Method and device for adjusting driving route, storage medium and electronic device

Abstract

The application discloses a kind of driving route adjustment method and device, storage medium and electronic device, comprising: through position sensitive detector in the process of self-moving equipment driving, position detection data is collected, wherein the position detection data is used to indicate the distance of the position sensitive detector and obstacle, the position sensitive detector is set to the self-moving equipment;According to the position detection data, curve fitting is carried out to obtain fitting contour curve, wherein the fitting contour curve is used to indicate the contour of the obstacle;According to the fitting contour curve, the driving route of the self-moving equipment is adjusted.The above technical scheme is used, in the prior art, only through side along edge sensor to the obstacle is perceived, the contour of the obstacle cannot be effectively perceived, and then the problem that multiple collisions occur between the obstacle and the robot during the driving process is solved.

Description

[Technical Field]

[0001] This invention relates to the field of communications, and more specifically, to a method and apparatus for adjusting a travel route, a storage medium, and an electronic device. [Background Technology]

[0002] With the development of technology, more and more people are starting to use smart devices for cleaning in their daily lives, such as robot vacuum cleaners. Robot vacuum cleaners can be roughly divided into smart vacuum cleaners, smart sweeping machines, and smart sweeping machines that combine vacuuming and sweeping. Among them, robot vacuum cleaners can move autonomously to different areas to perform cleaning tasks in different areas.

[0003] However, when a robot vacuum cleaner is cleaning an area, there will be many different kinds of obstacles in the area, such as stools, toys, tables, etc. During the process, the robot vacuum cleaner usually uses side edge sensors to clean along the edges of the area where the obstacle is located. However, during the process of the robot vacuum cleaner moving, it cannot perceive the outline of the obstacle well by only using side edge sensors. This may cause the robot vacuum cleaner to collide with the obstacle multiple times during the process.

[0004] There is currently no effective solution to the problem that existing technologies, which rely solely on side edge sensors to detect obstacles, cannot effectively perceive the outline of obstacles, leading to multiple collisions between the robot vacuum cleaner and obstacles during operation.

[0005] Therefore, it is urgent to improve the relevant technologies in order to at least partially solve the above-mentioned technical problems. [Summary of the Invention]

[0006] This invention provides a device for adjusting a driving route, a storage medium, and an electronic device to at least solve the problem in the prior art where the robot vacuum cleaner cannot effectively perceive the outline of obstacles by only using side edge sensors, thus causing multiple collisions with obstacles during driving.

[0007] According to one aspect of the present invention, a method for adjusting a driving route is provided, comprising: collecting position detection data during the driving of a self-moving device using a position-sensitive detector, wherein the position detection data is used to indicate the distance between the position-sensitive detector and an obstacle, and the position-sensitive detector is disposed on the self-moving device; performing curve fitting based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle; and adjusting the driving route of the self-moving device based on the fitted contour curve.

[0008] In an exemplary embodiment, collecting position detection data by a position-sensitive detector during the movement of a self-moving device includes: controlling the position-sensitive detector to emit a detection signal during the movement of the self-moving device; and, when the position-sensitive detector receives a feedback signal from the detection signal within a preset time range, using the distance between the position-sensitive detector and the obstacle calculated based on the emission time of the detection signal and the reception time of the feedback signal as the position detection data, wherein the maximum value of the preset time range is less than a preset threshold.

[0009] In an exemplary embodiment, curve fitting based on the position detection data to obtain a fitted contour curve includes: continuously collecting multiple position detection data during the movement of the self-moving device; calculating multiple second position coordinates of the obstacle based on the multiple position detection data, a first position coordinate, and a target direction, wherein the first position coordinate is used to indicate the position of the self-moving device when the position detection data is collected, the target direction is used to indicate the pose of the obstacle relative to the self-moving device when the position detection data is collected, and the multiple second position coordinates correspond one-to-one with the multiple position detection data; and performing curve fitting on the multiple second position coordinates using a preset fitting algorithm to obtain the fitted contour curve.

[0010] In an exemplary embodiment, after performing curve fitting on the plurality of second position coordinates using a preset fitting algorithm to obtain the fitted contour curve, the method further includes: saving the fitted contour curve to a map saved by the self-moving device, wherein the map already contains a plurality of fitted contour curves; when the self-moving device performs the next round of cleaning, determining a target fitted contour curve from the plurality of fitted contour curves obtained in the map, wherein the target fitted contour curve is the fitted contour curve in the map that has the smallest distance to the self-moving device; controlling the self-moving device to adjust its driving route in the target obstacle area to the target fitted contour curve, wherein the target obstacle area is the area where the target obstacle is located, and the target fitted contour curve is the fitted contour curve obstacle corresponding to the target fitted contour curve.

[0011] In one exemplary embodiment, adjusting the travel route of the self-moving device according to the fitted contour curve includes: determining whether the fitted contour curve is a closed shape; and if the fitted contour curve is a closed shape, controlling the self-moving device to move away from the fitted contour curve.

[0012] In an exemplary embodiment, after determining whether the fitted contour curve is a closed shape, the method further includes: if the fitted contour curve is a non-closed shape, extending the fitted contour curve according to parameter information of the fitted contour curve, wherein the parameter information includes at least one of the following: curvature, length; and controlling the self-moving device to adjust the current driving route to the extended fitted contour curve.

[0013] In one exemplary embodiment, extending the fitted contour curve according to the parameter information of the fitted contour curve includes: calculating a first shape and a first probability of the fitted contour curve according to the parameter information of the fitted contour curve, wherein the first probability is used to indicate the probability that the fitted contour curve is the first shape; determining a second shape corresponding to the second probability, wherein the second probability is the first probability with the largest value; and extending the fitted contour curve according to the second shape and the parameter information.

[0014] According to another aspect of the present invention, a driving route adjustment device is also provided. The device includes: a data acquisition module, configured to acquire position detection data during the driving of a self-moving device using a position-sensitive detector, wherein the position detection data is used to indicate the distance between the position-sensitive detector and an obstacle, and the position-sensitive detector is disposed on the self-moving device; a fitting module, configured to perform curve fitting based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle; and an adjustment module, configured to adjust the driving route of the self-moving device based on the fitted contour curve.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, wherein the computer program is configured to execute the above-described method for adjusting the driving route when it is run.

[0016] According to another aspect of the present invention, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-mentioned method for adjusting the driving route through the computer program.

[0017] In this embodiment of the invention, a position-sensitive detector installed on the self-moving device collects position detection data during the self-moving device's movement to indicate the distance between the position-sensitive detector and obstacles. Curve fitting is performed based on the position detection data to obtain a fitted contour curve indicating the outline of the obstacle. The self-moving device's driving route is adjusted based on the fitted contour curve. By collecting position detection data and performing curve fitting on the collected position detection data, the outline of the obstacle is identified, assisting the self-moving device in scene recognition and providing navigation assistance for the self-moving device's forward direction, thus helping the self-moving device to better complete cleaning. This technical solution solves the problem in the prior art where only side edge sensors are used to perceive obstacles, which cannot effectively perceive the outline of the obstacle, leading to multiple collisions between the robot vacuum and obstacles during movement. It achieves the technical effect of accurately identifying obstacle outlines, thereby helping the self-moving device adjust its driving direction. [Attached Image Description]

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and, together with the description thereof, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0019] Figure 1 This is a hardware structure block diagram of a sweeping robot according to an optional method for adjusting the driving route, as described in an embodiment of the present invention.

[0020] Figure 2 This is a flowchart of an optional method for adjusting a driving route according to an embodiment of the present invention;

[0021] Figure 3 This is a flowchart illustrating an optional method for adjusting a driving route according to an embodiment of the present invention;

[0022] Figure 4 This is a structural block diagram of an optional driving route adjustment device according to an embodiment of the present invention;

[0023] Figure 5 This is a schematic diagram of the structure of an optional self-moving device in an embodiment of the present invention.

Detailed Implementation Methods

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] The methods and embodiments provided in this invention can be executed in a robotic vacuum cleaner (equivalent to the aforementioned self-moving device) or a similar computing device. Taking its operation on a robotic vacuum cleaner as an example, Figure 1 This is a hardware structure block diagram of a sweeping robot using a method for adjusting its driving route according to an embodiment of the present invention. Figure 1 As shown, a robotic vacuum cleaner may include one or more ( Figure 1 Only one is shown in the image. A processor 102 (which may include, but is not limited to, a microprocessor unit (MPU) or a programmable logic device (PLD)) and a memory 104 for storing data are also shown. In one exemplary embodiment, the aforementioned sweeping robot may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned robotic vacuum cleaner. For example, the robotic vacuum cleaner may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 Equivalent functions or ratios shown Figure 1 The functions shown have more different configurations.

[0027] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the route adjustment method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the robot vacuum cleaner via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0028] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the robot vacuum cleaner's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0029] This embodiment provides a method for adjusting a driving route. Figure 2 This is a flowchart of a method for adjusting a driving route according to an embodiment of the present invention, the process including the following steps:

[0030] Step S202: During the movement of the self-moving device, position detection data is collected by a position-sensitive detector, wherein the position detection data is used to indicate the distance between the position-sensitive detector and the obstacle, and the position-sensitive detector is set on the self-moving device;

[0031] It should be noted that a position-sensitive detector (PSD) is a device that can detect photoelectric position. It is often used as a position sensor combined with a light source. PSD is basically a light sensor and is also called a coordinate photocell.

[0032] Step S204: Perform curve fitting based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle.

[0033] It should be noted that the above curve fitting process involves converting the collected position detection data into obstacle position coordinate data. By applying a curve fitting algorithm to these position coordinate data, a fitted contour curve that indicates the outline of the obstacle can be obtained.

[0034] Step S206: Adjust the driving route of the self-moving device according to the fitted contour curve.

[0035] Optionally, by extending the obtained fitted profile curve and adjusting the driving route to the extended fitted profile curve, the probability of collision between the self-moving device and obstacles can be reduced, helping the self-moving device to drive smoothly along the obstacles.

[0036] Through the above steps, a position-sensitive detector installed on the self-moving device collects position detection data during the self-moving device's movement to indicate the distance between the position-sensitive detector and obstacles; curve fitting is performed based on the position detection data to obtain a fitted contour curve indicating the outline of the obstacle; the self-moving device's driving route is adjusted based on the fitted contour curve; by collecting position detection data and performing curve fitting on the collected position detection data, the outline of the obstacle is identified, assisting the self-moving device in scene recognition and providing navigation assistance for the self-moving device's forward direction, thus helping the self-moving device to better complete cleaning. This technical solution solves the problem in existing technologies where only side edge sensors are used to perceive obstacles, which cannot effectively perceive the outline of obstacles, leading to multiple collisions between the robot vacuum and obstacles during movement; it achieves the technical effect of accurately identifying obstacle outlines, thereby helping the self-moving device adjust its driving direction.

[0037] The above-mentioned data collection step S202 involves collecting position detection data using a position-sensitive detector during the movement of the self-moving device. This includes the following steps: controlling the position-sensitive detector to emit a detection signal during the movement of the self-moving device; and, when the position-sensitive detector receives a feedback signal from the detection signal within a preset time range, calculating the distance between the position-sensitive detector and the obstacle based on the emission time of the detection signal and the reception time of the feedback signal, and using this distance as the position detection data. The maximum value of the preset time range is less than a preset threshold.

[0038] A position-sensitive detector is installed on the self-moving device. During the movement of the self-moving device, the position-sensitive detector continuously emits detection signals to sense obstacles around the self-moving device. If the position-sensitive detector receives a feedback signal from the detection signal within a preset time range, it indicates that an obstacle has appeared within the detection range of the position-sensitive detector. Since the self-moving device only needs to detect obstacles that are relatively close through the position-sensitive detector, the preset time range is set to be relatively small, that is, the minimum value of the preset time range must be less than a preset threshold, to avoid the self-moving device detecting obstacles that are too far away and affecting the movement of the self-moving device. The distance between the obstacle and the self-moving device is calculated based on the difference between the transmission time and the reception time of the detection signal, and this distance is used as the position detection data.

[0039] Using the above scheme, a position-sensitive detector installed on the self-moving device continuously sends detection signals as the self-moving device moves, and receives feedback signals from the detection signals. Since the self-moving device is constantly moving and the detection range is small, a preset time range is set. Only when the feedback signal of the detection signal is received within the preset time range is the distance between the position-sensitive detector and the obstacle calculated, thereby collecting the position data of the obstacle.

[0040] It should be noted that the method described above for calculating the distance by the difference between the transmission and reception times of the detection signal is only used as an example. Position-sensitive detectors can also obtain position data through other means, and this application does not limit this.

[0041] Optionally, the above fitting step S204: performing curve fitting based on the position detection data to obtain a fitted contour curve can be achieved through the following steps: continuously collecting multiple position detection data during the movement of the self-moving device; calculating multiple second position coordinates of the obstacle based on the multiple position detection data, the first position coordinates, and the target direction, wherein the first position coordinates are used to indicate the position of the self-moving device when the position detection data is collected, the target direction is used to indicate the pose of the obstacle relative to the self-moving device when the position detection data is collected, and the multiple second position coordinates correspond one-to-one with the multiple position detection data; and performing curve fitting on the multiple second position coordinates using a preset fitting algorithm to obtain the fitted contour curve.

[0042] During the movement of the self-moving device, position detection data is continuously collected to more accurately obtain the outline of the obstacle. While moving, the self-moving device performs curve fitting based on the collected position detection data, so that the self-moving device can adjust its driving direction according to the latest obtained fitted outline curve of the obstacle. Curve fitting requires first obtaining multiple position coordinates of the obstacle (equivalent to the second position coordinates mentioned above). Based on the position coordinates of the self-moving device when the position detection data was collected (equivalent to the first position coordinates mentioned above), the multiple position detection data obtained, and the orientation of the obstacle relative to the self-moving device when the position detection data was collected (equivalent to the target direction mentioned above), the multiple position coordinates of the obstacle are determined. Then, a preset fitting algorithm is used to perform curve fitting on the multiple position coordinates to obtain the fitted outline curve.

[0043] Using the above scheme, multiple position detection data of obstacles are continuously collected during the movement of the self-moving device, and the first position coordinates of the self-moving device and the orientation of the obstacle relative to the self-moving device at the time of collection are determined to obtain multiple position coordinates of the obstacle. Curve fitting of these multiple position coordinates can obtain a fitted contour curve, thereby helping the self-moving device to identify the contour of the obstacle, so as to plan the driving route.

[0044] It should be noted that the position-sensitive detector is set at a fixed position on the self-moving device. Therefore, the position of an obstacle relative to the self-moving device detected by the same position-sensitive detector at the same time can be determined based on the current pose of the self-moving device and the position of the position-sensitive detector on the self-moving device.

[0045] Based on the above steps, the fitting step S204 is executed: after performing curve fitting on the plurality of second position coordinates using a preset fitting algorithm to obtain the fitted contour curve, the method further includes: saving the fitted contour curve to the map saved by the self-moving device, wherein the map has already saved a plurality of fitted contour curves; when the self-moving device performs the next round of cleaning, determining a target fitted contour curve from the plurality of fitted contour curves obtained in the map, wherein the target fitted contour curve is the fitted contour curve in the map that has the smallest distance to the self-moving device; controlling the self-moving device to adjust its driving route in the target obstacle area to the target fitted contour curve, wherein the target obstacle area is the area where the target obstacle is located, and the target fitted contour curve is the fitted contour curve obstacle corresponding to the target fitted contour curve.

[0046] After obtaining the fitted contour curve, the mobile device records the fitted contour curve in the mobile device's map, which stores all the fitted contour curves obtained by the mobile device in history. When the mobile device performs the next round of cleaning, it selects the fitted contour curve of the nearest obstacle (equivalent to the target fitted contour curve mentioned above) in the map based on its current position. When the mobile device travels to the area where the target fitted contour curve is located according to the original route, it will travel according to the fitted contour curve to clean the area around the obstacle and avoid missing any areas.

[0047] Using the above scheme, after obtaining the fitted contour curve of the obstacle, the fitted contour curve is stored in the map. When the self-moving device moves to the vicinity of the fitted contour curve during the next cleaning, the driving route of the self-moving device in the area where the fitted contour curve is located is adjusted to the fitted contour curve, thereby helping the self-moving device to drive along the edge of the obstacle and avoid missing the scan.

[0048] It should be noted that if the newly obtained fitted contour curve of the self-moving device is different from the previously recorded fitted contour curve at the same location on the map, the self-moving device will update the fitted contour curve at that location.

[0049] Optionally, the above adjustment step S206: adjusting the driving route of the self-moving device according to the fitted contour curve can be achieved by the following scheme, specifically including: determining whether the fitted contour curve is a closed figure; if the fitted contour curve is a closed figure, controlling the self-moving device to move away from the fitted contour curve.

[0050] During the process of adjusting the travel route of the self-moving device according to the fitted contour curve, the self-moving device collects position detection data while driving to perform curve fitting. That is, the fitted contour curve is constantly being updated and extended. If the self-moving device detects that the fitted contour curve has been extended into a closed shape, it means that the self-moving device has traveled around the obstacle, has completely identified the contour of the obstacle, and has completed the cleaning of the area where the obstacle is located in this round of cleaning. Then, the self-moving device can be controlled to move away from the obstacle corresponding to the fitted contour curve and clean other areas.

[0051] Using the above scheme, if the obtained fitted contour curve is a closed shape, it can be confirmed that the self-moving device has traveled around the obstacle once, that is, the self-moving device has completely cleaned the area around the obstacle and has collected the PSD data (equivalent to the above position detection data) around the obstacle. The self-moving device can then be controlled to move away from the obstacle to avoid repeated cleaning.

[0052] Based on the above steps: after determining whether the fitted contour curve is a closed shape, the method further includes: if the fitted contour curve is a non-closed shape, extending the fitted contour curve according to the parameter information of the fitted contour curve, wherein the parameter information includes at least one of the following: curvature, length; controlling the self-moving device to adjust the current driving route to the extended fitted contour curve.

[0053] If the fitted contour curve is identified as a non-closed shape, it means that the automatic device has not fully identified the obstacle and needs to continue moving along the obstacle. However, the automatic device has not recorded the PSD data (equivalent to the position detection data mentioned above) in front. Therefore, it is necessary to make a certain prediction based on the currently obtained fitted contour curve, extend the fitted contour curve according to its curvature and length, and control the automatic device to drive according to the extended fitted contour curve.

[0054] Using the above method, if it is determined that the fitted contour curve is not a closed shape, it is determined that the self-moving device has not yet completely identified the contour of the obstacle. In order for the self-moving device to better fit the obstacle and drive, the self-moving device will appropriately extend the fitted contour curve according to the parameter information of the fitted contour curve, so as to adjust the driving route of the self-moving device and enable the self-moving device to drive along the edge of the obstacle.

[0055] Optionally, the above-mentioned extension step: extending the fitted contour curve according to the parameter information of the fitted contour curve includes: calculating a first shape and a first probability of the fitted contour curve according to the parameter information of the fitted contour curve, wherein the first probability is used to indicate the probability that the fitted contour curve is the first shape; determining a second shape corresponding to the second probability, wherein the second probability is the first probability with the largest value; and extending the fitted contour curve according to the second shape and the parameter information.

[0056] The fitting profile is extended based on the parameter information of the fitting profile curve, including the following steps: First, predict the possible shape of the fitting profile curve and the probability of each shape based on the curvature and length of the fitting profile curve. Then, determine the shape corresponding to the highest probability value among multiple probabilities as the shape of the fitting profile curve. Finally, extend the fitting profile curve based on the second shape and the curvature, length and other parameter information of the fitting profile curve.

[0057] For example, if the probability of the fitted contour curve being a rectangle is predicted to be 60%, a square to be 30%, and a circle to be 10%, then the fitted contour curve is identified as a rectangle, and the remaining length of the currently unidentified side is predicted based on the length of each side of the existing fitted contour curve, and the fitted contour curve is extended.

[0058] If the shape of the fitted profile curve is determined to be circular, the center and radius of the circle are calculated based on the length and curvature of the fitted profile curve. The length of the arc that has not yet been identified is predicted based on the obtained data, and the fitted profile curve is extended appropriately according to the current curvature and the predicted length.

[0059] Obviously, the embodiments described above are only some embodiments of the present invention, and not all embodiments. In order to better understand the above method for adjusting the driving route, the above process will be described in conjunction with optional embodiments below, but it is not intended to limit the technical solution of the embodiments of the present invention.

[0060] This embodiment provides a method for adjusting a driving route, which is a flowchart illustrating an optional method for adjusting a driving route according to an embodiment of the present invention. Figure 3 As shown, the specific steps are as follows:

[0061] Step S302: Collect PSD data (equivalent to the above-mentioned position detection data) by using the PSD sensor (equivalent to the above-mentioned position sensitive detector) set on the robot vacuum cleaner, and store it in the map;

[0062] Step S304: Perform curve fitting on the PSD data using a curve fitting algorithm to obtain the outline of the obstacle;

[0063] Step S306: Control the sweeping robot to adjust its driving direction in real time according to the obtained fitting curve (equivalent to the above fitting contour curve) so that the sweeping robot can drive around the obstacle and obtain the complete contour of the obstacle.

[0064] Step S308: When the robot vacuum cleaner performs the next cleaning cycle, a reference route is provided to the robot vacuum cleaner based on the stored fitted curve to help the robot vacuum cleaner complete the cleaning work better.

[0065] Through the above steps, the robotic vacuum cleaner first accumulates a large amount of PSD data by driving within the target area. Simultaneously, it performs curve fitting on the acquired PSD data. Based on the fitted curve, it helps the robotic vacuum cleaner adjust its driving direction to better complete the cleaning, avoiding premature turns that could cause missed areas. Furthermore, during the next cleaning cycle, the stored fitted curve provides a reference route for the robotic vacuum cleaner. This solves the problem in existing technologies where only side edge sensors detect obstacles, failing to effectively perceive the obstacle's outline and leading to multiple collisions during driving. The robotic vacuum cleaner achieves accurate obstacle outline recognition, thereby helping the self-moving device adjust its driving direction.

[0066] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0067] This embodiment also provides a route adjustment device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementations, or a combination of software and hardware, are also possible and contemplated.

[0068] Figure 4 This is a structural block diagram of an optional driving route adjustment device according to an embodiment of the present invention, the device comprising:

[0069] The acquisition module 42 is used to acquire position detection data during the movement of the self-moving device via a position sensitive detector, wherein the position detection data is used to indicate the distance between the position sensitive detector and obstacles, and the position sensitive detector is installed on the self-moving device;

[0070] The fitting module 44 is used to perform curve fitting based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle.

[0071] The adjustment module 46 is used to adjust the driving route of the self-moving device according to the fitted contour curve.

[0072] The aforementioned device collects position detection data, indicating the distance between the position-sensitive detector and obstacles, via a position-sensitive detector mounted on the self-moving device during its movement. Curve fitting is then performed based on the position detection data to obtain a fitted contour curve indicating the outline of the obstacle. The self-moving device's travel route is adjusted according to the fitted contour curve. By collecting position detection data and performing curve fitting, the outline of obstacles is identified, assisting the self-moving device in scene recognition and providing navigation assistance for its forward direction, thus helping it to better complete cleaning. This technical solution solves the problem in existing technologies where only side edge sensors are used to perceive obstacles, which cannot effectively detect the outline of obstacles, leading to multiple collisions with obstacles during the robot's movement. It achieves accurate obstacle outline identification, thereby helping the self-moving device adjust its travel direction.

[0073] The acquisition module 42 is further configured to control the position-sensitive detector to emit a detection signal during the movement of the self-moving device; when the position-sensitive detector receives a feedback signal of the detection signal within a preset time range, the distance between the position-sensitive detector and the obstacle calculated based on the emission time of the detection signal and the reception time of the feedback signal is used as the position detection data, wherein the maximum value of the preset time range is less than a preset threshold.

[0074] A position-sensitive detector is installed on the self-moving device. During the movement of the self-moving device, the position-sensitive detector continuously emits detection signals to sense obstacles around the self-moving device. If the position-sensitive detector receives a feedback signal from the detection signal within a preset time range, it indicates that an obstacle has appeared within the detection range of the position-sensitive detector. Since the self-moving device only needs to detect obstacles that are relatively close through the position-sensitive detector, the preset time range is set to be relatively small, that is, the minimum value of the preset time range must be less than a preset threshold, to avoid the self-moving device detecting obstacles that are too far away and affecting the movement of the self-moving device. The distance between the obstacle and the self-moving device is calculated based on the difference between the transmission time and the reception time of the detection signal, and this distance is used as the position detection data.

[0075] Using the above scheme, a position-sensitive detector installed on the self-moving device continuously sends detection signals as the self-moving device moves, and receives feedback signals from the detection signals. Since the self-moving device is constantly moving and the detection range is small, a preset time range is set. Only when the feedback signal of the detection signal is received within the preset time range is the distance between the position-sensitive detector and the obstacle calculated, thereby collecting the position data of the obstacle.

[0076] Optionally, the fitting module 44 is further configured to continuously collect multiple position detection data during the movement of the self-moving device; calculate multiple second position coordinates of the obstacle based on the multiple position detection data, the first position coordinates, and the target direction, wherein the first position coordinates are used to indicate the position of the self-moving device when the position detection data is collected, the target direction is used to indicate the pose of the obstacle relative to the self-moving device when the position detection data is collected, and the multiple second position coordinates correspond one-to-one with the multiple position detection data; and perform curve fitting on the multiple second position coordinates using a preset fitting algorithm to obtain the fitted contour curve.

[0077] During the movement of the self-moving device, position detection data is continuously collected to more accurately obtain the outline of the obstacle. While moving, the self-moving device performs curve fitting based on the collected position detection data, so that the self-moving device can adjust its driving direction according to the latest obtained fitted outline curve of the obstacle. Curve fitting requires first obtaining multiple position coordinates of the obstacle (equivalent to the second position coordinates mentioned above). Based on the position coordinates of the self-moving device when the position detection data was collected (equivalent to the first position coordinates mentioned above), the multiple position detection data obtained, and the orientation of the obstacle relative to the self-moving device when the position detection data was collected (equivalent to the target direction mentioned above), the multiple position coordinates of the obstacle are determined. Then, a preset fitting algorithm is used to perform curve fitting on the multiple position coordinates to obtain the fitted outline curve.

[0078] Using the above scheme, multiple position detection data of obstacles are continuously collected during the movement of the self-moving device, and the first position coordinates of the self-moving device and the orientation of the obstacle relative to the self-moving device at the time of collection are determined to obtain multiple position coordinates of the obstacle. Curve fitting of these multiple position coordinates can obtain a fitted contour curve, thereby helping the self-moving device to identify the contour of the obstacle, so as to plan the driving route.

[0079] Based on the above steps, the fitting module 44 is further configured to perform curve fitting on the plurality of second position coordinates using a preset fitting algorithm to obtain the fitted contour curve, and then save the fitted contour curve to the map saved by the self-moving device, wherein the map already contains a plurality of fitted contour curves; when the self-moving device performs the next round of cleaning, a target fitted contour curve is determined from the plurality of fitted contour curves obtained in the map, wherein the target fitted contour curve is the fitted contour curve in the map that has the smallest distance to the self-moving device; and the self-moving device is controlled to adjust its driving route in the target obstacle area to the target fitted contour curve, wherein the target obstacle area is the area where the target obstacle is located, and the target fitted contour curve is the fitted contour curve obstacle corresponding to the target fitted contour curve.

[0080] After obtaining the fitted contour curve, the mobile device records the fitted contour curve in the mobile device's map, which stores all the fitted contour curves obtained by the mobile device in history. When the mobile device performs the next round of cleaning, it selects the fitted contour curve of the nearest obstacle (equivalent to the target fitted contour curve mentioned above) in the map based on its current position. When the mobile device travels to the area where the target fitted contour curve is located according to the original route, it will travel according to the fitted contour curve to clean the area around the obstacle and avoid missing any areas.

[0081] Using the above scheme, after obtaining the fitted contour curve of the obstacle, the fitted contour curve is stored in the map. When the self-moving device moves to the vicinity of the fitted contour curve during the next cleaning, the driving route of the self-moving device in the area where the fitted contour curve is located is adjusted to the fitted contour curve, thereby helping the self-moving device to drive along the edge of the obstacle and avoid missing the scan.

[0082] In an exemplary embodiment, the adjustment module 46 is further configured to determine whether the fitted contour curve is a closed shape; and if the fitted contour curve is a closed shape, to control the self-moving device to move away from the fitted contour curve.

[0083] During the process of adjusting the travel route of the self-moving device according to the fitted contour curve, the self-moving device collects position detection data while driving to perform curve fitting. That is, the fitted contour curve is constantly being updated and extended. If the self-moving device detects that the fitted contour curve has been extended into a closed shape, it means that the self-moving device has traveled around the obstacle, has completely identified the contour of the obstacle, and has completed the cleaning of the area where the obstacle is located in this round of cleaning. Then, the self-moving device can be controlled to move away from the obstacle corresponding to the fitted contour curve and clean other areas.

[0084] Using the above scheme, if the obtained fitted contour curve is a closed shape, it can be confirmed that the self-moving device has traveled around the obstacle once, that is, the self-moving device has completely cleaned the area around the obstacle and has collected the PSD data (equivalent to the above position detection data) around the obstacle. The self-moving device can then be controlled to move away from the obstacle to avoid repeated cleaning.

[0085] Based on the above steps, the fitting module 44 is further configured to determine whether the fitted contour curve is a closed shape, and if the fitted contour curve is a non-closed shape, extend the fitted contour curve according to the parameter information of the fitted contour curve, wherein the parameter information includes at least one of the following: curvature, length; and control the self-moving device to adjust the current driving route to the extended fitted contour curve.

[0086] If the fitted contour curve is identified as a non-closed shape, it means that the automatic device has not fully identified the obstacle and needs to continue moving along the obstacle. However, the automatic device has not recorded the PSD data (equivalent to the position detection data mentioned above) in front. Therefore, it is necessary to make a certain prediction based on the currently obtained fitted contour curve, extend the fitted contour curve according to its curvature and length, and control the automatic device to drive according to the extended fitted contour curve.

[0087] Using the above method, if it is determined that the fitted contour curve is not a closed shape, it is determined that the self-moving device has not yet completely identified the contour of the obstacle. In order for the self-moving device to better fit the obstacle and drive, the self-moving device will appropriately extend the fitted contour curve according to the parameter information of the fitted contour curve, so as to adjust the driving route of the self-moving device and enable the self-moving device to drive along the edge of the obstacle.

[0088] Optionally, the fitting module 44 is further configured to calculate a first shape and a first probability of the fitted contour curve based on the parameter information of the fitted contour curve, wherein the first probability is used to indicate the probability that the fitted contour curve is the first shape; determine a second shape corresponding to the second probability, wherein the second probability is the first probability with the largest value; and extend the fitted contour curve according to the second shape and the parameter information.

[0089] The fitting profile is extended based on the parameter information of the fitting profile curve, including the following steps: First, predict the possible shape of the fitting profile curve and the probability of each shape based on the curvature and length of the fitting profile curve. Then, determine the shape corresponding to the highest probability value among multiple probabilities as the shape of the fitting profile curve. Finally, extend the fitting profile curve based on the second shape and the curvature, length and other parameter information of the fitting profile curve.

[0090] For example, if the probability of the fitted contour curve being a rectangle is predicted to be 60%, a square to be 30%, and a circle to be 10%, then the fitted contour curve is identified as a rectangle, and the remaining length of the currently unidentified side is predicted based on the length of each side of the existing fitted contour curve, and the fitted contour curve is extended.

[0091] If the shape of the fitted profile curve is determined to be circular, the center and radius of the circle are calculated based on the length and curvature of the fitted profile curve. The length of the arc that has not yet been identified is predicted based on the obtained data, and the fitted profile curve is extended appropriately according to the current curvature and the predicted length.

[0092] This invention also provides a schematic diagram of the structure of an optional self-moving device, such as... Figure 5 As shown, it specifically includes:

[0093] The lidar sensor 52, also known as LDS (Laser Docking Sensor), is used by self-moving equipment to sense and measure distances in the surrounding environment.

[0094] The position-sensitive detector 54, also known as the PSD (Position Sensitive detector), is located on the right side of the self-moving device and is used by the self-moving device to collect the position data of obstacles for curve fitting.

[0095] It should be noted that the aforementioned position-sensitive detector 54 can be set on the right side of the self-moving device, or on the left side of the self-moving device, or in other locations of the self-moving device; this application does not impose any restrictions on this.

[0096] It should be noted that the aforementioned position-sensitive detector can be a single unit or multiple units; the figure is for illustrative purposes only, and this application does not impose any restrictions on this.

[0097] Those skilled in the art will understand that Figure 5 The structure shown is for illustrative purposes only and does not limit the structure of the self-moving device described above. For example, the self-moving device may also include components that are larger than... Figure 5 The more or fewer components shown, or having the same Figure 5 Equivalent functions or ratios shown Figure 5 The functions shown have more different configurations.

[0098] Through the aforementioned structure, the self-moving device, through the cooperation of its components, jointly completes the set cleaning tasks and can handle unexpected situations autonomously. For example, when obstacles appear in its path, it can adjust its route to clean the area around the obstacle, avoiding any missed spots. This device solves the problem in existing technologies where obstacle detection relies solely on side edge sensors, which cannot effectively perceive the obstacle's outline, leading to multiple collisions with obstacles during operation. It achieves accurate obstacle outline recognition, thereby helping the self-moving device adjust its direction.

[0099] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0100] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0101] S1, position detection data is collected during the movement of the self-moving device by a position sensitive detector, wherein the position detection data is used to indicate the distance between the position sensitive detector and the obstacle, and the position sensitive detector is set on the self-moving device;

[0102] S2, perform curve fitting based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle;

[0103] S3, adjust the driving route of the self-moving device according to the fitted contour curve.

[0104] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0105] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0106] Embodiments of the present invention also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0107] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0108] S1, position detection data is collected during the movement of the self-moving device by a position sensitive detector, wherein the position detection data is used to indicate the distance between the position sensitive detector and the obstacle, and the position sensitive detector is set on the self-moving device;

[0109] S2, perform curve fitting based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle;

[0110] S3, adjust the driving route of the self-moving device according to the fitted contour curve.

[0111] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0112] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0113] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0114] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A travel route adjustment method characterized by comprising: include: Position detection data is collected during the movement of the self-moving device by a position-sensitive detector, wherein the position detection data is used to indicate the distance between the position-sensitive detector and obstacles, and the position-sensitive detector is installed on the self-moving device; Curve fitting is performed based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle; The driving route of the self-moving device is adjusted according to the fitted contour curve; Adjusting the travel route of the self-moving device based on the fitted contour curve includes: Determine whether the fitted contour curve is a closed shape; When the fitted contour curve is a closed shape, control the self-moving device to move away from the fitted contour curve; After determining whether the fitted contour curve is a closed shape, the method further includes: When the fitted contour curve is a non-closed shape, the fitted contour curve is extended according to the parameter information of the fitted contour curve, wherein the parameter information includes at least one of the following: curvature and length; The self-moving device is controlled to adjust the current driving route to an extended fitted contour curve; The process of extending the fitted contour curve based on its parameter information includes: The first shape and first probability of the fitted contour curve are calculated based on the parameter information of the fitted contour curve, wherein the first probability is used to indicate the probability that the fitted contour curve is the first shape; Determine the second shape corresponding to the second probability, wherein the second probability is the first probability with the largest value; The fitted contour curve is extended based on the second shape and the parameter information.

2. The travel route adjustment method according to claim 1, characterized by, Location detection data is collected during the movement of the self-moving device using a location-sensitive detector, including: During the movement of the self-moving device, the position-sensitive detector is controlled to emit a detection signal; When the position-sensitive detector receives a feedback signal from the detection signal within a preset time range, the distance between the position-sensitive detector and the obstacle is calculated based on the transmission time of the detection signal and the reception time of the feedback signal, and the distance is used as the position detection data, wherein the maximum value of the preset time range is less than a preset threshold.

3. The travel route adjustment method according to claim 1, characterized by, Based on the position detection data, curve fitting is performed to obtain a fitted contour curve, including: Multiple location detection data are continuously collected during the movement of the self-moving device; Based on the multiple location detection data, the first location coordinates, and the target direction, multiple second location coordinates of the obstacle are calculated respectively. The first location coordinates are used to indicate the position of the self-moving device when the location detection data is collected, and the target direction is used to indicate the pose of the obstacle relative to the self-moving device when the location detection data is collected. The multiple second location coordinates correspond one-to-one with the multiple location detection data. A preset fitting algorithm is used to perform curve fitting on the plurality of second position coordinates to obtain the fitted contour curve.

4. The travel route adjustment method according to claim 3, characterized by, After performing curve fitting on the plurality of second position coordinates using a preset fitting algorithm to obtain the fitted contour curve, the method further includes: The fitted contour curve is saved to the map saved on the self-mobile device, wherein multiple fitted contour curves are already saved in the map; In the next round of cleaning when the self-moving device is performing the current cleaning, a target fitting profile curve is determined from multiple fitting profile curves obtained in the map, wherein the target fitting profile curve is the fitting profile curve with the smallest distance to the self-moving device stored in the map. The self-moving device is controlled to adjust its driving route in the target obstacle area to the target fitted contour curve, wherein the target obstacle area is the area where the target obstacle is located, and the target fitted contour curve is the fitted contour curve corresponding to the target obstacle.

5. A travel route adjustment device characterized by comprising: include: A data acquisition module is used to acquire position detection data during the movement of a self-moving device via a position-sensitive detector. The position detection data is used to indicate the distance between the position-sensitive detector and an obstacle. The position-sensitive detector is installed on the self-moving device. A fitting module is used to perform curve fitting based on the position detection data to obtain a fitted contour curve, wherein the fitted contour curve is used to indicate the contour of the obstacle. An adjustment module is used to adjust the driving route of the self-moving device according to the fitted contour curve; The adjustment module is further configured to determine whether the fitted contour curve is a closed shape. When the fitted contour curve is a closed shape, control the self-moving device to move away from the fitted contour curve; The fitting module is further configured to extend the fitted contour curve according to the parameter information of the fitted contour curve when the fitted contour curve is a non-closed shape, wherein the parameter information includes at least one of the following: curvature and length. The adjustment module is also used to control the self-moving device to adjust the current driving route to an extended fitted contour curve. The fitting module is further configured to calculate a first shape and a first probability of the fitted contour curve based on the parameter information of the fitted contour curve, wherein the first probability is used to indicate the probability that the fitted contour curve is the first shape. Determine the second shape corresponding to the second probability, wherein the second probability is the first probability with the largest value; The fitted contour curve is extended based on the second shape and the parameter information.

6. A computer readable storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the method described in any one of claims 1 to 4 when it is run. 7.An electronic device comprising a memory and a processor, the electronic device characterized by, The memory stores a computer program, and the processor is configured to run the computer program to perform the method described in any one of claims 1 to 4.

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