device, and determines that the historical position is a calculation starting point;
a first obtaining unit 30, configured to select, according to a preset rule, a plurality of historical positions of the smart device after the calculation starting point and a plurality of subsequent positions of the smart device after the closing point to be determined;
a second obtaining unit 40, configured to obtain a first mutual position relationship among the multiple historical positions and a second mutual position relationship among the multiple subsequent positions according to a preset mutual position relationship matching method;
a first comparing unit 50 for performing similarity comparison on the first mutual positional relationship and the second mutual positional relationship;
and a first determining unit 60, configured to determine whether the trajectory of the smart device is closed at the to-be-closed point according to the result of the similarity comparison.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the first obtaining unit 30 includes:
a third obtaining unit, configured to sequentially select a first preset number of historical positions of the intelligent device after the calculation starting point;
and the fourth obtaining unit is used for sequentially selecting a first preset number of subsequent positions of the intelligent equipment behind the to-be-determined closing point corresponding to the historical positions.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the first obtaining unit 30 includes:
a fifth obtaining unit, configured to select multiple historical positions of the intelligent device after the calculation starting point, connect the calculation starting point with the historical positions to form multiple historical position vectors, select multiple subsequent positions of the intelligent device after the closing point to be determined, and connect the closing point to be determined with the multiple subsequent positions to form multiple subsequent position vectors;
and the sixth obtaining unit is used for stopping the selection process of the historical positions when the conditions meet that the included angle between one subsequent position vector and the first subsequent position vector exceeds a first preset judgment angle, the included angle between one historical position vector and the first historical position vector exceeds the first preset judgment angle or the number of the selected historical positions reaches any one of a first preset number.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the first obtaining unit 30 includes:
a seventh obtaining unit, configured to select multiple historical positions of the intelligent device after the calculation starting point, connect the calculation starting point with the historical positions to form multiple historical position vectors, select multiple subsequent positions of the intelligent device after the closing point to be determined, and connect the closing point to be determined with the multiple subsequent positions to form multiple subsequent position vectors;
and the eighth obtaining unit is used for stopping the selection process of the historical positions when the conditions meet any one of the accumulated values of the included angles of all the subsequent position vectors and the first subsequent position vector, the accumulated values of the included angles of all the historical position vectors and the first historical position vector exceed a second preset judgment angle or the number of the selected historical positions reaches a first preset number.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the second obtaining unit 40 includes:
a ninth acquisition unit configured to acquire all the history interval vectors and define as a first mutual positional relationship among a plurality of the history positions; all of the subsequent interval vectors are acquired and defined as a second mutual positional relationship between a plurality of the subsequent positions.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the first comparing unit 50 includes:
a second comparing unit, configured to calculate an angle difference and/or a length difference between the subsequent position vector and the historical position vector corresponding to each group, where one subsequent position vector and one historical position vector corresponding to each group are combined into one group.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the first comparing unit 50 includes:
and the third comparison unit is used for calculating the angle difference between the subsequent position vector and the historical position vector corresponding to each group, acquiring an accumulated angle value and/or length difference and acquiring an accumulated length value, and combining one subsequent position vector and one corresponding historical position vector into one group.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the first obtaining unit 30 includes:
a tenth obtaining unit, configured to select multiple history positions of the intelligent device after the calculation starting point and connect each pair of two adjacent history positions to form multiple history interval vectors, and select multiple subsequent positions of the intelligent device after the closing point to be determined and connect each pair of two adjacent subsequent positions to form multiple subsequent interval vectors;
and the eleventh obtaining unit is used for stopping the selection process of the historical positions when the condition meets that the included angle between one subsequent interval vector and the first subsequent interval vector exceeds a third preset judgment angle, the included angle between one historical interval vector and the first historical interval vector exceeds the third preset judgment angle or the selected number of the historical positions reaches any one of the first preset number.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the first obtaining unit 30 includes:
a twelfth obtaining unit, configured to select multiple history positions of the intelligent device after the calculation starting point and connect each pair of two adjacent history positions to form multiple history interval vectors, and select multiple subsequent positions of the intelligent device after the closing point to be determined and connect each pair of two adjacent subsequent positions to form multiple subsequent interval vectors;
and the thirteenth acquisition unit is used for stopping the selection process of the historical positions when the conditions meet that the accumulated value of the included angles between all adjacent historical interval vectors exceeds a fourth preset judgment angle, the accumulated value of the included angles between all adjacent subsequent interval vectors exceeds the fourth preset judgment angle or the number of the selected historical positions reaches any one of a first preset number.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
In one embodiment, the second obtaining unit 40 includes:
a fourteenth obtaining unit configured to obtain all the history interval vectors and define as a first mutual positional relationship among a plurality of the history positions; all of the subsequent interval vectors are acquired and defined as a second mutual positional relationship between a plurality of the subsequent positions.
In this embodiment, please refer to the corresponding method embodiments for the specific implementation of each unit, which will not be described herein again.
Referring to fig. 4, the present invention further provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the trajectory closure determination method when executing the computer program.
The invention also provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the above-mentioned trajectory closure determination method.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by hardware associated with instructions of a computer program, which may be stored on a non-volatile computer-readable storage medium, and when executed, may include processes of the above embodiments of the methods. Any reference to memory, storage, database, or other medium provided herein and used in the examples may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), RambuS (RambuS) direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the present invention relates to a trajectory closure determination method, apparatus, computer device, and storage medium, wherein a to-be-determined closing point is found by determining whether a distance value between a historical position before a current time and a position at the current time is smaller than a first determination distance, and a calculation starting point is obtained therefrom, and a comparison is performed between a first mutual position relationship between a plurality of historical positions and a second mutual position relationship between a plurality of subsequent positions, so as to verify whether the to-be-determined closing point is true through a comparison result, thereby accurately determining whether the trajectory is closed, and avoiding a misjudgment situation due to similarity of environments when comparing environmental images.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. A track closing judgment method is applied to intelligent equipment and is characterized by comprising the following steps:
acquiring parameters of the intelligent equipment at the position of the current time every preset interval;
if the distance value between a historical position before the current time and the position at the current time is smaller than a first judgment distance, judging that the position at the current time is a to-be-determined closing point of the track of the intelligent equipment, and judging that the historical position is a calculation starting point;
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point and a plurality of subsequent positions of the intelligent equipment after the closing point to be determined according to a preset rule, wherein the plurality of subsequent positions are in one-to-one correspondence with the plurality of selected historical positions;
obtaining a first mutual position relation among a plurality of historical positions and a second mutual position relation among a plurality of subsequent positions according to a preset mutual position relation matching method;
comparing the similarity of the first mutual position relation and the second mutual position relation;
and judging whether the track of the intelligent equipment is closed at the to-be-determined closing point or not according to the similarity comparison result.
2. The trajectory closure determination method according to claim 1, wherein the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule comprises:
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point, connecting the calculation starting point with the historical positions respectively to form a plurality of historical position vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting the closing point to be determined with the subsequent positions respectively to form a plurality of subsequent position vectors;
and when the conditions meet that the included angle between one subsequent position vector and the first subsequent position vector exceeds a first preset judgment angle, the included angle between one historical position vector and the first historical position vector exceeds the first preset judgment angle or the number of the selected historical positions reaches a first preset number, stopping the selection process of the historical positions.
3. The trajectory closure determination method according to claim 1, wherein the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule comprises:
selecting a plurality of historical positions of the intelligent equipment after the calculation starting point, connecting the calculation starting point with the historical positions respectively to form a plurality of historical position vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting the closing point to be determined with the subsequent positions respectively to form a plurality of subsequent position vectors;
and stopping the selection process of the historical positions when the conditions meet any one of the accumulated values of the included angles between all the subsequent position vectors and the first subsequent position vector, the accumulated values of the included angles between all the historical position vectors and the first historical position vector exceeding a second preset judgment angle or the number of the selected historical positions reaching a first preset number.
4. The trajectory closure determination method according to any one of claims 2 to 3, wherein the step of obtaining a first mutual positional relationship between a plurality of the historical positions and a second mutual positional relationship between a plurality of the subsequent positions according to a preset positional relationship mutual matching method includes:
acquiring all the historical position vectors and defining the historical position vectors as a first mutual position relation among a plurality of historical positions; and acquiring all the subsequent position vectors and defining the subsequent position vectors as a second mutual position relation among a plurality of the subsequent positions.
5. The trajectory closure determination method according to claim 1, wherein the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule comprises:
selecting a plurality of historical positions of the intelligent equipment after the starting point is calculated, connecting every two adjacent historical positions to form a plurality of historical interval vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting every two adjacent subsequent positions to form a plurality of subsequent interval vectors;
and when the conditions meet that the included angle between one subsequent interval vector and the first subsequent interval vector exceeds a third preset judgment angle, the included angle between one historical interval vector and the first historical interval vector exceeds the third preset judgment angle or the number of the selected historical positions reaches any one of the first preset number, stopping the selection process of the historical positions.
6. The trajectory closure determination method according to claim 1, wherein the step of selecting a plurality of historical positions of the smart device after the calculation starting point and selecting a plurality of subsequent positions of the smart device after the closing point to be determined according to a preset rule comprises:
selecting a plurality of historical positions of the intelligent equipment after the starting point is calculated, connecting every two adjacent historical positions to form a plurality of historical interval vectors, selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined, and connecting every two adjacent subsequent positions to form a plurality of subsequent interval vectors;
and when the conditions meet that the accumulated value of included angles between all adjacent historical interval vectors exceeds a fourth preset judgment angle, the accumulated value of included angles between all adjacent subsequent interval vectors exceeds the fourth preset judgment angle or the number of the selected historical positions reaches any one of a first preset number, stopping the selection process of the historical positions.
7. The trajectory closure determination method according to any one of claims 5 to 6, wherein the step of obtaining a first mutual positional relationship between a plurality of the historical positions and a second mutual positional relationship between a plurality of the subsequent positions according to a preset positional relationship mutual matching method includes:
acquiring all the historical interval vectors and defining the historical interval vectors as a first mutual position relation among a plurality of historical positions; all of the subsequent interval vectors are acquired and defined as a second mutual positional relationship between a plurality of the subsequent positions.
8. An apparatus for performing a trajectory closure determination method, comprising:
the first recording unit is used for acquiring parameters of the intelligent equipment at the position of the current time every preset interval;
the first comparison determination unit is used for determining that the current time position is a to-be-determined closing point of the track of the intelligent equipment and determining that the historical position is a calculation starting point if a distance value between a historical position before the current time and the current time position is smaller than a first determination distance;
the first obtaining unit is used for selecting a plurality of historical positions of the intelligent equipment after the calculation starting point and selecting a plurality of subsequent positions of the intelligent equipment after the closing point to be determined according to a preset rule;
a second obtaining unit, configured to obtain a first mutual position relationship among the plurality of historical positions and a second mutual position relationship among the plurality of subsequent positions according to a preset mutual position relationship matching method;
a first comparing unit, configured to perform similarity comparison on the first mutual position relationship and the second mutual position relationship;
and the first confirming unit is used for judging whether the track of the intelligent equipment is closed at the point to be closed or not according to the result of the similarity comparison.
9. A computer device comprising a memory and a processor, the memory having stored therein a computer program, wherein the processor when executing the computer program implements the steps of the trajectory closure determination method according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the trajectory closure determination method according to one of claims 1 to 7.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115480275A (en) * 2022-09-15 2022-12-16 中华人民共和国广东海事局 Motion state acquisition method and device, computer equipment and storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109394095A (en) * 2018-10-23 2019-03-01 珠海市微半导体有限公司 A kind of control method, chip and the clean robot of the offset of robot motion's carpet
CN111152266A (en) * 2020-01-09 2020-05-15 安徽宇润道路保洁服务有限公司 Control method and system of cleaning robot
CN111178315A (en) * 2020-01-03 2020-05-19 深圳市无限动力发展有限公司 Method and device for identifying corner and computer equipment
CN111580525A (en) * 2020-05-26 2020-08-25 珠海市一微半导体有限公司 Judgment method for returning to starting point in edgewise walking, chip and visual robot
CN112056993A (en) * 2020-09-07 2020-12-11 上海高仙自动化科技发展有限公司 Cleaning method, cleaning device, electronic equipment and computer-readable storage medium

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109394095A (en) * 2018-10-23 2019-03-01 珠海市微半导体有限公司 A kind of control method, chip and the clean robot of the offset of robot motion's carpet
CN111178315A (en) * 2020-01-03 2020-05-19 深圳市无限动力发展有限公司 Method and device for identifying corner and computer equipment
CN111152266A (en) * 2020-01-09 2020-05-15 安徽宇润道路保洁服务有限公司 Control method and system of cleaning robot
CN111580525A (en) * 2020-05-26 2020-08-25 珠海市一微半导体有限公司 Judgment method for returning to starting point in edgewise walking, chip and visual robot
CN112056993A (en) * 2020-09-07 2020-12-11 上海高仙自动化科技发展有限公司 Cleaning method, cleaning device, electronic equipment and computer-readable storage medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115480275A (en) * 2022-09-15 2022-12-16 中华人民共和国广东海事局 Motion state acquisition method and device, computer equipment and storage medium
CN115480275B (en) * 2022-09-15 2023-08-08 中华人民共和国广东海事局 Motion state acquisition method and device, computer equipment and storage medium

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