CN115344034A - Intelligent cleaning robot path planning method and intelligent cleaning device - Google Patents
Intelligent cleaning robot path planning method and intelligent cleaning device Download PDFInfo
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Abstract
The application discloses an intelligent cleaning robot path planning method and an intelligent cleaning device, relates to the technical field of intelligent cleaning, and solves the problems that a cleaning robot in the prior art cannot automatically judge the position of the cleaning robot and cannot mark out an optimal cleaning route without regulations. The method comprises the steps of acquiring real-time position information under the condition of a known environment map, and sending the real-time position information to a control terminal; receiving the optimal cleaning path sent by the control terminal, and cleaning according to the optimal cleaning path; when an obstacle is encountered in the optimal cleaning path, recording the position information of the obstacle and sending the position information to the control terminal; and receiving an obstacle avoidance strategy sent by the control terminal, and completing a cleaning task. By adopting the intelligent cleaning robot path planning method and the intelligent cleaning device, the automatic recording of a map, the judgment of the position of the robot and the planning of the optimal cleaning route can be realized.
Description
Technical Field
The application relates to the technical field of intelligent cleaning, in particular to a path planning method for an intelligent cleaning robot and an intelligent cleaning device.
Background
At present, the known cleaning robot can generally set time for scheduled cleaning and self-charging. A sensor is arranged in front of the robot, can detect obstacles, can automatically turn when detecting walls or other obstacles, and can drive and plan cleaning areas according to different judgment mechanisms and according to different manufacturer settings. Most of sweeping robots in the market at present adopt a random path sweeping mode without accurate positioning, the sweeping area coverage rate is low, the time consumption is long, the efficiency is low, the missing sweeping and the repeated sweeping of partial rooms and corners are easy to occur, and the time consumption for cleaning is long. Although the sweeping robot adopting the improved algorithm planning optimizes the arch-shaped sweeping mode, the sweeping robot is random in nature because of no positioning in the implementation mode, and has higher price and lower performance price.
Disclosure of Invention
The embodiment of the application provides an intelligent cleaning robot path planning method and an intelligent cleaning device, solves the problems that a cleaning robot in the prior art cannot automatically judge the position of the cleaning robot and an optimal cleaning route is planned without regulations, and realizes automatic recording of a map to judge the position of the cleaning robot and plan the optimal cleaning route.
In a first aspect, an embodiment of the present invention provides an intelligent cleaning robot path planning method, including:
when the mobile terminal is in a known environment map, acquiring real-time position information, and sending the real-time position information to a control terminal, wherein the control terminal is used for comparing the real-time position information with the known environment map, establishing new environment map information, and planning an optimal cleaning path;
receiving the optimal cleaning path sent by the control terminal, and cleaning according to the optimal cleaning path;
when an obstacle is encountered in the optimal cleaning path, recording the position information of the obstacle and sending the position information to the control terminal; the control terminal is used for making an obstacle avoidance strategy according to the received position information of the obstacle;
and receiving the obstacle avoidance strategy sent by the control terminal, and completing the cleaning task.
Further, the obtaining the real-time location information and sending the real-time location information to the control terminal includes:
acquiring real-time position information through an ultrasonic sensor and an infrared sensor, and sending the real-time position information to a control terminal;
when the real-time position information is consistent with the known environment map information, planning an optimal cleaning path according to the known environment map information;
and when the real-time position information is inconsistent with the known environment map information, redrawing the environment map according to a threshold value, and planning an optimal cleaning path according to the new environment map information.
Further, the receiving the obstacle avoidance policy sent by the control terminal and completing the cleaning task includes:
receiving an obstacle avoidance strategy sent by the control terminal;
tracking the contour of an obstacle, and driving to a target point immediately when the obstacle can move directly to the target point; and when the mobile robot cannot directly move to the target point, if the path reaching the target point does not exist, replanning the route, and repeating the steps until the cleaning task is completed.
Still further, the intelligent cleaning robot path planning method further includes:
when the mobile terminal is in the condition of an unknown environment map, acquiring environment perception characteristics and carrying out local positioning;
the environment perception feature and the local positioning information are sent to the control terminal, and the control terminal is used for judging and positioning inflection point endpoint coordinates according to the environment perception feature and the local positioning information and establishing local map information;
and cleaning according to a planned route in the local map information.
Further, the acquiring the environmental perception feature and the locally positioning include:
the environmental perception characteristics are obtained through the ultrasonic sensor, and local positioning is carried out through serial connection of environmental topology nodes.
Furthermore, the environment topological nodes adopt geometric expressions, and meanwhile, the consistency of the environment map expression is maintained.
Further, acquiring the environment perception feature comprises extracting the environment feature, establishing a corner vertical line segment, judging and positioning the endpoint coordinate of the corner according to an empirical threshold.
In a second aspect, an embodiment of the present invention provides an intelligent cleaning device, including:
the system comprises an acquisition module, a control terminal and a data processing module, wherein the acquisition module is used for acquiring real-time position information and sending the real-time position information to the control terminal, and the control terminal is used for comparing the real-time position information with a known environment map, establishing new environment map information and planning an optimal cleaning path;
the receiving module is used for receiving the optimal cleaning path sent by the control terminal and cleaning according to the optimal cleaning path;
the obstacle avoidance module is used for recording the position information of the obstacle and sending the position information to the control terminal when the obstacle is encountered in the optimal cleaning path; the control terminal is used for making an obstacle avoidance strategy according to the received position information of the obstacle;
and the driving module is used for receiving the obstacle avoidance strategy sent by the control terminal and completing the cleaning task.
In a third aspect, an embodiment of the present invention provides a server, where the server includes: a memory and a processor;
the memory is to store program instructions;
the processor is used for executing program instructions in the server, so that the server executes the intelligent cleaning robot path planning method.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where executable instructions are stored in the computer-readable storage medium, and when the executable instructions are executed by a computer, the method for planning a path of an intelligent cleaning robot can be implemented.
One or more technical schemes provided in the embodiments of the present invention have at least the following technical effects or advantages:
according to the path planning method for the intelligent cleaning robot, provided by the embodiment of the invention, when the intelligent cleaning robot is in a known environment map, the intelligent cleaning robot positions the intelligent cleaning robot to obtain the real-time position information, uploads the real-time position information to the control terminal, plans the optimal cleaning route through the control terminal, and cleans according to the optimal cleaning route, so that the cleaning robot is ensured to achieve the optimal cleaning efficiency within the limited working time and the cleaning time is shortest. When an obstacle is encountered in the cleaning process, the intelligent cleaning robot records and sends the position information of the obstacle to the control terminal, then the control terminal works out an obstacle avoidance strategy according to the received information, and then the intelligent cleaning robot finishes cleaning the optimal cleaning path according to the obstacle avoidance strategy. By adopting the intelligent cleaning robot path planning method, the problems that the cleaning robot in the prior art cannot automatically judge the position of the cleaning robot and an optimal cleaning route is planned without regulations are effectively solved, and the automatic recording of a map to judge the position of the cleaning robot and the planning of the optimal cleaning route are realized.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a first schematic flow structure diagram of a path planning method for an intelligent cleaning robot according to an embodiment of the present disclosure;
fig. 2 is a schematic flow structure diagram of a second method for planning a path of an intelligent cleaning robot according to an embodiment of the present application;
fig. 3 is a main screen of intelligent cleaning robot control terminal software provided in the embodiment of the present application;
fig. 4 is a manual control picture of the intelligent cleaning robot control terminal provided in the embodiment of the present application;
fig. 5 is a first drawing of a laser building of a control terminal of the intelligent cleaning robot provided by the embodiment of the present application;
fig. 6 is a second drawing of a laser building of the control terminal of the intelligent cleaning robot provided in the embodiment of the present application;
fig. 7 is a first task configuration screen of a control terminal of the intelligent cleaning robot according to the embodiment of the present application;
fig. 8 is a task configuration screen of a control terminal of the intelligent cleaning robot according to the embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In a first aspect, referring to fig. 1, an embodiment of the present invention provides an intelligent cleaning robot path planning method, including:
step S100: and under the condition of a known environment map, acquiring real-time position information, and sending the real-time position information to the control terminal, wherein the control terminal is used for comparing the real-time position information with the known environment map, establishing new environment map information and planning an optimal cleaning path.
Specifically, when the intelligent cleaning robot is used, a switch of the intelligent cleaning robot is turned on, the mobile phone or the computer device is connected with the intelligent cleaning robot wifi, the picture shown in fig. 3 is referred to, initialization setting of the intelligent cleaning robot is achieved, a user selects functions of the intelligent cleaning robot according to needs, and the laser navigation sensor on the front side of the machine body is used for establishing environment map information.
And entering a map tool shown in figures 5-6 according to the main pictures shown in figures 3-4 to perform a new map function task, after the map is named, manually remotely operating the machine to perform laser scanning on the site to build a map, and storing the map after the map is built. Then, editing the established map, wherein the map comprises a virtual wall and noise points, and the virtual wall can isolate a section of area which cannot be reached by the robot on the map, namely, an area without obstacles is protected in space; when the noise points are cleared, namely the scanogram is cleared, the moving unfixed points on the periphery are cleared, so that the positions of all objects fixed in the environment are well positioned, invalid interference points are cleared, the cleaning line can be effectively planned, and the cleaning time frequency of the area can be set.
Step S101: and receiving the optimal cleaning path sent by the control terminal, and cleaning according to the optimal cleaning path.
After the map is built, the task configuration of fig. 7-8 is carried out, a new path area is added to the partitioned path in the task type, then the area needing to work is drawn on the generated map through software, the starting point position of the robot during working can be set, the robot is convenient to manage, and then the planned route is generated according to the generated area name. For convenience of management, two circuit modes of a Chinese character 'Bo' shape and a Chinese character 'Hui' shape are provided, and the Chinese character 'Bo' shape circuit can also switch the trend of rows and columns. And the software generates an adaptive optimal navigation traveling route according to an algorithm and a preset robot size.
Step S102: when an obstacle is encountered in the optimal cleaning path, recording the position information of the obstacle and sending the position information to the control terminal; and the control terminal is used for making an obstacle avoidance strategy according to the received position information of the obstacle.
In the cleaning process, roadblock scanning is carried out, an obstacle avoiding program is entered when an obstacle is encountered, and meanwhile, the position information of the obstacle is recorded into map data; then the control terminal judges whether the cleaning of all the cleanable grilles is finished, and if the cleaning is finished, the process is finished; otherwise, returning to the step.
Step S103: and receiving an obstacle avoidance strategy sent by the control terminal, and completing a cleaning task.
According to the path planning method for the intelligent cleaning robot, provided by the embodiment of the invention, when the intelligent cleaning robot is in a known environment map, the intelligent cleaning robot positions the intelligent cleaning robot to obtain the real-time position information, uploads the real-time position information to the control terminal, plans the optimal cleaning route through the control terminal, and cleans according to the optimal cleaning route, so that the cleaning robot is ensured to achieve the optimal cleaning efficiency within the limited working time and the cleaning time is shortest. When an obstacle is encountered in the cleaning process, the intelligent cleaning robot records and sends the position information of the obstacle to the control terminal, then the control terminal works out an obstacle avoidance strategy according to the received information, and then the intelligent cleaning robot finishes cleaning the optimal cleaning path according to the obstacle avoidance strategy. By adopting the intelligent cleaning robot path planning method, the problems that the cleaning robot in the prior art cannot automatically judge the position of the cleaning robot and an optimal cleaning route is planned without regulations are effectively solved, and the automatic recording of a map to judge the position of the cleaning robot and the planning of the optimal cleaning route are realized.
In addition, in order to conveniently manage different areas and cleaning time interval times, tasks of different areas can be added into the task list, personalized work setting is achieved, cleaning requirements for different areas are provided, and cleaning efficiency is more scientifically planned. And when the electric quantity is lower than the requirement, the cleaning robot automatically goes to a planned charging area to automatically charge so as to complete full-automatic work and management. In addition, as shown in fig. 3-8, a fault problem specific display is provided above the software in the mobile phone or the computer device, the exclamation mark can be clicked to be viewed, and the color of the robot mark is displayed when the communication is abnormal. A sophisticated application set provides good service.
The input steps of the unit domain plan with the known map are as follows:
inputting a two-dimensional array map = (x, y) representing a map; according to the characteristic of a two-dimensional array, the origin of coordinates is at the upper left corner, y is high, x is wide, y is increased progressively downwards, and x is increased progressively rightwards; packaging x and y into a class, carrying out parameter transmission, and comparing coordinates (x, y) by rewriting an equals method; when x (k) = x (k-1), y (k) = y (k-1), map (k) = map (k-1), otherwise when x (k) is not equal to x (k-1) or y (k) is not equal to y (k-1), map (k) = map (k-2); and encapsulating the path node class, wherein the fields comprise: coordinates, g values, f values and father nodes to realize a composable interface; the final data structure is a * All data input by the algorithm is packaged together.
Wherein, a * The algorithm processing steps are as follows:
several constants are defined in the algorithm to determine: the bar =1 value in the two-dimensional array represents an obstacle, the path =2 value is a representative value of a path drawn in the two-dimensional array, the direct _ value =10 value represents the cost of horizontal and vertical movement required for calculating the g value, and the direct _ value =14 value represents the cost of oblique movement; respectively defining open and close auxiliary tables by using PRIORTyqueue and arraylist to obtain a minimum value and a storage node; defining a Boolean judgment method; calculating h value, wherein the coordinates are respectively added by taking difference values by using a 'Manhattan' method; searching nodes from an open list; adding adjacent nodes to an open table; drawing a path by a backtracking method; and (4) searching a path by the open-loop mobile node, and setting a loop ending condition, wherein an open table is empty or a final node is in a close table.
Further, with reference to fig. 2, the method for planning the path of the intelligent cleaning robot further includes:
step S200: and under the condition of unknown environment maps, acquiring environment perception features and carrying out local positioning.
The intelligent cleaning robot acquires real-time position information by using the near ultrasonic sensor and the infrared sensor and sends the real-time position information to the control terminal.
When the real-time position information is consistent with the known environment map information, the intelligent cleaning robot plans an optimal cleaning path according to the known environment map information. And when the real-time position information is inconsistent with the known environment map information, the intelligent cleaning robot redraws a new environment map according to the acquired real-time position coordinate threshold value and plans an optimal cleaning path according to the new environment map information.
Step S201: and sending the environment perception characteristics and the local positioning information to a control terminal, wherein the control terminal is used for judging and positioning the endpoint coordinates of the inflection point according to the environment perception characteristics and the local positioning information and establishing local map information.
Positioning the laser sensor by the laser sensor; the gyroscope and the photoelectric encoder are common tools for measuring the angular velocity and the motion state of the robot, can accurately measure the velocity, the acceleration and the angular velocity, can solve the moving distance and the rotating angle of the robot, and then position the robot according to a laser radar map. The method has the advantage of self-reference and self-measurement, namely the motion parameters can be measured by self without external information. Different from the dead reckoning in the market, the physical quantity measured by the gyroscope and the photoelectric encoder is more accurate, errors caused by integral operation errors and timing system time difference can not be gradually accumulated along with the passage of working time, and the established local map information is more accurate.
Step S202: the local map information is cleaned according to the planned route.
After the local map is built, referring to the cleaning steps, the task configuration of the figures 7-8 is entered, new path areas are added to the partitioned paths in the task types, then areas needing to work are drawn by circles on the generated map through software, the starting point position of the robot during working can be set, and then the planned route is generated according to the generated area names. For convenience of management, two circuit modes of a Chinese character 'Bo' shape and a Chinese character 'Hui' shape are provided, and the Chinese character 'Bo' shape circuit can also switch the trend of rows and columns. The software generates an adaptive optimal navigation travel route according to the algorithm and the preset robot size.
Further, the obtaining the environment perception feature and the local positioning comprise:
the environmental perception characteristics are obtained through the ultrasonic sensor, and local positioning is carried out through serial connection of environmental topology nodes.
An environment map is established by utilizing a geometric-topological mixed map technology, an optimal cleaning path is planned by using an advanced path planning algorithm by combining the environment map and a real-time position, and data is uploaded to a cloud platform to realize real-time analysis, recording and control. Specifically, the environment topology nodes of the accurate positioning module are connected in series to perform local positioning, the accurate positioning module comprises a gyroscope and a laser radar, the gyroscope is used for collecting the angular speed, the speed and the acceleration of the deviation of the intelligent cleaning robot, the walking direction of the intelligent cleaning robot is judged, and the running condition of an indoor navigation positioning system and a walking motor is matched.
Furthermore, the environment topological nodes adopt geometric expressions, and meanwhile, the consistency of the environment map expression is maintained.
The corner judgment of geometric-topological mixed map dead reckoning in practice is as follows:
wherein (x) 1 ,y 1 ,xc 1 ,yc 1 ) And (x) 2 ,y 2 ,xc 2 ,yc 2 ) Two approximately perpendicular line segments for forming corners; (xc) 1 ,yc 1 ) And (xc) 2 ,yc 2 ) To be at the corner region line segment endpoint coordinates, es and ed are threshold empirical values.
Further, acquiring the environment perception feature comprises extracting the environment feature, establishing a corner vertical line segment, judging and positioning the endpoint coordinate of the corner according to an empirical threshold.
Through the multi-sensor information fusion technology, an environment map is recorded, the current position is judged in real time, the position of the intelligent cleaning robot on the constructed environment map is accurately positioned, the positions of obstacles such as tables and chairs are accurately positioned, the optimal path planning of the maximum cleanliness can be achieved, and meanwhile, the cleaning time is saved.
Furthermore, the receiving of the obstacle avoidance policy sent by the control terminal and the completion of the cleaning task include:
and receiving an obstacle avoidance strategy sent by the control terminal.
Tracking the contour of the obstacle, and driving to the target point immediately when the obstacle can directly move to the target point; and when the mobile robot cannot move to the target point directly, if the path reaching the target point does not exist, replanning the route, and repeating the steps until the cleaning task is completed.
Specifically, the obstacle avoidance strategy when encountering an obstacle is a bug2 obstacle strategy, and specifically comprises the following steps:
the intelligent cleaning robot firstly tracks the outline of the obstacle, and when the intelligent cleaning robot can directly move to a target point, the intelligent cleaning robot immediately leaves; connecting qstart and qgoal by m-line in the bug algorithm to form a fixed straight line; when the intelligent cleaning robot meets an obstacle, the intelligent cleaning robot enters a contour tracking mode, and when the intelligent cleaning robot reaches a position on the m-line, which is close to a target point, the intelligent cleaning robot continues to drive to the target along the m-line; if the intelligent cleaning robot again encounters the previous impact point on the m-line, the path to the target does not exist; carrying out infrared scanning and data detection returned by the gyroscope during cleaning, and detecting whether the intelligent cleaning robot body leaves the ground or not; and if the vehicle body is detected to leave the ground, stopping all functions and entering a standby state.
An embodiment of the present invention further provides an intelligent cleaning device, including:
the acquisition module is used for acquiring real-time position information and sending the real-time position information to the control terminal, and the control terminal is used for comparing the real-time position information with a known environment map, establishing new environment map information and planning an optimal cleaning path.
Preferably, under the condition of a known environment map, the acquisition module is used for acquiring real-time position information and sending the real-time position information to the control terminal, and the control terminal is used for comparing the real-time position information with the known environment map, establishing new environment map information and planning an optimal cleaning path.
Specifically, when the intelligent cleaning robot is used, a switch of the intelligent cleaning robot is turned on, the mobile phone or the computer device is connected with the intelligent cleaning robot wifi, the picture shown in fig. 3 is referred to, initialization setting of the intelligent cleaning robot is achieved, a user selects functions of the intelligent cleaning robot according to needs, and the laser navigation sensor on the front side of the machine body is used for establishing environment map information.
And entering a map tool shown in figures 5-6 according to the main pictures shown in figures 3-4 to perform a new map function task, after the name of the map is given, performing laser scanning map building on the site by using a manual remote control operation machine, and storing the map after the map building is finished. Then, editing the established map, wherein the map comprises a virtual wall and noise elimination points, and the virtual wall can isolate a section of area which cannot be reached by the robot on the map, namely, an unobstructed area is protected in space; when noise points are cleared, namely, sweeping images are cleared, moving unfixed points around the sweeping images are cleared, so that the positions of all objects fixed in the environment are well positioned, invalid interference points are cleared, a cleaning line can be effectively planned, and the cleaning time frequency of the area can be set.
Wherein, obtaining the environmental perception characteristic and performing the local positioning comprises:
the environmental perception characteristics are obtained through the ultrasonic sensor, and local positioning is carried out through serial connection of environmental topology nodes.
An environment map is established by utilizing a geometric-topological mixed map technology, an optimal cleaning path is planned by using an advanced path planning algorithm by combining the environment map and a real-time position, and data is uploaded to a cloud platform to realize real-time analysis, recording and control. Specifically, the environment topology nodes of the accurate positioning module are connected in series to perform local positioning, the accurate positioning module comprises a gyroscope and a laser radar, the gyroscope is used for collecting the angular speed, the speed and the acceleration of the deviation of the intelligent cleaning robot, the walking direction of the intelligent cleaning robot is judged, and the running condition of an indoor navigation positioning system and a walking motor is matched.
In addition, under the condition of unknown environment maps, the acquisition module can also acquire environment perception features and perform local positioning.
The intelligent cleaning robot acquires real-time position information by using the near ultrasonic sensor and the infrared sensor and sends the real-time position information to the control terminal.
And when the real-time position information is consistent with the known environment map information, planning an optimal cleaning path according to the known environment map information. And when the real-time position information is inconsistent with the known environment map information, redrawing the environment map according to the threshold value, and planning an optimal cleaning path according to the new environment map information. And then, the environment perception feature and the local positioning information are sent to a control terminal, and the control terminal is used for judging and positioning the endpoint coordinates of the inflection point according to the environment perception feature and the local positioning information and establishing local map information.
Positioning the laser sensor by the laser sensor; the gyroscope and the photoelectric encoder are common tools for measuring the angular velocity and the motion state of the robot, can accurately measure the velocity, the acceleration and the angular velocity, can solve the moving distance and the rotating angle of the robot, and then position the robot according to a laser radar map. The method has the advantage of self-reference and self-measurement, namely the motion parameters can be measured by self without external information. Different from the dead reckoning in the market, the physical quantity measured by the gyroscope and the photoelectric encoder is more accurate, errors caused by integral operation errors and timing system time difference can not be gradually accumulated along with the passage of working time, and the established local map information is more accurate.
And the receiving module is used for receiving the optimal cleaning path sent by the control terminal and cleaning according to the optimal cleaning path.
Preferably, the receiving module of this embodiment is configured to receive the optimal cleaning path sent by the control terminal, and perform cleaning according to the optimal cleaning path. After the map is built, the task configuration of fig. 7-8 is carried out, a new path area is added to the partitioned path in the task type, then the area needing to work is drawn on the generated map through software, the starting point position of the robot during working can be set, the robot is convenient to manage, and then the planned route is generated according to the generated area name. For convenience of management, two circuit modes of a Chinese character 'Bo' shape and a Chinese character 'Hui' shape are provided, and the Chinese character 'Bo' shape circuit can also switch the trend of rows and columns. And the software generates an adaptive optimal navigation traveling route according to an algorithm and a preset robot size.
The obstacle avoidance module is used for recording and sending position information of the obstacle to the control terminal when the obstacle is encountered in the optimal cleaning path; and the control terminal is used for making an obstacle avoidance strategy according to the received position information of the obstacle.
Specifically, the obstacle avoidance module performs obstacle scanning in the cleaning process, enters an obstacle avoidance program when an obstacle is encountered, and records the position information of the obstacle into map data; then the control terminal judges whether the cleaning of all the cleanable grilles is finished, and if the cleaning is finished, the process is finished; otherwise, returning to the step.
Furthermore, the receiving of the obstacle avoidance policy sent by the control terminal and the completion of the cleaning task include:
and receiving an obstacle avoidance strategy sent by the control terminal.
Tracking the contour of the obstacle, and driving to the target point immediately when the obstacle can directly move to the target point; and when the robot cannot directly move to the target point, if the path reaching the target point does not exist, replanning the route, and repeating the steps until the cleaning task is completed.
Specifically, the obstacle avoidance strategy when encountering an obstacle is a bug2 obstacle strategy, and specifically comprises the following steps:
the intelligent cleaning robot firstly tracks the outline of the obstacle, and when the intelligent cleaning robot can directly move to a target point, the intelligent cleaning robot immediately leaves; connecting qstart and qgoal by m-line in the bug algorithm to form a fixed straight line; when the intelligent cleaning robot meets an obstacle, the intelligent cleaning robot enters a contour tracking mode, and when the intelligent cleaning robot reaches a position on the m-line, which is close to a target point, the intelligent cleaning robot continues to drive to the target along the m-line; if the intelligent cleaning robot again encounters the previous impact point on the m-line, the path to the target does not exist; carrying out infrared scanning and data detection returned by the gyroscope during cleaning, and detecting whether the intelligent cleaning robot body leaves the ground or not; and if the vehicle body is detected to leave the ground, stopping all functions and entering a standby state.
And the driving module is used for receiving the obstacle avoidance strategy sent by the control terminal and completing the cleaning task.
The intelligent cleaning robot comprises a driving module, a control terminal and an intelligent cleaning robot, wherein the driving module is used for receiving an obstacle avoidance strategy sent by the control terminal and completing a cleaning task, when an obstacle is encountered in a cleaning process, the intelligent cleaning robot can record position information of the obstacle and send the position information to the control terminal, then the control terminal works out the obstacle avoidance strategy according to the received information, and then the intelligent cleaning robot completes cleaning of an optimal cleaning path according to the obstacle avoidance strategy.
Another embodiment of the present invention also provides a server, including: a memory and a processor.
The memory is for storing program instructions.
The processor is used for executing program instructions in the server, so that the intelligent cleaning robot path planning method is executed by the server.
The invention further provides a computer-readable storage medium which stores executable instructions, and the intelligent cleaning robot path planning method can be realized when the computer executes the executable instructions.
The storage medium includes, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Cache, a Hard Disk (Hard Disk Drive), or a Memory Card (HDD). The memory may be used to store computer program instructions.
Although the present application provides method steps as described in an embodiment or flowchart, additional or fewer steps may be included based on conventional or non-inventive efforts. The sequence of steps recited in this embodiment is only one of many steps in execution sequence, and does not represent a unique order of execution. When an actual apparatus or client product executes, it can execute sequentially or in parallel (e.g., in the context of parallel processors or multi-threaded processing) according to the methods shown in this embodiment or the figures.
The apparatuses or modules illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. The functionality of the modules may be implemented in the same one or more software and/or hardware implementations of the present application. Of course, a module that implements a certain function may be implemented by a plurality of sub-modules or sub-units in combination.
The methods, apparatus or modules described herein may be implemented in a computer readable program code means for a controller in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application Specific Integrated Circuits (ASICs), programmable logic controllers and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be conceived to be both a software module implementing the method and a structure within a hardware component.
Some of the modules in the apparatus described herein may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary hardware. Based on such understanding, the technical solutions of the present application may be embodied in the form of software products or in the implementation process of data migration, which essentially or partially contributes to the prior art. The computer software product may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a mobile terminal, a server, or a network device, etc.) to perform the methods described in the embodiments or some parts of the embodiments of the present application.
The embodiments in the present specification are described in a progressive manner, and the same or similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. All or portions of the present application are operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, mobile communication terminals, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications or substitutions do not depart from the spirit and scope of the present disclosure.
Claims (10)
1. An intelligent cleaning robot path planning method is characterized by comprising the following steps:
when the mobile robot is in the condition of a known environment map, acquiring real-time position information, and sending the real-time position information to a control terminal, wherein the control terminal is used for comparing the real-time position information with the known environment map, establishing new environment map information, and planning an optimal cleaning path;
receiving the optimal cleaning path sent by the control terminal, and cleaning according to the optimal cleaning path;
when an obstacle is encountered in the optimal cleaning path, recording the position information of the obstacle and sending the position information to the control terminal; the control terminal is used for making an obstacle avoidance strategy according to the received position information of the obstacle;
and receiving the obstacle avoidance strategy sent by the control terminal, and completing a cleaning task.
2. The intelligent cleaning robot path planning method according to claim 1, wherein the acquiring real-time position information and sending the real-time position information to a control terminal comprises:
acquiring real-time position information through an ultrasonic sensor and an infrared sensor, and sending the real-time position information to a control terminal;
when the real-time position information is consistent with the known environment map information, planning an optimal cleaning path according to the known environment map information;
and when the real-time position information is inconsistent with the known environment map information, redrawing the environment map according to a threshold value, and planning an optimal cleaning path according to the new environment map information.
3. The intelligent cleaning robot path planning method according to claim 1, wherein the receiving the obstacle avoidance strategy sent by the control terminal and completing the cleaning task comprises:
receiving an obstacle avoidance strategy sent by the control terminal;
tracking the contour of the obstacle, and driving to a target point immediately when the obstacle can move to the target point directly; and when the robot can not directly move to the target point, confirming that a path reaching the target point does not exist, replanning the route, and repeating the steps until the cleaning task is completed.
4. The intelligent cleaning robot path planning method according to claim 1, further comprising:
when the mobile terminal is in the condition of an unknown environment map, acquiring environment perception features and carrying out local positioning;
the environment perception feature and the local positioning information are sent to the control terminal, and the control terminal is used for judging and positioning inflection point endpoint coordinates according to the environment perception feature and the local positioning information and establishing local map information;
and cleaning according to a planned path in the local map information.
5. The intelligent cleaning robot path planning method of claim 4, wherein the obtaining environmental awareness features and locally locating comprise:
and acquiring the environment perception characteristics through an ultrasonic sensor, and performing local positioning through serial connection of environment topology nodes.
6. The intelligent cleaning robot path planning method of claim 5, wherein the environment topology nodes are geometrically represented while maintaining consistency of the representation of the environment map.
7. The intelligent cleaning robot path planning method of claim 4, wherein obtaining context aware features comprises extracting context features, establishing corner vertical line segments, judging and locating corner endpoint coordinates based on empirical thresholds.
8. An intelligent cleaning device, comprising:
the system comprises an acquisition module, a control terminal and a data processing module, wherein the acquisition module is used for acquiring real-time position information and sending the real-time position information to the control terminal, and the control terminal is used for comparing the real-time position information with a known environment map, establishing new environment map information and planning an optimal cleaning path;
the receiving module is used for receiving the optimal cleaning path sent by the control terminal and cleaning according to the optimal cleaning path;
the obstacle avoidance module is used for recording and sending position information of the obstacle to the control terminal when the obstacle is encountered in the optimal cleaning path; the control terminal is used for making an obstacle avoidance strategy according to the received position information of the obstacle;
and the driving module is used for receiving the obstacle avoidance strategy sent by the control terminal and completing the cleaning task.
9. A server, comprising: a memory and a processor;
the memory is to store program instructions;
the processor is configured to execute program instructions in a server, so that the server performs the intelligent cleaning robot path planning method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing executable instructions that when executed by a computer enable the intelligent cleaning robot path planning method according to any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117031986A (en) * | 2023-10-10 | 2023-11-10 | 江苏通创现代建筑产业技术研究院有限公司 | Control method and system for automatic cleaning of building curtain wall |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117031986A (en) * | 2023-10-10 | 2023-11-10 | 江苏通创现代建筑产业技术研究院有限公司 | Control method and system for automatic cleaning of building curtain wall |
| CN117031986B (en) * | 2023-10-10 | 2023-12-15 | 江苏通创现代建筑产业技术研究院有限公司 | Control method and system for automatic cleaning of building curtain wall |
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