CN111796586B

CN111796586B - Local path planning method and device for intelligent mobile equipment

Info

Publication number: CN111796586B
Application number: CN201910208668.8A
Authority: CN
Inventors: 栾成志
Original assignee: Beijing Qihoo Technology Co Ltd
Current assignee: Beijing Qihoo Technology Co Ltd
Priority date: 2019-03-19
Filing date: 2019-03-19
Publication date: 2024-08-27
Anticipated expiration: 2039-03-19
Also published as: CN111796586A

Abstract

The invention discloses a local path planning method and device of intelligent mobile equipment. According to the local path planning method of the intelligent mobile equipment, the tracking object is determined, the target point is determined according to the current position of the tracking object, the path from the current position of the intelligent mobile equipment to the target point is planned to be used as the global path, and the tracking object is tracked. And selecting one track line from a preset track line set as a local path according to the current speed and the global path of the intelligent mobile equipment. Before tracking is started, the travelling direction of the intelligent mobile equipment is determined, so that the intelligent mobile equipment has a travelling basis, and the problem that the tracking object moves too fast to cause loss is avoided. Moreover, the local path can realize accurate control on the movement of the intelligent mobile equipment, so that the advancing precision of the intelligent mobile equipment is improved, and the advancing efficiency can be improved to a certain extent.

Description

Local path planning method and device for intelligent mobile equipment

Technical Field

The invention relates to the field of intelligent mobile equipment control, in particular to a local path planning method and device for intelligent mobile equipment.

Background

In the prior art, intelligent mobile devices, such as sweeping robots, generally travel according to a planned path and can only travel in a single movement mode. In this way, the movement efficiency of the intelligent mobile device is affected to some extent. Moreover, in complex situations, a single movement pattern tends to deviate the smart mobile device from the planned path, so that the smart mobile device cannot move to the target point. Moreover, the movement of the intelligent mobile equipment is not regulated in the moving process, so that the control precision of the intelligent mobile equipment is also affected, and the intelligent mobile equipment cannot work accurately. Accordingly, a corresponding solution is needed.

Disclosure of Invention

The present invention has been made in view of the above problems, and it is an object of the present invention to provide a method and apparatus for local path planning for an intelligent mobile device that overcomes or at least partially solves the above problems.

According to one aspect of the present invention, there is provided a local path planning method for an intelligent mobile device, including:

determining a tracking object;

Determining a target point according to the current position of the tracking object, planning a path from the current position of the intelligent mobile equipment to the target point as a global path, and tracking the tracking object;

and selecting one track line from a preset track line set as a local path according to the current speed of the intelligent mobile equipment and the global path.

Optionally, the determining the tracking object includes:

And detecting through a depth camera and/or a laser radar, and determining the detected object which accords with the preset characteristic as a tracking object.

Optionally, the planning a path from the current location of the smart mobile device to the target point comprises:

Searching a track line reaching the target point from the current position of the intelligent mobile device based on an A-algorithm.

Optionally, the method further comprises:

Setting a plurality of sampling speeds according to parameters of the intelligent mobile equipment;

and respectively generating the track lines of the intelligent mobile equipment at each sampling speed, and putting the track lines into the preset track line set.

Optionally, the selecting one track line from the preset track line set as the local path includes:

For each track line in a preset track line set, calculating an evaluation value related to the current speed and the global path according to a preset evaluation function;

and selecting the track line with the optimal evaluation value as the local path.

Optionally, the calculating, for each track line in the preset track line set, an evaluation value related to the current speed and the global path according to a preset evaluation function includes:

And according to the preset evaluation function, evaluating values are obtained according to the deviation of the sampling speed corresponding to each track line and the current speed, the angle deviation of each track line and the global path and the position deviation of each track line and the global path.

Optionally, the method further comprises:

Detecting an obstacle in the tracking process;

When an obstacle is detected, the local path is adjusted according to the detected obstacle position.

Optionally, the intelligent mobile device is a sweeping robot, and the tracking object is a human body.

According to another aspect of the present invention, there is provided a local path planning apparatus for an intelligent mobile device, including:

a determination unit adapted to determine a tracked object;

The global path unit is suitable for determining a target point according to the current position of the tracking object, planning a path from the current position of the intelligent mobile equipment to the target point as a global path, and tracking the tracking object;

And the local path unit is suitable for selecting one path line from a preset path line set as a local path according to the current speed of the intelligent mobile equipment and the global path.

Optionally, the determining unit is adapted to detect by means of a depth camera and/or a lidar, and determine the detected object according to the preset feature as the tracking object.

Optionally, the global path unit is adapted to search for a trajectory from the current location of the smart mobile device to the target point based on an a-algorithm.

Optionally, the apparatus further comprises:

the track line unit is suitable for setting a plurality of sampling speeds according to the parameters of the intelligent mobile equipment;

Optionally, the local path unit is adapted to calculate, for each track line in a preset track line set, an evaluation value related to the current speed and the global path according to a preset evaluation function;

Optionally, the local path unit is further adapted to calculate, according to the preset evaluation function, an evaluation value according to a deviation of the sampling speed corresponding to each trace line from the current speed, an angular deviation of each trace line from the global path, and a positional deviation of each trace line from the global path.

Optionally, the apparatus further comprises:

An obstacle unit adapted to perform obstacle detection during tracking;

According to still another aspect of the present invention, there is provided an electronic apparatus including: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to perform a method as described in any of the above.

According to a further aspect of the present invention there is provided a computer readable storage medium storing one or more programs which when executed by a processor implement a method as described in any of the above.

From the above, according to the technical scheme of the invention, the tracking object is tracked by determining the tracking object, determining the target point according to the current position of the tracking object, and planning a path from the current position of the intelligent mobile device to the target point as a global path. And selecting one track line from a preset track line set as a local path according to the current speed and the global path of the intelligent mobile equipment. Before tracking is started, the travelling direction of the intelligent mobile equipment is determined, so that the intelligent mobile equipment has a travelling basis, and the problem that the tracking object moves too fast to cause loss is avoided. Moreover, the local path can realize accurate control on the movement of the intelligent mobile equipment, so that the advancing precision of the intelligent mobile equipment is improved, and the advancing efficiency can be improved to a certain extent.

The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:

FIG. 1 shows a flow diagram of a method for local path planning for an intelligent mobile device, according to one embodiment of the invention;

FIG. 2 shows a schematic diagram of a local path planning apparatus for an intelligent mobile device according to one embodiment of the present invention;

FIG. 3 shows a schematic diagram of an electronic device according to one embodiment of the invention;

fig. 4 illustrates a schematic structure of a computer-readable storage medium according to an embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Fig. 1 shows a flow diagram of a local path planning method of an intelligent mobile device according to an embodiment of the invention. As shown in fig. 1, the method includes:

Step S110, determining a tracking object.

Tracking objects with movable capabilities are objects, such as people, that the smart mobile device needs to follow.

Step S120, determining a target point according to the current position of the tracking object, planning a path from the current position of the intelligent mobile device to the target point as a global path, and tracking the tracking object.

The intelligent mobile device can be any mobile intelligent device, such as a sweeping robot, an unmanned mobile platform and the like. The intelligent mobile equipment needs to pre-judge the target point of the tracked object in advance, and plans a path reaching the target point so as to achieve a better tracking effect. For example, the tracking object is in the right front of the intelligent mobile device, then the target point is determined to be in the right front and farther than the tracking object, and the planned path is taken as the global path. Therefore, before tracking is started, the travelling direction of the intelligent mobile equipment is determined, so that the intelligent mobile equipment has a travelling basis, and the situation that the tracking object moves too fast to cause loss is avoided.

Step S130, selecting a track line from a preset track line set as a local path according to the current speed of the intelligent mobile device and the global path.

The global path is used for guiding the travelling direction of the intelligent mobile equipment, and in the travelling process, a local path line is also required to be determined to assist the intelligent mobile equipment to travel along the global path, wherein the local path line is the local path. The global path is longer, which is unfavorable for controlling the intelligent mobile device. If the intelligent mobile device only adopts a single moving mode to travel along the global path to the target point, the travelling efficiency can be affected to a certain extent. Moreover, if the speed of the intelligent mobile device is too high, when the road surface is uneven, the road surface may deviate from the global path in the running process, which is not beneficial to the precision control of the intelligent mobile device. Therefore, the intelligent mobile equipment moves along the local path, and because the local path is shorter, the accurate control on the movement of the intelligent mobile equipment can be realized, and the moving precision of the intelligent mobile equipment is improved. On different local paths, different moving modes are adopted to improve the travelling efficiency. And each time the intelligent mobile equipment completes the travelling of one local path, the travelling result can be evaluated so as to adjust the next local path. For example, if the current speed is high, the shorter local path is adjusted, and if the current speed is low, the local path can be correspondingly prolonged. And if the current local path deviates from the direction of the global path, the direction of the next local path is correspondingly adjusted.

According to the technical scheme, the target point is determined according to the current position of the tracking object by determining the tracking object, and a path from the current position of the intelligent mobile device to the target point is planned to be used as a global path to track the tracking object. And selecting one track line from a preset track line set as a local path according to the current speed and the global path of the intelligent mobile equipment. Before tracking is started, the travelling direction of the intelligent mobile equipment is determined, so that the intelligent mobile equipment has a travelling basis, and the problem that the tracking object moves too fast to cause loss is avoided. Moreover, the local path can realize accurate control on the movement of the intelligent mobile equipment, so that the advancing precision of the intelligent mobile equipment is improved, and the advancing efficiency can be improved to a certain extent.

In one embodiment of the present invention, in the method as shown in fig. 1, determining the tracking object in step S110 includes: and detecting through a depth camera and/or a laser radar, and determining the detected object which accords with the preset characteristic as a tracking object.

The depth camera or the laser radar can perform scanning detection, is arranged on the intelligent mobile device, and can acquire detection results of the surrounding environment of the intelligent mobile device.

In one specific example, a human leg is probed with a single line laser. Specifically, the surrounding environment of the intelligent mobile device is scanned through single-line laser, and a plurality of scanning points are obtained. And identifying one or more sections of curves which are formed by the scanning points and accord with the arc characteristics according to the distribution condition of a plurality of scanning points. And judging whether each section of the identified curve accords with the characteristics of the human legs, and if so, determining the detected human body position according to the corresponding curve.

The single-line laser is arranged on the intelligent mobile device, and the scanning point is obtained by sending out laser for scanning. The obtained scanning points can reflect the outline information of the object and the position information of the object. The single line laser has high working efficiency, and if the single line laser is rotated, the scanning point of the object outline within the 360-degree range of the intelligent mobile device can be obtained, and the scanning range is enlarged. The intelligent mobile device of the embodiment needs to detect people in the surrounding environment, so that human body information existing in the surrounding environment is obtained through single-line laser scanning.

And processing the scanning points, analyzing and obtaining specific information of the surrounding environment, for example, connecting the scanning points in sequence to obtain the outline of the object, and judging the object attribute through the outline to judge whether people exist in the surrounding environment. The human body contours are mostly curves and lack sharp edges, and whether the human body exists in the surrounding environment can be effectively identified by identifying whether one or more curves which are formed by the scanning points and accord with the characteristics of the circular ring exist or not. Whether the curve accords with the arc characteristic is identified, if the curvature has a large change, the curve accords with the arc characteristic.

Of course, there may be curves in the surrounding environment where the contour of other objects conforms to the characteristics of a circular arc, such as a cylindrical table or chair. Therefore, it is necessary to further determine whether the curve conforming to the circular arc feature conforms to the human leg feature, such as whether the width, curvature, etc. of the curve conforms to the human leg contour. Only when the curve accords with the characteristics of the human legs, the curve is judged to belong to the curve of the contour of the human legs, and the position of the curve is the position of the human body. After the human body position is identified, the intelligent mobile device can perform corresponding processing, such as avoiding the human body or tracking the human body. On the other hand, only the curve is judged to be in line with the characteristics of the human legs, so that certain data processing work is reduced, and the recognition efficiency and the working efficiency can be effectively improved.

According to the technical scheme, the human body in the surrounding environment can be accurately identified by combining the curve characteristics of the human body outline to carry out identification judgment, and the position of the human body is obtained. Meanwhile, only the curve obtained by scanning is judged to be in line with the characteristics of the human legs, so that certain data processing work is reduced, and the recognition efficiency and the working efficiency can be effectively improved. Moreover, the single-line laser is adopted for scanning, so that the scanning efficiency and the accuracy can be ensured, and the scanning range can be enlarged.

In a specific embodiment, the identifying one or more segments of curves, which are formed by the scanning points and conform to the arc characteristics, according to the distribution situation of a plurality of scanning points includes: and performing circle fitting according to the distribution condition of a plurality of scanning points to obtain one or more sections of curves formed by the scanning points.

In the above embodiment, the scanning points are sequentially connected to obtain the outline of the object. However, the contour curve obtained by the method is a broken line with discontinuous curvature formed by a plurality of segments, and thus does not conform to the objective rule that the contour of a common object is continuous. Therefore, the folding line needs to be smoothly processed, so that the folding line meets the objective rule of the contour line. For a curve conforming to the characteristic of an arc, for example, the curvature change between several consecutive scanning points is large, a circle fitting is performed on the curve, that is, the curve is processed into a theoretical arc.

In a specific embodiment, the identifying one or more segments of curves, which are formed by the scanning points and conform to the arc characteristics, according to the distribution situation of a plurality of scanning points includes: when a section of curve conforming to the characteristics of the arc is identified, judging whether continuous scanning points exist on the straight lines corresponding to the two endpoints of the arc; if yes, estimating the width of the detected object corresponding to the arc according to the continuous scanning points; if the width is larger than the preset value, discarding the identified curve which accords with the arc characteristic, and not carrying out identification on the continuous scanning points whether accords with the arc characteristic.

As can be seen from the above embodiments, the identification of the curve conforming to the arc characteristic is to determine whether the curve conforms to the leg characteristic. Considering that in practice, a human leg of normal size is typically between 10cm and 20cm wide. If the distance between the two end points of the curve exceeds 20cm or is less than 10cm, the width of the curve is obviously not in line with the width of the leg of the person, so that the curve is filtered, the data quantity to be judged is reduced, and the efficiency is improved for the next judgment.

On the other hand, the laser has measurement errors during scanning, for example, when a wall is scanned, wavy scanning points may be obtained due to the measurement errors. Thus, a plurality of continuous curves conforming to the arc characteristics are obtained. In order to avoid misjudging the curve conforming to the arc characteristic as a curve conforming to the characteristics of the human leg, a plurality of sections of continuous curves conforming to the arc characteristic need to be specially processed. Specifically, two end points of the multi-segment arc are connected to obtain a corresponding straight line. Thus, there must be a continuous scan point in the middle of the line. Judging whether the width of the first section of arc in the multiple sections of arcs accords with the width of the leg of the person, if not, indicating that the corresponding arc is not a curve obtained by scanning the leg of the person. And similarly, all the arc curves in the middle of the straight line are not curves obtained by scanning the legs of the human, so that the identified curves conforming to the arc characteristics are discarded, and whether continuous scanning points conform to the arc characteristics or not is not identified, the data processing capacity is reduced, and the identification rate is improved.

In a specific embodiment, the determining whether each segment of the identified curve meets the leg feature includes: judging whether the central angles corresponding to the curves are in a first preset angle range or not, and if so, judging that the corresponding curves accord with the characteristics of the legs.

The intelligent mobile device performs scanning at a fixed position during laser scanning. If the human leg is scanned, only a partial contour of the human leg is obtained, and not an entire closed circular contour. Thus, the curve conforming to the characteristics of a person's leg should have a fan angle. Since the curve can be regarded as a circular arc, that is to say, by judging whether the central angle corresponding to the curve is within the first preset angle range, whether the corresponding curve meets the human leg characteristics can be effectively identified. The first predetermined angular range is set in combination with the contour curve of the human leg.

Considering that the human leg contour curve is not theoretically circular, the first preset angle range is set to 60 ° to 120 ° in order to improve the determination accuracy. When the central angle corresponding to the curve is 60-120 degrees, the curve is considered to be the curve conforming to the characteristics of human legs, and the object corresponding to the curve is considered to be a human body. If the central angle corresponding to the curve is too large or too small, the curve is difficult to match with the actual human leg contour curve, and the curve is judged to be not in accordance with the human leg characteristics.

In a specific embodiment, the determining whether each segment of the identified curve meets the leg feature includes: judging whether each section of curve accords with the theorem of the circumference angle, if so, judging that the corresponding curve accords with the characteristics of the human legs.

Besides the judgment according to the central angle of the curve, the judgment can be carried out on the circumferential angle of the curve. In the actual operation process, the contour curve of the human leg is considered as a complete circle, and then any section of circular arc obtained from the contour curve is in accordance with the theorem of the circumferential angle, that is, the circumferential angles of any point on the corresponding circular arc of the section of circular arc are equal. Therefore, an arbitrary point on the curve other than the two end points of the curve is taken as an apex, the angle formed by the apex and the two end points is regarded as the circumferential angle of the curve, and if the angles of a plurality of circumferential angles are equal, the curve is judged to conform to the circumferential angle theorem, and therefore the curve is judged to conform to the leg characteristics.

In a specific example, two end points of the curve are M, N, any three non-coincident points A, B, C are taken on the curve, A, B, C and M, N are not coincident, and the two end points M, N respectively form the circumferential angles +.MAN, ++MBN and++MCN of the three curves, and if the angles of the three circumferential angles are equal, the section of curve accords with the circumferential angle theorem.

In a specific embodiment, the determining whether each segment of the curve meets the circumference angle theorem includes: for a section of curve, sequentially calculating circumferential angle angles formed by each point on the curve, the first end point and the second end point along the first end point to the second end point of the section of curve; if the change trend of the circumferential angle corresponding to each point is that the change trend is firstly smaller and then larger, it is determined that the segment of the curve does not conform to the circumference angle theorem.

Considering that the contour curve of a human leg is not actually a theoretical circle, the curve obtained by scanning the human leg does not completely conform to the circumferential angle theorem. That is, the respective circumferential angles may not be equal. In addition, during the laser scanning process, if a wall or other object with a right angle is scanned, a curve is obtained. In order to avoid erroneous judgment, the judgment accuracy is improved, and the judgment of the circumference angle theorem is further optimized.

The transformation of the circumference angle of the curve obtained by scanning the right-angle wall body or object has a certain rule. For example, if the first end point to the second end point of the curve are followed, a point on the curve is sequentially taken as a vertex, and a circumferential angle is formed by the two end points. The closer to the apex of the endpoint, the greater its circumferential angle. Therefore, the change rule of the circumferential angle is gradually decreased and then gradually increased at the circumferential angle formed by sequentially taking the points as the vertexes.

As in the specific example described above, the two end points of the curve are M, N, and starting from point M, a point is sequentially taken on the curve at regular intervals, and a circumferential angle is formed between the two end points. For example, A, B, C, D is taken, A, B, C, D and M, N are not coincident, and the circumferential angles of four curves are respectively formed by the two endpoints M, N, namely +.MAN, +.MBN, +.MCN and +.MDN. The transformation rule of the four circumferential angles is that the transformation rule is firstly reduced and then increased, namely, the < MAN > < MBN, < MCN < MDN >. When the change rule of firstly reducing and then enlarging is judged to be met between the peripheral angles, the curve is considered to be the curve obtained by scanning the right-angle part. And the contour curve of the human leg does not have a right angle feature, so that the curve is judged to be not in accordance with the theorem of the circumferential angle, namely not in accordance with the human leg feature.

In a specific embodiment, the determining whether each segment of the curve meets the circumference angle theorem includes: for a section of curve, sequentially calculating circumferential angle angles formed by each point on the curve, the first end point and the second end point along the first end point to the second end point of the section of curve; and calculating the mean square error of each circumferential angle, and if the mean square error is larger than a preset value, judging that the section of curve does not accord with the circumferential angle theorem.

Considering that the contour curve of a human leg is not actually a theoretical circle, the curve obtained by scanning the human leg does not completely conform to the theorem of circumferential angles, but each circumferential angle fluctuates within a certain angular range. And obtaining the degree of dispersion of the circumferential angles by judging the mean square error of each circumferential angle. If the degree of dispersion is within the preset range, the curve is considered to conform to the circumference angle theorem.

Taking the above embodiment as an example, two end points of the curve are M, N, and starting from the point M, a point is sequentially taken on the curve at regular intervals, and a circumferential angle is formed between the two end points. For example, A, B, C, D is taken, A, B, C, D and M, N are not coincident, and the circumferential angles of four curves are respectively formed by the two endpoints M, N, namely +.MAN, +.MBN, +.MCN and +.MDN. And calculating the mean square error of the four circumferential angles, and if the mean square error is smaller than a preset value, indicating that the dispersion degree of the four circumferential angles is smaller, judging that the curve accords with the circumferential angle theorem. If the mean square error is larger than the preset value, the dispersion degree of the four circumferential angles is larger, and the curve is judged to be not in accordance with the circumferential angle theorem. For example, the preset value is 0.5, and if the mean square error is 0, the angles of the four circumferential angles are equal. If the mean square error is 2 and is more than 0.5, the degree of dispersion of the four circumferential angles is larger, the curvature change of the curve is larger, and the curve does not accord with the contour curve characteristics of the human legs.

In a specific embodiment, the determining the detected position of the human body according to the corresponding curve includes: if the distance between the two sections of curves is smaller than the preset value, determining the same human body according to the two sections of curves.

One person corresponds to two legs, and in the laser scanning process, the high probability can obtain two sections of curves which accord with the characteristics of the legs of the person. In view of the fact that the distance between the two legs does not generally exceed a certain value, it is determined whether the two curves belong to the same person by determining the distance between the two curves. For example, an adult walking normally, the distance between the legs is 60cm. And setting the preset distance value of the curve to be 75cm, judging that the two sections of curves belong to two legs of the same person when the distance between the two sections of curves is smaller than 75cm, and determining the position of the human body according to the positions of the two sections of curves. For example, one curve is 100cm away from the intelligent mobile device, the other curve is 80cm away from the intelligent mobile device, the middle value of the two curves is taken, and the position of the human body is determined to be 90cm away from the intelligent mobile device.

There is of course also a case where only a curve conforming to the characteristics of a person's leg may be obtained during a scan. In this case, the segment of the curve is also regarded as a human leg contour curve, and the human leg position is determined from the position of the curve. In the actual scanning process, two human legs may overlap, and two segments of curves conforming to the characteristic curves of the human legs cannot be obtained, for example, the intelligent mobile device is located on the side surface of a human body, and when scanning is performed from the side surface, two legs of the human body overlap, and two segments of curves cannot be obtained.

In a specific embodiment, the scanning the surrounding environment of the smart mobile device by the single line laser includes: 360-degree surrounding scanning is carried out at a preset frequency through a laser radar.

The single-line laser is a laser radar, and in order to reduce certain data processing amount, the laser radar does not continuously scan in real time in the actual scanning process, but scans at a preset frequency. For example, one scan is performed at intervals of 1s, 5s and 8s, so that a certain time is left for processing the scan result after each scan is completed, and the accuracy of the result is ensured. The laser radar is arranged on a rotating platform of the intelligent mobile equipment, when the intelligent mobile equipment rotates or independently rotates the laser radar, the laser radar can realize 360-degree surrounding scanning, and the outline information of all objects in the surrounding environment is obtained.

In one embodiment of the present invention, in the method as shown in fig. 1, planning a path from the current location of the smart mobile device to the target point in step S120 includes: searching a track line reaching a target point from the current position of the intelligent mobile device based on an A-algorithm.

The algorithm A is a direct search method which is most effective in solving the shortest path in a static road network, and is also an effective algorithm for solving a plurality of path search problems. The current position and the target point position of the intelligent mobile equipment are determined, the trajectory line between the current position and the target point position can be quickly obtained by searching through an A-type algorithm, and the final searching speed is higher when the distance estimated value is closer to the actual distance value. Thus, the tracking efficiency of the intelligent mobile device can be further improved.

In one embodiment of the present invention, as in the method shown in fig. 1, the method further comprises: setting a plurality of sampling speeds according to parameters of the intelligent mobile equipment; and respectively generating the track lines of the intelligent mobile equipment at each sampling speed, and putting the track lines into a preset track line set.

The intelligent mobile device is provided with different moving modes and track lines corresponding to the sampling speeds, so that the travelling efficiency or the working efficiency of the intelligent mobile device is improved. For example, setting the sampling speeds of the intelligent mobile device to be 0, 0.1, 0.2 and 0.3m/s, and rotating the corresponding intelligent mobile device in situ when the sampling speed is 0 m/s; four traveling directions are set at 0.1m/s, traveling in each direction is 0.5m, and rotation is performed at the same time with 0.1m as a radius during traveling, so that four track lines are generated. The track line generated at other sampling speeds can be referred to as a generation mode of 0.1m/s, and the travelling distance and the rotation radius can be set according to specific situations. All the generated trajectories are stored, obtaining a set of trajectories. Therefore, when the intelligent mobile equipment needs to move, the most suitable track line is directly selected from the track line set to move, so that the moving efficiency is improved.

In one embodiment of the present invention, in the method as shown in fig. 1, selecting a trajectory line from a preset trajectory line set as a local path includes: for each track line in a preset track line set, calculating an evaluation value related to the current speed and the global path according to a preset evaluation function; and selecting the track line with the optimal evaluation value as the local path.

In the above embodiment, the trace set includes a plurality of preset traces traveling in different directions, and how to select the most suitable trace as the uniform distribution path is a problem to be solved. In the embodiment, an evaluation function is set, and the current speed and the global path of the intelligent mobile equipment are combined to evaluate each preset track line, so that an evaluation value is obtained. The evaluation value reflects the correlation between the local path and the global path and the correlation between the local path and the current state of the intelligent mobile equipment, and the track line with the optimal evaluation value is selected as the local path, so that the moving efficiency of the intelligent mobile equipment can be effectively improved.

In a specific example, the direction of global path planning is 30 ° in the east-north direction of the intelligent device, the track line set includes track lines moving in the east, south, west and north directions of the intelligent mobile device, and according to the evaluation function, the evaluation value of the track line moving in the east direction is the highest, and the track line moving in the east direction is the most fit with the planning direction of the global path, so that the track line moving in the east direction is selected as the local path.

In one embodiment of the present invention, in the method, for each track line in the preset track line set, calculating the evaluation value related to the current speed and the global path according to the preset evaluation function includes: according to a preset evaluation function, an evaluation value is obtained according to the deviation of the sampling speed and the current speed corresponding to each track line, the angle deviation of each track line and the global path and the position deviation of each track line and the global path.

The embodiment provides a specific implementation mode for evaluating the preset track line. The method mainly comprises two aspects of comparison evaluation of the current speed and the sampling speed of the intelligent mobile equipment and comparison evaluation of the track line and the global path. The larger the deviation between the current speed and the sampling speed of the intelligent equipment is, the lower the corresponding evaluation value is; similarly, the larger the angle deviation between the trajectory line and the global path is, the lower the corresponding evaluation value is; the further the position of the trajectory line end point is from the global path end point, i.e., the position of the target point, the larger the evaluation value thereof is. The total evaluation value of the track line can be obtained by integrating the evaluation values.

In one embodiment of the present invention, as in the method shown in fig. 1, the method further comprises: detecting an obstacle in the tracking process; when an obstacle is detected, the local path is adjusted according to the detected obstacle position.

Adjustment of the local path also requires adjustment in combination with the position of the obstacle. For example, the global path indicates a north direction of movement and the local path is moved 0.5m north. In the moving process, the obstacle is detected to be 0.4m away from the intelligent mobile device. And adjusting the moving distance of the local path to be 0.3m, and selecting the northeast direction from the direction of the next local path, wherein the moving distance is 0.5m so as to avoid the obstacle. By adopting the mode, the obstacle can be found in time, the local path is correspondingly adjusted, and the intelligent mobile equipment is prevented from colliding with the obstacle.

In one embodiment of the present invention, as in the method shown in fig. 1, the intelligent mobile device is a sweeping robot, and the tracking object is a human body.

The robot tracks the human body. Therefore, the sweeping robot can conduct sweeping work under the belt of a person, collision with obstacles is effectively avoided, damage risk of the sweeping robot is reduced, and service life of the sweeping robot is prolonged. For example, articles placed in a common living room are more, and under the guidance of a person, the sweeping robot can sweep on the moving area of the person, so that the obstacle is effectively avoided. Meanwhile, the sweeping robot does not need to get rid of poverty and find a sweeping route, and the sweeping efficiency is also greatly improved.

Fig. 2 is a schematic structural diagram of a local path planning apparatus for an intelligent mobile device according to an embodiment of the present invention. As shown in fig. 2, the apparatus 200 includes:

The determining unit 210 is adapted to determine a tracked object.

The global path unit 220 is adapted to determine the target point according to the current position of the tracked object, and plan a path from the current position of the smart mobile device to the target point as a global path for tracking the tracked object.

The local path unit 230 is adapted to select one trajectory line from a preset set of trajectory lines as a local path according to the current speed and the global path of the intelligent mobile device.

In an embodiment of the present invention, as in the apparatus 200 shown in fig. 2, the determining unit 210 is adapted to detect by means of a depth camera and/or a lidar, and determine the detected object according to the preset feature as the tracking object.

Taking a robot for sweeping the floor as an example for tracking a human body, the robot for sweeping the floor uses a laser radar for detection, partial human legs can be detected, the human legs are characterized by semicircular arcs, and a certain distance exists between the two legs. That is, when a single line laser detects a human leg, two semicircular arc characteristics whose distance is within a certain range can be obtained, or when one leg is detected, one semicircular arc characteristic is obtained, whereby it is determined that the semicircular arc characteristic corresponds to a human body, which is taken as a tracking object.

In an embodiment of the invention, the global path unit 220 is adapted to search a trajectory from the current location of the smart mobile device to the target point based on an a-algorithm, as in the apparatus 200 shown in fig. 2.

In one embodiment of the present invention, as in the apparatus 200 shown in fig. 2, the apparatus 200 further comprises: the track line unit is suitable for setting a plurality of sampling speeds according to parameters of the intelligent mobile equipment; and respectively generating the track lines of the intelligent mobile equipment at each sampling speed, and putting the track lines into a preset track line set.

And setting a plurality of sampling speeds, wherein different moving modes and track lines are arranged corresponding to the adopted speeds, so that the advancing efficiency or the working efficiency of the intelligent mobile equipment is improved. For example, setting the sampling speeds of the intelligent mobile device to be 0, 0.1, 0.2 and 0.3m/s, and rotating the corresponding intelligent mobile device in situ when the sampling speed is 0 m/s; four traveling directions are set at 0.1m/s, traveling in each direction is 0.5m, and rotation is performed at the same time with 0.1m as a radius during traveling, so that four track lines are generated. The track line generated at other sampling speeds can be referred to as a generation mode of 0.1m/s, and the travelling distance and the rotation radius can be set according to specific situations. All the generated trajectories are stored, obtaining a set of trajectories. Therefore, when the intelligent mobile equipment needs to move, the most suitable track line is directly selected from the track line set to move, so that the moving efficiency is improved.

In one embodiment of the present invention, in the apparatus 200, the local path unit 230 is adapted to calculate, for each trace line in the preset trace line set, an evaluation value related to the current speed and the global path according to a preset evaluation function; and selecting the track line with the optimal evaluation value as the local path.

In an embodiment of the present invention, in the apparatus 200, the local path unit is further adapted to calculate the evaluation value according to a preset evaluation function, based on a deviation of the sampling speed corresponding to each trace line from the current speed, an angular deviation of each trace line from the global path, and a positional deviation of each trace line from the global path.

In one embodiment of the present invention, as in the apparatus 200 shown in fig. 2, the apparatus further comprises: an obstacle unit adapted to perform obstacle detection during tracking; when an obstacle is detected, the local path is adjusted according to the detected obstacle position.

In one embodiment of the present invention, as in the apparatus 200 shown in fig. 2, the intelligent mobile device is a sweeping robot, and the tracking object is a human body.

In summary, according to the technical scheme of the invention, the tracking object is tracked by determining the tracking object, determining the target point according to the current position of the tracking object, and planning a path from the current position of the intelligent mobile device to the target point as a global path. And selecting one track line from a preset track line set as a local path according to the current speed and the global path of the intelligent mobile equipment. Before tracking is started, the travelling direction of the intelligent mobile equipment is determined, so that the intelligent mobile equipment has a travelling basis, and the problem that the tracking object moves too fast to cause loss is avoided. Moreover, the local path can realize accurate control on the movement of the intelligent mobile equipment, so that the advancing precision of the intelligent mobile equipment is improved, and the advancing efficiency can be improved to a certain extent.

It should be noted that:

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose devices may also be used with the teachings herein. The required structure for the construction of such devices is apparent from the description above. In addition, the present invention is not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.

In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functions of some or all of the components in a local path planning apparatus for an intelligent mobile device according to embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.

For example, fig. 3 shows a schematic structural diagram of an electronic device according to an embodiment of the present invention. The electronic device comprises a processor 310 and a memory 320 arranged to store computer executable instructions (computer readable program code). The memory 320 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. The memory 320 has a memory space 330 storing computer readable program code 331 for performing any of the method steps described above. For example, the memory space 330 for storing computer readable program code may include respective computer readable program code 331 for implementing the respective steps in the above method, respectively. The computer readable program code 331 can be read from or written to one or more computer program products. These computer program products comprise a program code carrier such as a hard disk, a Compact Disc (CD), a memory card or a floppy disk. Such a computer program product is typically a computer readable storage medium as described for example in fig. 4. Fig. 4 illustrates a schematic structure of a computer-readable storage medium according to an embodiment of the present invention. The computer readable storage medium 400 stores computer readable program code 331 for performing the steps of the method according to the invention, which may be read by the processor 310 of the electronic device 300, which computer readable program code 331, when executed by the electronic device 300, causes the electronic device 300 to perform the steps of the method described above, in particular the computer readable program code 331 stored by the computer readable storage medium may perform the method shown in any of the embodiments described above. The computer readable program code 331 may be compressed in a suitable form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.

The invention provides A1, a local path planning method of intelligent mobile equipment, which comprises the following steps:

determining a tracking object;

A2, the method of A1, wherein the determining the tracking object comprises:

A3, the method of A1, wherein the planning a path from the current location of the smart mobile device to the target point comprises:

A4, the method of A1, wherein the method further comprises:

A5, the method of A1, wherein selecting one track line from a preset track line set as a local path comprises:

A6, the method of A5, wherein the calculating the evaluation value related to the current speed and the global path according to the preset evaluation function for each track line in the preset track line set comprises:

A7, the method of A1, wherein the method further comprises:

Detecting an obstacle in the tracking process;

A8, the method of A1, wherein the intelligent mobile device is a sweeping robot, and the tracking object is a human body.

The invention also provides a B9, a local path planning device of the intelligent mobile equipment, which comprises:

a determination unit adapted to determine a tracked object;

B10, the device as defined in B9, wherein the determining unit is adapted to detect by a depth camera and/or a laser radar, and determine the detected object according to the preset feature as the tracking object.

B11, the apparatus of B9, wherein the global path unit is adapted to search a trajectory from the current location of the smart mobile device to the target point based on an a-x algorithm.

B12, the apparatus of B9, wherein the apparatus further comprises:

B13, the device of B9, wherein the local path unit is adapted to calculate, for each track line in a preset track line set, an evaluation value related to the current speed and the global path according to a preset evaluation function;

B14, the apparatus of B13, wherein the local path unit is further adapted to calculate an evaluation value according to the preset evaluation function, according to a deviation between the sampling speed corresponding to each trace line and the current speed, an angular deviation between each trace line and the global path, and a positional deviation between each trace line and the global path.

B15, the apparatus of B9, wherein the apparatus further comprises:

An obstacle unit adapted to perform obstacle detection during tracking;

B16, the apparatus of B9, wherein the intelligent mobile device is a sweeping robot, and the tracking object is a human body.

The invention also provides C17, an electronic device, wherein the electronic device comprises: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method of any of A1-A8.

The invention also provides D18, a computer readable storage medium storing one or more programs which, when executed by a processor, implement the method of any of A1-A8.

Claims

1. A local path planning method for an intelligent mobile device, comprising:

determining a tracking object;

Selecting a track line from a preset track line set as a local path according to the current speed of the intelligent mobile equipment and the global path;

The method further comprises the steps of: setting a plurality of sampling speeds according to parameters of the intelligent mobile equipment; respectively generating a track line of the intelligent mobile equipment at each sampling speed, and placing the track line into the preset track line set;

The selecting a trace line from a preset trace line set as a local path comprises: for each track line in a preset track line set, calculating an evaluation value related to the current speed and the global path according to a preset evaluation function; and selecting the track line with the optimal evaluation value as the local path.

2. The method of claim 1, wherein the determining a tracking object comprises:

3. The method of claim 1, wherein the planning a path from a current location of a smart mobile device to the target point comprises:

4. The method of claim 1, wherein said evaluating the current speed and the global path for each trace line in the set of predetermined trace lines according to a predetermined evaluation function comprises:

5. The method of claim 1, wherein the method further comprises:

Detecting an obstacle in the tracking process;

6. The method of claim 1, wherein the intelligent mobile device is a sweeping robot and the tracking object is a human body.

7. A local path planning apparatus for an intelligent mobile device, comprising:

a determination unit adapted to determine a tracked object;

the local path unit is suitable for selecting one path line from a preset path line set as a local path according to the current speed of the intelligent mobile equipment and the global path;

the track line unit is suitable for setting a plurality of sampling speeds according to the parameters of the intelligent mobile equipment; respectively generating a track line of the intelligent mobile equipment at each sampling speed, and placing the track line into the preset track line set;

the local path unit is further suitable for solving evaluation values related to the current speed and the global path according to a preset evaluation function for each track line in a preset track line set; and selecting the track line with the optimal evaluation value as the local path.

8. The apparatus according to claim 7, wherein the determining unit is adapted to detect by means of a depth camera and/or a lidar, and determine the detected object according to the preset feature as a tracking object.

9. The apparatus of claim 7, wherein the global path unit is adapted to search for a trajectory from a current location of the smart mobile device to the target point based on an a-algorithm.

10. The apparatus of claim 7, wherein the local path unit is further adapted to calculate an evaluation value according to the preset evaluation function based on a deviation of the sampling speed corresponding to each trajectory from the current speed, an angular deviation of each trajectory from the global path, and a positional deviation of each trajectory from the global path.

11. The apparatus of claim 7, wherein the apparatus further comprises:

An obstacle unit adapted to perform obstacle detection during tracking;

12. The apparatus of claim 7, wherein the intelligent mobile device is a sweeping robot and the tracking object is a human body.

13. An electronic device, wherein the electronic device comprises: a processor; and a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of any of claims 1-6.

14. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs, which when executed by a processor, implement the method of any of claims 1-6.