WO2022110928A1

WO2022110928A1 - Robot mapping method, robot, storage medium and electronic apparatus

Info

Publication number: WO2022110928A1
Application number: PCT/CN2021/114003
Authority: WO
Inventors: 田丰溥; 丘伟楠
Original assignee: 追觅创新科技(苏州)有限公司
Priority date: 2020-11-24
Filing date: 2021-08-23
Publication date: 2022-06-02
Also published as: CN114532898B; CN114532898A

Abstract

A robot mapping method, a robot, a storage medium and an electronic apparatus. The method comprises: searching an initial map of a target region for an unknown region satisfying a preset condition, the preset condition comprising at least one of the following: the area of the unknown region being greater than a preset threshold value, and a robot being allowed to reach the unknown region (S102); after the robot travels to the unknown region, controlling the robot to reconstruct a map in the unknown region, and updating the initial map according to the reconstructed map (S104); and when no unknown region satisfying the preset condition is found in the reconstructed map, using the currently reconstructed map as a mapping result of the robot (S106). By means of the method, the problem of the long exploration time for a robot during an autonomous exploration process is solved.

Description

Robot mapping method, robot, storage medium, electronic device

technical field

The present application relates to the field of communications, and in particular, to a method for mapping a robot, a robot, a storage medium, and an electronic device.

Background technique

In related technologies, how to explore robots in unknown fields is a research hotspot in the field of robotics. In the process of robot exploration, autonomous exploration technology usually requires the robot to have the capabilities of simultaneous localization and mapping (SLAM), so that the robot can build an environmental map in an unknown environment. At present, the main method used in related technologies is to arrange special signs in an unknown environment. However, this method takes a long time to conduct autonomous exploration, and has low efficiency and low success rate, which may cause the robot to fail to complete the autonomous exploration task. .

Aiming at the problems in related technologies, such as the long exploration time of robots in the process of autonomous exploration, no effective solutions have been proposed.

SUMMARY OF THE INVENTION

The embodiments of the present application provide a robot mapping method, a robot, a storage medium, and an electronic device, so as to at least solve the problem of a long exploration time of a robot in an autonomous exploration process in the related art.

According to an optional embodiment of the present application, a method for mapping a robot is provided, which includes: searching for an unknown area that satisfies a preset condition from an initial map of a target area, wherein the preset condition includes at least one of the following : The area of the unknown area is greater than the preset threshold, and the robot is allowed to reach the unknown area; after the robot travels to the unknown area, the robot is controlled to perform map reconstruction in the unknown area, and update all maps according to the reconstructed map. The initial map; in the case that the unknown area that meets the preset condition cannot be found in the reconstructed map, the current reconstructed map is used as the mapping result of the robot.

Optionally, before using the currently reconstructed map as a mapping result of the robot, the method further includes: cyclically executing the following steps: searching for an unknown area that satisfies a preset condition from the initial map of the target area, and controlling the robot After traveling to the unknown area, perform map reconstruction in the unknown area, and update the initial map according to the reconstructed map, until an unknown area that meets the preset conditions cannot be found in the reconstructed map .

Optionally, after controlling the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and after updating the initial map according to the reconstructed map, the method further includes: from the reconstructed The search range is determined from the map of , and the unknown area that satisfies the preset condition is searched from the search range, wherein the search range does not include: the search range that has been searched from the initial map and meets the preset condition the unknown area; control the robot to perform map reconstruction again in the unknown area searched from the search range, and update the reconstructed map according to the reconstructed map again.

Optionally, search for an unknown area that satisfies preset conditions from the initial map of the target area, control the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and update all the information according to the reconstructed map. The initial map includes: after updating the initial map according to the reconstructed map, determining a search range from the reconstructed map, and searching again from the search range for unknown unknowns that meet the preset conditions area, wherein the search range does not include: the unknown area that has been searched from the initial map that meets the preset conditions; the robot is controlled to map the unknown area searched from the search range again. Reconstructing, and updating the reconstructed map according to the re-reconstructed map, so as to search for an unknown area that satisfies the preset condition in the re-reconstructed map.

Optionally, searching for an unknown area that satisfies the preset condition from the initial map of the target area includes: setting a fixed shape of the unknown area, wherein the area of the fixed shape is greater than the preset threshold; According to the fixed shape, an unknown area that satisfies the preset condition is searched from the initial map of the target area.

Optionally, searching for an unknown area that satisfies the preset condition from an initial map of the target area includes: determining an edge area and a central area in the initial map of the target area, where the target area includes: the edge area and the center area; search for an unknown area that satisfies the preset condition from the edge area; after the edge area search is completed, search the center area for an unknown area that satisfies the preset condition area.

Optionally, after searching for an unknown area that satisfies the preset condition from the initial map of the target area, the method further includes: acquiring a navigation path for the robot to travel from the current position to the unknown area; The robot travels to the unknown area according to the navigation path.

Optionally, acquiring a navigation path for the robot to travel from the current position to the unknown area includes: determining at least one navigation path for the robot to travel from the current position to the unknown area; from the at least one navigation path A first navigation path that satisfies a preset rule is determined, wherein the preset rule includes: the travel cost is the smallest; and the robot is instructed to travel to an unknown area corresponding to the first navigation path according to the first navigation path.

Optionally, after searching for an unknown area that satisfies the preset condition from the initial map of the target area, the method further includes: in the case that there are multiple unknown areas that satisfy the preset condition, obtaining the robot. Travel from the current position to at least one navigation path of a plurality of unknown areas; determine a second navigation path that satisfies a preset rule from the at least one navigation path, wherein the preset rule includes: the travel cost is the smallest; according to the The second navigation path instructs the robot to travel to an unknown area corresponding to the second navigation path.

According to another embodiment of the present application, a robot is also provided, comprising: a processing module for searching an unknown area that satisfies a preset condition from an initial map of a target area, wherein the preset condition includes at least one of the following 1: The area of the unknown area is greater than the preset threshold, and the robot is allowed to reach the unknown area; control the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and update the map according to the reconstructed map the initial map; a determination module, configured to use the currently reconstructed map as the robot's mapping result when an unknown area that meets the preset condition cannot be found in the reconstructed map.

According to yet another embodiment of the present application, a storage medium is also provided, and a computer program is stored in the storage medium, wherein the computer program is configured to execute the steps in any one of the above method embodiments when running.

According to yet another embodiment of the present application, an electronic device is also provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any one of the above Steps in Method Examples.

Through this application, since the unknown area can be determined from the map of the target area, and then the unknown area is mapped, in the case where the unknown area that meets the preset conditions cannot be found in the map corresponding to the target area, the current reconstructed map of the robot As the mapping result of the robot, the unknown area in the map of the target area can be searched, and the mapping result of the robot is determined after all the unknown areas have been searched, and a new technical solution for autonomous exploration is provided. The above technical solution solves the problems in the related art that special signs are generally arranged in an unknown environment to realize the autonomous exploration process, but due to the complexity of the unknown environment and other reasons, the robot has a long exploration time in the autonomous exploration process. Furthermore, in the process of reconstructing the map of the target area by the robot, the time for autonomous exploration of the robot can be shortened, and the efficiency of autonomous exploration of the robot can be improved.

Description of drawings

The drawings described herein are used to provide further understanding of the present application and constitute a part of the present application. The schematic embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation of the present application. In the attached image:

Fig. 1 is a hardware structure block diagram of a robot according to a method for constructing a robot according to an embodiment of the present application;

FIG. 2 is a flowchart of a method for constructing a map of a robot according to an embodiment of the present application;

3 is a structural block diagram of a robot according to an embodiment of the present application;

FIG. 4 is a schematic flowchart of a method for mapping a robot according to an optional embodiment of the present application.

Detailed ways

Hereinafter, the present application will be described in detail with reference to the accompanying drawings and in conjunction with the embodiments. It should be noted that the embodiments in the present application and the features of the embodiments may be combined with each other in the case of no conflict.

It should be noted that the terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence.

The method embodiments provided in the embodiments of the present application may be executed in a robot or a similar computing device. Taking running on a robot as an example, FIG. 1 is a hardware structural block diagram of a robot according to a method for constructing a robot in an embodiment of the present application. As shown in FIG. 1 , the robot may include one or more (only one is shown in FIG. 1 ) processors 102 (the processors 102 may include, but are not limited to, a Microprocessor Unit (MPU) or a programmable logic device for short) (Programmable logic device, abbreviated as PLD) etc. and the memory 104 for storing data, optionally, the above-mentioned robot may also include a transmission device 106 and an input and output device 108 for communication functions. Those of ordinary skill in the art It can be understood that the structure shown in Fig. 1 is only for illustration, and it does not limit the structure of the above-mentioned robot. For example, the robot may also include more or less components than those shown in Fig. 1, or have different components than those shown in Fig. 1 Equivalent function or a different configuration with more functions than shown in Figure 1.

The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer programs corresponding to the method for constructing the robot in the embodiments of the present application. Executing various functional applications and data processing implements the above-mentioned methods. 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 examples, memory 104 may further include memory located remotely from processor 102, which may be connected to robot 10 through a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

The transmission device 106 is used to receive or transmit data via the network. The specific example of the above-mentioned network may include a wireless network provided by the communication provider of the robot 10 . In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC for short), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (Radio Frequency, RF for short) module, which is used to communicate with the Internet in a wireless manner.

This embodiment provides a method for building a map that runs on the above-mentioned robot. FIG. 2 is a flowchart of a method for building a map for a robot according to an embodiment of the present application. As shown in FIG. 2 , the process includes the following steps:

Step S102, searching for an unknown area that satisfies the preset condition from the initial map of the target area, wherein the preset condition includes at least one of the following: the area of the unknown area is greater than a preset threshold, and the robot is allowed to reach the unknown area;

It should be noted that the above preset condition is a limitation on the area of the unknown area and whether the robot can reach it. In actual operation, other limitations may also be made on the above preset condition, which is not limited in the embodiments of the present application. .

It can be understood that the initial map of the target area is a preliminary map established by the SLAM module after the robot reaches an unknown area. The robot can subsequently search for the unknown area according to the preliminary map, and reconstruct and update the map.

Step S104, control the robot to carry out map reconstruction in the unknown area after traveling to the unknown area, and update the initial map according to the reconstructed map;

Step S106, in the case that an unknown area that meets the preset condition cannot be found in the reconstructed map, the currently reconstructed map is used as the mapping result of the robot.

Through the above technical solution, since the unknown area can be determined from the map of the target area, and then the unknown area is mapped, in the case where the unknown area that meets the preset conditions cannot be found in the map corresponding to the target area, the current reconstruction of the robot is carried out. The map is used as the mapping result of the robot, that is, the unknown area in the map of the target area can be searched. After all the unknown areas are searched, the mapping result of the robot is determined, and a new technical solution for autonomous exploration is provided. The above technical solution solves the problem that in related technologies, special signs are generally arranged in an unknown environment to realize the autonomous exploration process. However, due to the complexity of the unknown environment and other reasons, the robot has a long exploration time in the autonomous exploration process. , which can shorten the time of autonomous exploration of the robot and improve the efficiency of autonomous exploration of the robot in the process of reconstructing the map of the target area.

In the embodiment of the present application, in order to perform the map reconstruction process of the robot more accurately, the above steps S102 and S104 may be executed cyclically: searching for an unknown area that satisfies the preset conditions from the initial map of the target area, and controlling the robot After traveling to the unknown area, map reconstruction is performed in the unknown area, and the initial map is updated according to the reconstructed map, until an unknown area that meets the preset conditions cannot be found in the reconstructed map.

That is to say, steps S102 and 104 may be performed once, or may be performed repeatedly in a loop, until there is no more unknown area that meets the preset conditions in the map of the target area.

In order to save the autonomous exploration time of the robot during the autonomous exploration process, the robot is controlled to perform map reconstruction in the unknown region after traveling to the unknown region, and after updating the initial map according to the reconstructed map, the The method further includes: determining a search range from the reconstructed map, and searching for an unknown area that satisfies the preset condition from the search range, wherein the search range does not include: The searched unknown area that meets the preset condition can also be understood as the initial map including: the search range, and the unknown area that meets the preset condition searched from the initial map; The robot performs map reconstruction again in the unknown area searched from the search range, and updates the reconstructed map according to the reconstructed map again.

That is to say, after the map reconstruction of the unknown area, when the unknown area is determined next time, the unknown area that has been determined last time can be used as the known area, that is, the unknown area that has been determined last time is not searched, in short , the search range of the unknown area that meets the preset conditions in the next search does not include the unknown area that has been determined last time. Through such a technical solution, the content of the map of the unknown area determined in each cycle will actually be updated. The unknown area for map reconstruction is searched again, so that all unknown areas can be effectively and accurately reconstructed, without repeating the work, saving the robot's autonomous exploration time.

In addition, during the cyclic execution of steps S102 to S104, an unknown area that satisfies the preset conditions is searched from the initial map of the target area, and the robot is controlled to perform a map in the unknown area after traveling to the unknown area. The cyclic process of reconstructing and updating the initial map according to the reconstructed map may include the following technical solution: after updating the initial map according to the reconstructed map, determining a search range from the reconstructed map , and search for the unknown area that satisfies the preset condition from the search range again, wherein the search range does not include: the unknown area that has been searched from the initial map that satisfies the preset condition; control The robot performs map reconstruction again in the unknown area searched from the search range, and updates the reconstructed map according to the re-reconstructed map, so as to search for the re-reconstructed map that satisfies the predetermined conditions. Unknown region to set conditions.

It should be noted that, in the specific loop process, the process of searching for the unknown area is performed repeatedly until the unknown area that meets the preset conditions cannot be found in the map of the target area.

In the above step S102, there may be various ways to determine the unknown area that satisfies the preset condition. In an optional embodiment, searching for the unknown area that satisfies the preset condition from the initial map of the target area mainly includes Do this by:

The first implementation

A fixed shape of the unknown area is set, wherein the area of the fixed shape is greater than the preset threshold; an unknown area that satisfies the preset condition is searched from the initial map of the target area according to the fixed shape.

That is, the unknown area can be set to a fixed shape, and the area of the fixed shape is set to a fixed value greater than the preset threshold, and then the unknown area that meets the preset conditions can be determined cyclically from the map of the target area according to this fixed shape, for example , you can set the fixed shape of the unknown area to be a rectangle, or a circle or other shapes that can be set, and then you can explore the target area piece by piece according to the unknown area of this fixed shape. The above threshold can be set according to the actual operation experience. Meter to 0.04 square meters, which can avoid searching for an unknown area surrounded by a known area during map search, so as to perform many unnecessary navigations, resulting in a waste of time and cost.

The second implementation

Determine the edge area and the center area in the initial map of the target area, where the target area includes: the edge area and the center area; search for an unknown area that satisfies the preset condition from the edge area ; after the edge area search is completed, search for an unknown area that satisfies the preset condition from the center area.

That is, in the embodiment of the present application, the edge area and the center area corresponding to the target area can be determined. After the edge area is explored, the center area can be explored. For the determination process of the edge area and the center area, the target area can be An area formed by extending the edge of the map to the central area for a certain area is used as the above-mentioned edge area, and further, the area in the map corresponding to the target area other than the edge area is used as the above-mentioned central area.

In another optional embodiment, after the edge area and the center area are determined, the center area can be explored first, and then the edge area can be explored. The embodiments do not limit the above process.

In the embodiment of the present application, after searching for an unknown area that satisfies the preset condition from the initial map of the target area, the method further includes: acquiring a navigation path for the robot to travel from the current position to the unknown area ; control the robot to travel to the unknown area according to the navigation path.

It can be seen that after each unknown area is determined, the robot needs to locate and determine its current position, and then obtain the navigation path from the current position to the unknown area, and then control the robot to travel from the current position to the unknown area.

In the actual operation process, there may be only one determined unknown area, but there is at least one path from the current position to the unknown area. In this application scenario, the navigation of the robot from the current position to the unknown area is obtained. The path can be achieved by: determining at least one navigation path for the robot to travel from the current position to the unknown area; determining a first navigation path that satisfies a preset rule from the at least one navigation path, wherein the The preset rules include: the travel cost is the smallest; and the robot is instructed to travel to the unknown area corresponding to the first navigation path according to the first navigation path.

It should be noted that the walking cost refers to the cost calculated by the robot according to the map search module according to the path length from the current position to the target position, obstacle information, and the like. That is, there is at least one navigation path when the robot travels from the current position to the unknown area, the first navigation path is the one with the smallest travel cost, and the robot travels to the unknown area according to the first navigation path.

There may also be a situation where there are multiple unknown areas that meet the preset conditions, and the robot needs to select an unknown area with the smallest walking cost. That is to say, the unknown area that satisfies the preset conditions is In the case of more than one, obtain at least one navigation path for the robot to travel from the current position to a plurality of unknown areas; determine a second navigation path that satisfies a preset rule from the at least one navigation path, wherein the preset The rules include: the travel cost is the smallest; and the robot is instructed to travel to the unknown area corresponding to the second navigation path according to the second navigation path.

In an optional embodiment, during the process of the robot performing the above automatic exploration, the target device used with the robot can be uninterrupted or send a recharge signal according to a preset period, then when the robot detects the recharge signal , and when the robot is successfully positioned, the robot is controlled to travel to the target device that sends the recharge signal. In one example, the target device may be a charging base.

From the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is better implementation. Based on this understanding, the technical solutions of the present application can be embodied in the form of software products in essence or the parts that make contributions to the prior art. Memory, referred to as ROM), Random Access Memory (Random Access Memory, referred to as RAM), magnetic disk, optical disk), including several instructions to make a terminal device (can be a mobile phone, computer, server, or network device) etc.) to perform the methods described in the various embodiments of the present application.

In this embodiment, a robot is also provided, and the robot is used to implement the above-mentioned embodiments and preferred implementations, and what has been described will not be repeated. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, implementations in hardware, or a combination of software and hardware, are also possible and contemplated.

3 is a structural block diagram of a robot according to an embodiment of the present application. As shown in the figure, the device includes:

The processing module 30 is configured to search for an unknown area that meets preset conditions from the initial map of the target area, and control the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and based on the reconstructed map Updating the initial map, the preset conditions include at least one of the following: the area of the unknown area is greater than a preset threshold, and the robot is allowed to reach the unknown area;

The determining module 32 is configured to use the currently reconstructed map as a mapping result of the robot in the event that an unknown area that meets the preset condition cannot be found in the reconstructed map.

It should be noted that the above processing modules may include: a map search module, a navigation module, a SLAM module, and a decision-making module in the robot, which are not limited in this embodiment of the present application.

Optionally, the processing module 30 is further configured to perform the following steps cyclically: searching for an unknown area that satisfies a preset condition from the initial map of the target area, and controlling the robot to proceed in the unknown area after traveling to the unknown area. The map is reconstructed, and the initial map is updated according to the reconstructed map, until an unknown area that meets the preset condition cannot be found in the reconstructed map.

Optionally, in order to save the autonomous exploration time of the robot in the autonomous exploration process, the processing module 30 is further configured to determine a search range from the reconstructed map, and search for a search range that satisfies the preset conditions from the search range. Unknown area, wherein the search range does not include: the unknown area that meets the preset condition has been searched from the initial map, it can also be understood that the initial map includes: the search range, and The unknown area that meets the preset conditions found in the initial map; controls the robot to perform map reconstruction again in the unknown area searched from the search range, and updates the reconstructed map according to the re-reconstructed map. map.

Optionally, the processing module 30 is further configured to, after updating the initial map according to the reconstructed map, determine a search range from the reconstructed map, and search again from the search range to meet the predetermined requirements. Unknown area with set conditions, wherein the search range does not include: unknown areas that have been searched from the initial map that meet the preset conditions; unknown areas that control the robot to search from the search range The map is reconstructed again in the area, and the reconstructed map is updated according to the reconstructed map, so as to search for an unknown area that satisfies the preset condition in the reconstructed map.

It should be noted that, in the specific loop process, the process of searching for the unknown area is performed cyclically multiple times until the unknown area that meets the preset conditions cannot be found in the map of the target area.

Optionally, the map search module included in the processing module 30 searches for an unknown area that satisfies the preset conditions from the map corresponding to the target area, which can be implemented mainly in the following ways:

The first implementation

The processing module 30 is further configured to set a fixed shape of the unknown area, wherein the area of the fixed shape is greater than the preset threshold; search for the initial map of the target area according to the fixed shape that satisfies the preset Unknown region of the condition.

The second implementation

The processing module 30 is further configured to determine an edge area and a center area in the initial map of the target area, wherein the target area includes: the edge area and the center area; The unknown area of the preset condition is searched; after the edge area search is completed, the unknown area that satisfies the preset condition is searched from the central area.

In another optional embodiment, the processing module 30 may also, after determining the edge area and the center area, explore the center area first, and then explore the edge area. Specifically, the center area of the center area may be used as a starting point, and the exploration may be expanded outward. , the above process is not limited in the embodiments of the present application.

Optionally, the processing module 30 is further configured to acquire a navigation path for the robot to travel from the current position to the unknown area; and control the robot to travel to the unknown area according to the navigation path.

Optionally, in the actual operation process, there may be only one determined unknown area, but there is at least one path from the current position to the unknown area. In this application scenario, the processing module 30 is also used to determine the robot from At least one navigation path from the current position to the unknown area; determining a first navigation path that satisfies a preset rule from the at least one navigation path, wherein the preset rule includes: the travel cost is the smallest; according to the first navigation path A navigation path instructs the robot to travel to an unknown area corresponding to the first navigation path.

It should be noted that the walking cost refers to the cost calculated by the machine according to the map search module according to the path length from the current position to the target position, obstacle information, and the like. That is, there is at least one navigation path when the robot travels from the current position to the unknown area, the first navigation path is the one with the smallest travel cost, and the robot travels to the unknown area according to the first navigation path.

Optionally, there may be a situation where there is at least one unknown area that satisfies the preset conditions determined, and the robot needs to select an unknown area with the smallest walking cost, that is, when the preset conditions are met. In the case that there are multiple unknown areas, the processing module 30 is further configured to acquire at least one navigation path for the robot to travel from the current position to the multiple unknown areas when there are multiple unknown areas that satisfy the preset condition; A second navigation path satisfying a preset rule is determined from the at least one navigation path, wherein the preset rule includes: the travel cost is the smallest; instructing the robot to travel to the second navigation path according to the second navigation path The unknown area corresponding to the path.

In an optional embodiment, during the process of the robot performing the above automatic exploration, the target device used with the robot can be uninterrupted, or send a recharge signal according to a preset period, then the processing module is also used for When the robot detects the recharging signal, and the robot is successfully positioned, the robot is controlled to travel to the target device that issued the recharging signal. In one example, the target device may be a charging base.

In order to better understand the mapping process of the above-mentioned robot, the above-mentioned technical solutions are explained below with reference to optional embodiments.

An optional embodiment of the present application takes a self-moving robot (for example, a sweeping robot) as an example. In the application process of the cleaning robot, an autonomous exploration scheme is usually used to discover special signs, signals, etc. existing in the environment. However, under this scheme, The self-moving robot has a long exploration time and an unsatisfactory exploration success rate, which leads to a situation where the robot's mapping efficiency is low or even cannot be constructed. In order to solve this technical problem, an optional embodiment of the present application provides the following technical solutions:

An optional embodiment of the present application provides a technical solution for autonomous exploration and mapping of a self-moving robot, including the following steps:

Step 1: Use the map search module to find an unknown area in the map with an area not less than a preset threshold and passable by the self-moving robot with the smallest walking cost.

It should be noted that in this step, the map can be the initial map of the target area, for example, the initial map obtained by the cleaning robot through the SLAM module after the user places the cleaning robot in the target area for the first time, the map can refer to the bedroom, or the living room. For the corresponding map, select an area larger than a certain threshold from the above-mentioned target areas, and there is no object such as glass to block, and pass through an unknown area whose distance is larger than the width of the robot. As for whether the walking cost is the smallest, the optional embodiments of this application may not be limited. , if the matching area is greater than a certain threshold and there is no object such as glass blocking, passing through an unknown area with a distance greater than the width of the robot, even if the walking cost is the largest, such a target area can be identified as eligible.

In an optional embodiment of the present application, the preset threshold may be taken from a value range of 0.0025 square meters to 0.04 square meters. This method can avoid that in step 1, the map search module searches an unknown area surrounded by a known area, thereby carrying out many unnecessary navigations, causing a waste of time cost; what the walking cost corresponds to is that the robot is based on the map search module according to the current The cost calculated by the path length, obstacle information, etc., from the position to the target position.

Step 2: Control the robot to go to the unknown area determined in step 1 through the navigation module, and then the SLAM module synchronously updates the map and its own pose.

Step 3: Repeat the above steps 1 and 2 until the map search module can no longer find a new passable unknown area. At this time, the latest map reconstructed by the SLAM module is used as the mapping result obtained by the robot's autonomous exploration of the target area. .

In the process of determining the unknown area in the above step 1, in order to improve the efficiency of autonomous exploration and reduce the time required for the autonomous exploration process, the decision-making module will determine the exploration location of the unknown area in real time according to the update of the map (it can be understood as search range for unknown areas).

For example: after the robot goes to the unknown area calculated in step I, it reconstructs the map, then in the next process of determining the unknown area that meets the preset conditions, the original unknown area is updated to the known area, and the robot will return to the Step I recalculates the new unknown region. This behavior saves time and cost, and also effectively avoids collisions when there are obstacles in the unknown area.

In addition, since the charging base corresponding to the robot will continuously send out signals, during the above steps 1 and 2, if the recharging sensor in the robot detects the recharging signal of the charging base in real time, the detected conditions will be met. Exit the current exploration process, and then control the robot to return to the position corresponding to the charging base.

For the above-mentioned determination process of the unknown area, it can be implemented by one of the following schemes:

1) A fixed exploration range is set in advance, and autonomous exploration is carried out within the fixed exploration range each time, and the entire target area is explored piece by piece according to the fixed exploration range (which can be understood as an unknown area). The fixed exploration range can be, for example, a rectangle with a predetermined size. It can be seen that, since the unknown area to be explored by the robot is fixed, a unified search program can be set for the robot to conduct autonomous exploration in the map according to the fixed search range, saving energy. Time to explore on your own.

2) First explore the unknown area along the edge (that is, the edge of the wall, etc.), and after the map boundary is closed, the interior of the boundary is explored. The embodiment of the present application can be understood as first exploring the edge area according to a unified processing method, and then exploring the center. area to explore.

FIG. 4 is a schematic flowchart of a method for mapping a robot according to an optional embodiment of the present application, as shown in FIG. 4 , including:

It should be noted that the sequence numbers of the steps in the following drawings are not used to limit the execution order of the steps, but are only used to explain the technical solutions of the optional embodiments of the present application. In the actual operation process, the execution order of some steps can be exchanged.

Step S402: the SLAM module is initialized;

Step S404: the SLAM module acquires or updates the map of the target area;

Step S406: The map search module searches for an unknown area in the map whose area is not less than a certain threshold and the robot can pass through, with the smallest walking cost;

Step S408: The robot exits the autonomous exploration process when it judges that there is no unknown area in the target area; it can be understood that the autonomous exploration process can be understood as including searching for an unknown area in the map, driving to the unknown area, and finding the unknown area. In the process of building a map, when it is judged that there is an unknown area in the storage target area, step S410 is performed;

Step S410: after the navigation module determines the unknown area, calculates the navigation path from the current position of the robot to the unknown area in real time;

Step S412: During the actual driving process of the robot, if the unknown area is found to be unreachable, step S410 is performed to determine a new path that may reach the unknown area. If the unknown area is reachable, after the unknown area is reconstructed, step S410 is performed. S404.

It should be noted that during the execution of the above steps, if the recharge sensor in the robot detects a recharge signal, it will exit the current autonomous exploration process.

It should be noted that the above modules can be implemented by software or hardware, and the latter can be implemented in the following ways, but not limited to this: the above modules are all located in the same processor; or, the above modules can be combined in any combination The forms are located in different processors.

Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored in the storage medium, wherein the computer program is configured to execute the steps in any one of the above method embodiments when running.

Optionally, in this embodiment, the above-mentioned storage medium may be configured to store a computer program for executing the following steps:

S1, searching for an unknown area that satisfies a preset condition from an initial map of the target area, wherein the preset condition includes at least one of the following: the area of the unknown area is greater than a preset threshold, and the robot is allowed to reach the unknown area;

S2, control the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and update the initial map according to the reconstructed map;

S3 , in the case that an unknown area that meets the preset condition cannot be found in the reconstructed map, use the currently reconstructed map as a mapping result of the robot.

Optionally, in this embodiment, the above-mentioned storage medium may include, but is not limited to: U disk, read-only memory ROM, random access memory RAM, removable hard disk, magnetic disk or optical disk and other media that can store computer programs.

Embodiments of the present application further provide an electronic device, including a memory and a processor, where a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

Optionally, the above-mentioned electronic device may further include a transmission device and an input-output device, wherein the transmission device is connected to the above-mentioned processor, and the input-output device is connected to the above-mentioned processor.

Optionally, in this embodiment, the above-mentioned processor may be configured to execute the following steps through a computer program:

Optionally, for specific examples in this embodiment, reference may be made to the examples described in the foregoing embodiments and optional implementation manners, and details are not described herein again in this embodiment.

Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present application can be implemented by a general-purpose computing device, and they can be centralized on a single computing device, or distributed in a network composed of multiple computing devices Alternatively, they may be implemented in program code executable by a computing device, such that they may be stored in a storage device and executed by the computing device, and in some cases, in a different order than here The steps shown or described are performed either by fabricating them separately into individual integrated circuit modules, or by fabricating multiple modules or steps of them into a single integrated circuit module. As such, the present application is not limited to any particular combination of hardware and software.

The above descriptions are only preferred embodiments of the present application, and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the principles of this application shall be included within the protection scope of this application.

Claims

A method for mapping a robot, comprising:

Searching for an unknown area that satisfies a preset condition from the initial map of the target area, wherein the preset condition includes at least one of the following: the area of the unknown area is greater than a preset threshold, and the robot is allowed to reach the unknown area;

control the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and update the initial map according to the reconstructed map;

In the case that an unknown area that meets the preset condition cannot be found in the reconstructed map, the currently reconstructed map is used as the mapping result of the robot.
The method according to claim 1, characterized in that before using the currently reconstructed map as the mapping result of the robot, the method further comprises:

The following steps are performed cyclically: searching for an unknown area that satisfies preset conditions from the initial map of the target area, controlling the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and updating according to the reconstructed map From the initial map, until the reconstructed map fails to find an unknown area that meets the preset condition.
The method according to claim 1, wherein the robot is controlled to perform map reconstruction in the unknown area after traveling to the unknown area, and after updating the initial map according to the reconstructed map, the Methods also include:

A search range is determined from the reconstructed map, and an unknown area that satisfies the preset condition is searched from the search range, wherein the search range does not include: the search range from the initial map that satisfies the preset condition is not included. the unknown area of the preset condition;

The robot is controlled to perform map reconstruction again in the unknown area searched from the search range, and the reconstructed map is updated according to the reconstructed map again.
The method according to claim 2, characterized in that, searching for an unknown area that satisfies a preset condition from an initial map of the target area, and controlling the robot to perform map reconstruction in the unknown area after traveling to the unknown area , and update the initial map according to the reconstructed map, including:

After the initial map is updated according to the reconstructed map, a search range is determined from the reconstructed map, and an unknown area that satisfies the preset condition is searched again from the search range, wherein the The search range does not include: the unknown area that has been searched from the initial map and meets the preset condition;

Controlling the robot to perform map reconstruction again in the unknown area searched from the search range, and updating the reconstructed map according to the reconstructed map, so as to search the reconstructed map to meet the requirements of the Unknown areas of preset conditions.
The method according to claim 1, wherein searching for an unknown area that satisfies the preset condition from an initial map of the target area comprises:

setting the shape of the unknown region as a fixed shape, wherein the area of the fixed shape is greater than the preset threshold;

According to the fixed shape, an unknown area that satisfies the preset condition is searched from the initial map of the target area.
The method according to claim 1, wherein searching for an unknown area that satisfies the preset condition from an initial map of the target area comprises:

Determine the edge area and the center area in the initial map of the target area, wherein the target area includes: the edge area and the center area;

Searching for an unknown area that satisfies the preset condition from the edge area;

After the edge area search is completed, an unknown area that satisfies the preset condition is searched from the center area.
The method according to claim 1, characterized in that after searching for an unknown area that satisfies the preset condition from the initial map of the target area, the method further comprises:

obtaining the navigation path of the robot from the current position to the unknown area;

The robot is controlled to travel to the unknown area according to the navigation path.
The method according to claim 7, wherein acquiring the navigation path of the robot from the current position to the unknown area comprises:

determining at least one navigation path for the robot to travel from the current location to the unknown area;

A first navigation path that satisfies a preset rule is determined from the at least one navigation path, wherein the preset rule includes: the travel cost is the smallest;

According to the first navigation path, the robot is instructed to travel to the unknown area corresponding to the first navigation path.
The method according to claim 1, characterized in that after searching for an unknown area that satisfies the preset condition from the initial map of the target area, the method further comprises:

In the case that there are multiple unknown areas satisfying the preset condition, acquiring at least one navigation path for the robot to travel from the current position to the multiple unknown areas;

A second navigation path that satisfies a preset rule is determined from the at least one navigation path, wherein the preset rule includes: minimum travel cost;

According to the second navigation path, the robot is instructed to travel to the unknown area corresponding to the second navigation path.
A robot, characterized in that it includes:

The processing module is used to search for an unknown area that meets preset conditions from the initial map of the target area, control the robot to perform map reconstruction in the unknown area after traveling to the unknown area, and update according to the reconstructed map In the initial map, the preset conditions include at least one of the following: the area of the unknown area is greater than a preset threshold, and the robot is allowed to reach the unknown area;

A determination module, configured to use the currently reconstructed map as a mapping result of the robot when an unknown area that meets the preset condition cannot be found in the reconstructed map.
A computer-readable storage medium, characterized in that a computer program is stored in the storage medium, wherein the computer program is configured to execute the method described in any one of claims 1 to 9 when running .
An electronic device comprising a memory and a processor, characterized in that, a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of the claims 1 to 9. method described.