CN112068557A - Mobile robot full-coverage path planning method, chip and robot - Google Patents
Mobile robot full-coverage path planning method, chip and robot Download PDFInfo
- Publication number
- CN112068557A CN112068557A CN202010879964.3A CN202010879964A CN112068557A CN 112068557 A CN112068557 A CN 112068557A CN 202010879964 A CN202010879964 A CN 202010879964A CN 112068557 A CN112068557 A CN 112068557A
- Authority
- CN
- China
- Prior art keywords
- sub
- block
- robot
- blocks
- cleaning
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000004140 cleaning Methods 0.000 claims abstract description 83
- 230000004888 barrier function Effects 0.000 claims description 10
- 230000011218 segmentation Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 abstract description 15
- 238000010408 sweeping Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 4
- 230000003670 easy-to-clean Effects 0.000 description 2
- 230000007704 transition Effects 0.000 description 2
- 241001417527 Pempheridae Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Electric Vacuum Cleaner (AREA)
Abstract
The invention relates to a mobile robot full-coverage path planning method, a chip and a robot, wherein the full-coverage path planning method comprises the following steps: s1, detecting obstacles in the cleaning area by the robot, generating a map containing obstacle information, and dividing the map into a plurality of sub-blocks; s2, cleaning paths in the robot planning sub-blocks; s3, the robot determines the starting sub-blocks and cleans the sub-blocks, then calculates the path cost among the sub-blocks, selects the next cleaned sub-block according to the path cost and circulates the steps until the cleaning of all the sub-blocks is completed. The novel full-coverage path planning method can reduce the calculation complexity and improve the coverage efficiency of the robot.
Description
Technical Field
The invention relates to the field of intelligent robots, in particular to a mobile robot full-coverage path planning method, a chip and a robot.
Background
At present, for a full-coverage robot, such as a sweeper, a mower, a window cleaner, a mine clearance robot and the like, all places which can be reached by the robot need to be covered by the shortest path. While the full coverage approach is generally the traveling salesman (NP-hard) problem, it is addressed to solve the shortest loop that visits each city once and returns to the starting city, given a series of cities and the distance between each pair of cities. When the dimensionality of the problem increases, the calculation time required for solving the problem increases sharply, which causes the robot to spend more time for path planning, affects the working efficiency, is not intelligent, and reduces the use experience of the user. Based on this, it is necessary to develop a new path covering method to improve the path covering efficiency of the intelligent robot.
Disclosure of Invention
In order to solve the problems, the invention provides a mobile robot full-coverage path planning method, a chip and a robot, which can greatly reduce the calculation complexity and improve the coverage efficiency of the robot. The specific technical scheme of the invention is as follows:
a mobile robot full coverage path planning method, the method comprising the steps of: s1, detecting obstacles in the cleaning area by the robot, generating a map containing obstacle information, and dividing the map into a plurality of sub-blocks; s2, cleaning paths in the robot planning sub-blocks; s3, the robot determines the starting sub-blocks and cleans the sub-blocks, then calculates the path cost among the sub-blocks, selects the next cleaned sub-block according to the path cost and circulates the steps until the cleaning of all the sub-blocks is completed. The novel full-coverage path planning method can reduce the calculation complexity and improve the coverage efficiency of the robot.
Further, the step S1 specifically includes the following steps: the robot detects obstacles in a cleaning area through a vision system, generates a map and reads the boundary of the map and the obstacles; the robot sets a plurality of parallel cleaning lines on a map according to the boundary of the map and an obstacle, and the distances between the adjacent cleaning lines are equal; the robot takes a cleaning line with two ends respectively positioned on the boundaries of two sides of the map and at least one robot radius away from the obstacle as a sub-block dividing line; the robot divides the map into a plurality of sub-blocks by taking the sub-block dividing line and the boundaries of two sides of the barrier as boundaries. According to the invention, through the arrangement of the cleaning line, accurate and effective reference basis can be provided for the positioning of the subsequent dividing line; the cleaning area can be divided into a plurality of regular geometric figures which are easy to clean by taking the dividing line and the boundaries of two sides of the barrier as boundaries.
Further, the cleaning line is in the horizontal direction or the vertical direction.
Furthermore, in the process of dividing the map, the robot regards the area where the sub-block dividing line is located as a sub-block, and the sub-block only comprises a cleaning line of the sub-block dividing line. The invention regards the sub-block dividing line as a sub-block, and the sub-block dividing line is used as a transition, so that the robot can move among the sub-blocks with higher efficiency.
Further, the robot passes through A*And planning a cleaning path in the sub-block by using an algorithm so that the robot walks in the sub-block in a bow shape. The invention is achieved by A*The algorithm plans the cleaning path in the sub-blocks, and can solve the cleaning path in an efficient mode.
Further, the step S3 specifically includes the following steps: the robot reads the distribution condition of the sub-blocks; the robot takes the sub-block where the robot is located as an initial sub-block; the robot traverses all the sub-blocks which are not cleaned and are communicated with the initial sub-block, and if only one sub-block exists, the sub-block is used as the next cleaning area; if two or more sub-blocks exist, respectively calculating the sum of the path cost of each branch going and returning, and selecting the sub-block on the branch with the minimum sum of the path cost to clean; if the sub-block is looped back, the path cost from the starting sub-block to the next sub-block is only needed to be compared, and the sub-block with the small path cost is selected for cleaning.
Furthermore, the sub-block loopback determining method is that starting from a sub-block, if a path returning to the sub-block can be found without repeating the path, all sub-blocks on the path constitute a sub-block loopback.
Further, when traversing the uncleaned sub-block communicated with the starting sub-block, if the starting sub-block does not have the next communicated uncleaned sub-block, returning to the previous sub-block, and continuously traversing all the communicated uncleaned sub-blocks until all the sub-blocks are cleaned.
A chip is internally provided with a control program, and the control program is used for controlling a robot to execute the full coverage path planning method. By using the chip provided by the invention, the calculation complexity of the robot in planning the full-coverage path can be reduced, and the path coverage efficiency is improved.
A robot is equipped with a main control chip, and the main control chip is the chip. The robot of the invention can improve the efficiency of path coverage, reduce the planning time consumed by the robot in the process of completing tasks and improve the user experience.
The invention has the beneficial effects that: the robot takes the obstacles in the cleaning area as reference, and divides the sub-blocks according to the obstacles and the dividing lines, so that the calculation complexity can be greatly reduced; the robot judges the cleaning sequence of the sub-blocks according to the path cost among the sub-blocks, so that the calculation complexity is greatly reduced, the cleaning of a room can be completed at low cost, and the coverage efficiency of the robot is improved. Therefore, the robot can plan the full coverage path more efficiently and intelligently, the time required by calculation is greatly reduced, and the user experience can be improved.
Drawings
Fig. 1 is a schematic flow chart illustrating a method for planning a full coverage path of a mobile robot according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a mobile robot performing a full coverage path planning operation according to an embodiment of the present invention.
Fig. 3 is a schematic diagram illustrating a path cost calculation performed by a mobile robot according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a mobile robot performing a full coverage path planning operation according to another embodiment of the present invention.
Fig. 5 is a schematic diagram of a mobile robot performing path cost calculation according to another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail below with reference to the accompanying drawings in the embodiments of the present invention. It should be understood that the following specific examples are illustrative only and are not intended to limit the invention.
In the following description, specific details are given to provide a thorough understanding of the embodiments. However, it will be understood by those of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits may be shown in block diagrams in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, structures and techniques may not be shown in detail in order not to obscure the embodiments.
The robot can be an intelligent mobile robot such as a sweeping robot, a mowing robot, a window cleaning robot, a mine clearing robot and the like, and can comprise a robot main body, a sensing system, a control system, a driving system, a cleaning system, an energy system, a human-computer interaction system and the like.
As shown in fig. 1, a method for planning a full coverage path of a mobile robot includes the following steps: s1, detecting obstacles in the cleaning area by the robot, generating a map containing obstacle information, and dividing the map into a plurality of sub-blocks; s2, cleaning paths in the robot planning sub-blocks; s3, the robot determines the starting sub-blocks and cleans the sub-blocks, then calculates the path cost among the sub-blocks, selects the next cleaned sub-block according to the path cost and circulates the steps until the cleaning of all the sub-blocks is completed. According to the new full-coverage path planning method, the dividing line is set on the basis of the cleaning line, the sub-block sequence is planned by using the path cost, the sub-block dividing and sequence planning processes are simplified, the calculation complexity is reduced, the calculation time is saved, and therefore the coverage efficiency of the robot is improved.
As one embodiment, the step S1 specifically includes the following steps: firstly, detecting obstacles in a cleaning area by a robot through a vision system, generating a map, and simultaneously reading the map and the boundary of the obstacles; then, the robot sets a plurality of cleaning lines which are parallel to each other on the map according to the boundary of the map and the barrier, the cleaning lines start from one side boundary of the map, the cleaning lines stop when the other side boundary of the map or one side boundary of the barrier is detected, the cleaning lines start from the other side boundary of the barrier until the other side boundary of the map is detected when one side boundary of the barrier is met, and the distances between the cleaning lines are equal; then, the robot takes cleaning lines with two ends respectively positioned on the boundaries of the two sides of the map and at least one robot radius away from the obstacles as sub-block dividing lines, if the dividing lines are positioned between the two obstacles (including the wall) and the distance is less than the diameter of the robot, the two obstacles are taken as a whole, and the cleaning lines are not taken as the dividing lines; and finally, dividing the map into a plurality of sub-blocks by the robot by taking the sub-block dividing line and the boundaries of two sides of the barrier as boundaries. According to the method, accurate and effective reference basis can be provided for positioning of the subsequent dividing line through the arrangement of the cleaning line; the cleaning area can be divided into a plurality of regular geometric figures which are easy to clean by taking the dividing line and the boundaries of two sides of the barrier as boundaries.
In one embodiment, the cleaning line is in a horizontal direction or a vertical direction.
As an embodiment, in the map segmentation process, the robot regards an area where the sub-block segmentation line is located as a sub-block, and the sub-block only includes a cleaning line of the sub-block segmentation line. The invention regards the sub-block dividing line as a sub-block, and the sub-block dividing line is used as a transition, so that the robot can move among the sub-blocks with higher efficiency.
As one embodiment, the robot passes through A*And planning a cleaning path in the sub-block by using an algorithm so that the robot walks in the sub-block in a bow shape. A is described*The algorithm is a classical method for solving the optimal path, can be used for planning the motion tracks of two points on a map, and is widely applied to path finding and graph traversal due to high efficiency. The method of this example, by A*The algorithm plans the cleaning path in the sub-blocks, and can solve the cleaning path in an efficient mode.
As one embodiment, the step S3 specifically includes the following steps: firstly, a robot reads the distribution condition of the sub-blocks; then, the robot takes the sub-block where the robot is located as an initial sub-block; finally, the robot traverses all the sub-blocks which are not cleaned and are communicated with the initial sub-block, and if only one sub-block exists, the sub-block is used as the next cleaning area; if two or more sub-blocks exist, respectively calculating the sum of the path cost of each branch going to and returning, wherein the sum of the path cost comprises the sum of all paths which are passed by the robot from the starting sub-block to the starting sub-block, and selecting the sub-block on the branch with the smallest sum of the path cost for cleaning; if the sub-block is looped back, the path cost from the starting sub-block to the next sub-block is only needed to be compared, and the sub-block with the small path cost is selected for cleaning. The traversal means that the robot accesses the information of all the sub-blocks on the map. The judgment method of the sub-block loop is that starting from a sub-block, if a path returning to the sub-block can be found under the condition that the path is not repeated, all the sub-blocks on the path form a sub-block loop. According to the method, the cleaning sequence among the sub-blocks is judged according to the path cost, so that the calculation complexity is greatly reduced, and the path coverage efficiency is improved.
As one embodiment, when traversing the uncleaned sub-block connected to the starting sub-block, if the starting sub-block has no next connected uncleaned sub-block, the robot returns to the previous sub-block and continues to traverse all connected uncleaned sub-blocks until all sub-blocks are cleaned.
The embodiment of the invention also provides a chip, which is internally provided with a control program, wherein the control program is used for controlling the robot to execute the full coverage path planning method. By using the chip provided by the invention, the calculation complexity of the robot in planning the full-coverage path can be reduced, and the path coverage efficiency is improved. The chip can be assembled on an intelligent mobile robot such as a sweeping robot, a mowing robot, a window cleaning robot, a mine clearing robot and the like.
The embodiment of the invention also provides a robot, which is provided with the main control chip. The robot equipped with the chip can execute the full-coverage path planning method, has the same technical effect as the full-coverage path planning method, and is not described herein again.
The following description will be given taking the cleaning robot cleaning the room as an example:
as shown in fig. 2, assuming that the sweeping robot cleans a room, a bed and a table are located near a wall in the room, and both are considered as obstacles. When the sweeping robot detects an obstacle through the vision system, a room map containing obstacle information is generated. Then, the robot reads the boundary of the obstacle and the map, a plurality of mutually parallel cleaning lines with equal distance are arranged between the boundary of the obstacle and the map, and the cleaning lines are shown in the picture at the upper left corner of the figure 2. Next, the robot takes the cleaning lines with both ends located at the boundaries on both sides of the map and adjacent to the obstacles as the sub-block dividing lines, the number of which is determined by the number and position of the obstacles, as shown in fig. 2, and two obstacles are present in the room and close to the wall, so that only two dividing lines are taken, located in the sub-blocks with the numbers 3 and 5 in the figure, respectively. Subsequently, the whole room is divided into 7 sub-blocks by using the dividing line and the boundary of the barrier as boundaries, wherein the 7 sub-blocks comprise sub-blocks with serial numbers of 1, 2, 6 and 7 at two sides of the bed and the table respectively, a sub-block with a serial number of 4 in the middle of the bed and the table and sub-blocks with serial numbers of 3 and 5 at which the two dividing lines are located. Next, A is used*The algorithm performs a zigzag planning on the cleaning path in each sub-block, and the result is shown in the lower right corner picture of fig. 2. Finally, the sequence of the sub-blocks is ordered according to the path cost between the sub-blocks, as shown in fig. 3, the circles represent the sub-blocks, the numbers correspond to the sub-block numbers in fig. 2, and the arrows represent the path cost between the sub-blocks. Let a =5, b =6, c =7, d =6, e =2, f =1, g =10, h =15, i =13, j =12, k =4, l = 5. Assuming that the robot cleans the sub-block 1, i.e. the left side of the bed, all sub-blocks communicating with the sub-block 1 are traversed after the cleaning is completed, and only one communicating sub-block 3 is found, so that the sweeping robot moves to the sub-block 3 for sweeping. After cleaning is finished, all the sub-blocks communicated with the sub-block 3 are continuously traversedIf two sub-blocks are found, the sum of the path costs of the two different branches to sum back is calculated. Wherein, the sum of the path costs toward the sub-block 2 is c + d = 13; the sum of the path costs in the direction to the sub-block 4 is f + g + k + l + j + i + h + e =62, and according to the result, the robot selects the sub-block 2 to clean. After cleaning the sub-block 2, the robot finds that there is no next uncleaned connected sub-block, and then returns to the previous sub-block 3. Now only the sub-sector 4 is available for selection and then goes to cleaning. After completion, all the sub-blocks connected with the sub-block 4 are continuously traversed, and only the uniquely connected sub-block 5 is found to go to cleaning. After the completion, continuing to traverse the sub-block connected with the sub-block 5, finding the sub-block 6 and the sub-block 7, and beginning to calculate the path cost sum: the sum of the path costs toward the sub-block 6 is i + j = 25; the sum of the path costs in the direction of the sub-block 7 is k + l =9, and the sub-block 7 is selected for cleaning according to the result. After completion, the factor block 7 has no next uncleaned connected subblock, and returns to the previous subblock 5. Now only the sub-sector 6 is available for selection and then goes to cleaning. After completion, the factor block 6 has no next uncleaned connected sub-block, so that the previous sub-block 5 is returned, and the uncleaned sub-blocks connected to the sub-block 5 are continuously traversed, and no such sub-block exists, and the cleaning is finished.
As another example, the following describes a sweeping robot sweeping a restaurant:
as shown in fig. 4, assuming that there is a table in the center of the restaurant, similarly, the robot first generates a restaurant map including obstacle information, and then sets a cleaning line and a sub-block dividing line. In this example, although there is only one obstacle, since the obstacle is in the middle, it is necessary to take a dividing line at each of the upper and lower boundaries of the obstacle, as shown by reference numerals 2 and 5 in the drawing. Then, dividing the restaurant into 6 sub-blocks by using the dividing line and the boundary of the obstacle as boundaries, wherein the 6 sub-blocks comprise a sub-block 1 above the obstacle and a sub-block 6 below the obstacle, a sub-block 3 on the left and a sub-block 4 on the right, and a sub-block 2 and a sub-block 5 where the two dividing lines are located. Then, the sweeping path in each sub-block is planned in a zigzag manner, and the result is shown in the lower right-hand picture of fig. 4. Finally, the sequence sorting of the sub-blocks is performed according to the path cost between the sub-blocks, as shown in fig. 5, where a =5, b =6, c =7, d =6, e =2, f =1, g =10, h =15, i =13, j =12, k =4, and l = 5. Assuming that the robot cleans the sub-block 1, all sub-blocks connected with the sub-block 1 are traversed after the cleaning is completed, and only one connected sub-block 2 is found, so that the sweeping robot moves to the sub-block 2 for cleaning. After the completion, all the uncleaned sub-blocks communicated with the sub-block 2 are traversed, the sub-block 3 and the sub-block 4 are found, and the judgment is made that they belong to the same sub-block loop, at this time, the calculation mode is no longer the sum of the path costs of two different branches to and from, but the path cost of the sub-block 2 to the next sub-block is compared. As shown in fig. 5, the path cost of the sub-block 2 to the sub-block 3 is e =2, and the path cost of the sub-block 2 to the sub-block 4 is d =6, and according to the result, the robot selects to go to the sub-block 3 with smaller path cost for cleaning. After completion, all uncleaned sub-blocks that communicate with sub-block 3 are traversed to find only the uniquely communicating sub-block 5, and sub-block 5 is cleaned. And after cleaning, continuously traversing all the sub-blocks communicated with the sub-block 5, and if two sub-blocks are found, respectively calculating the sum of the path costs of the two different branches going and returning. Wherein, the sum of the path costs toward the sub-block 4 is i + j = 25; the sum of the path costs in the direction of the sub-block 6 is k + l =9, and the sub-block 6 is selected for cleaning according to the result. Upon completion, it is found that there is no next uncleaned connected sub-block and the previous sub-block 5 is returned, at which point only sub-block 4 is available for selection and the cleaning is proceeded to. After completion, the factor block 4 has no next uncleaned connected sub-block, so that the previous sub-block 5 is returned, and the uncleaned sub-blocks connected to the sub-block 5 are continuously traversed, and no such sub-block exists, and the cleaning is finished.
Those skilled in the art will appreciate that all or part of the steps in the method according to the above embodiments may be implemented by a program, which is stored in a storage medium and includes instructions for causing a single chip, a chip, or a processor (processor) to execute all or part of the steps in the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled 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; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A mobile robot full coverage path planning method is characterized by comprising the following steps:
s1, detecting obstacles in the cleaning area by the robot, generating a map containing obstacle information, and dividing the map into a plurality of sub-blocks;
s2, cleaning paths in the robot planning sub-blocks;
s3, the robot determines the starting sub-blocks and cleans the sub-blocks, then calculates the path cost among the sub-blocks, selects the next cleaned sub-block according to the path cost and circulates the steps until the cleaning of all the sub-blocks is completed.
2. The method for planning a full coverage path of a mobile robot according to claim 1, wherein the step S1 specifically comprises the following steps:
the robot detects obstacles in a cleaning area through a vision system, generates a map and reads the boundary of the map and the obstacles;
the robot sets a plurality of parallel cleaning lines on a map according to the boundary of the map and an obstacle, and the distances between the adjacent cleaning lines are equal;
the robot takes a cleaning line with two ends respectively positioned on the boundaries of two sides of the map and at least one robot radius away from the obstacle as a sub-block dividing line;
the robot divides the map into a plurality of sub-blocks by taking the sub-block dividing line and the boundaries of two sides of the barrier as boundaries.
3. The method of claim 2, wherein the cleaning line is horizontal or vertical.
4. The method of claim 2, wherein during the map segmentation, the robot regards the area where the sub-block segmentation line is located as a sub-block, and the sub-block only includes a cleaning line of the sub-block segmentation line.
5. The method as claimed in claim 1, wherein the robot passes through A*And planning a cleaning path in the sub-block by using an algorithm so that the robot walks in the sub-block in a bow shape.
6. The method for planning a full coverage path of a mobile robot according to claim 1, wherein the step S3 specifically comprises the following steps:
the robot reads the distribution condition of the sub-blocks;
the robot takes the sub-block where the robot is located as an initial sub-block;
the robot traverses all the sub-blocks which are not cleaned and are communicated with the initial sub-block, and if only one sub-block exists, the sub-block is used as the next cleaning area; if two or more sub-blocks exist, respectively calculating the sum of the path cost of each branch going and returning, and selecting the sub-block on the branch with the minimum sum of the path cost to clean; if the sub-block loops back, the path cost from the starting sub-block to the next sub-block is only needed to be compared, and the sub-block with the small path cost is selected for cleaning.
7. The method of claim 6, wherein the sub-block looping is determined by starting from a sub-block, and if a path back to the sub-block can be found without repeating the path, then all sub-blocks on the path form a sub-block looping.
8. The method of claim 6, wherein the robot, while traversing an uncleaned sub-block in communication with the starting sub-block, returns to the previous sub-block if the starting sub-block has no next connected uncleaned sub-block, and continues to traverse all connected uncleaned sub-blocks until all sub-blocks have completed cleaning.
9. A chip with a built-in control program, wherein the control program is used for controlling a robot to execute the robot full coverage path planning method according to any one of claims 1 to 8.
10. A robot equipped with a master control chip, characterized in that the master control chip is the chip of claim 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010879964.3A CN112068557A (en) | 2020-08-27 | 2020-08-27 | Mobile robot full-coverage path planning method, chip and robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010879964.3A CN112068557A (en) | 2020-08-27 | 2020-08-27 | Mobile robot full-coverage path planning method, chip and robot |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112068557A true CN112068557A (en) | 2020-12-11 |
Family
ID=73659559
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010879964.3A Pending CN112068557A (en) | 2020-08-27 | 2020-08-27 | Mobile robot full-coverage path planning method, chip and robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112068557A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112650252A (en) * | 2020-12-25 | 2021-04-13 | 珠海市一微半导体有限公司 | Path-finding cost obtaining method and chip for searching initial cleaning position |
| CN112764418A (en) * | 2020-12-25 | 2021-05-07 | 珠海市一微半导体有限公司 | Clean entrance position determination method based on path finding cost, chip and robot |
| CN112799398A (en) * | 2020-12-25 | 2021-05-14 | 珠海市一微半导体有限公司 | Cleaning path planning method based on path finding cost, chip and cleaning robot |
| CN113534822A (en) * | 2021-09-14 | 2021-10-22 | 深圳市元鼎智能创新有限公司 | Sweeping robot and path control method and device thereof |
| CN114397889A (en) * | 2021-12-22 | 2022-04-26 | 深圳市银星智能科技股份有限公司 | Full-coverage path planning method based on unit decomposition and related equipment |
| CN114600622A (en) * | 2022-03-14 | 2022-06-10 | 未岚大陆(北京)科技有限公司 | Traveling path planning method, control device, mower and self-moving system |
| CN115211765A (en) * | 2022-07-19 | 2022-10-21 | 深圳胡杨智能创新有限公司 | Cleaning robot control method, cleaning robot, and storage medium |
| WO2023019873A1 (en) * | 2021-08-18 | 2023-02-23 | 上海仙途智能科技有限公司 | Cleaning route planning |
| CN115211765B (en) * | 2022-07-19 | 2024-06-07 | 深圳胡杨智能创新有限公司 | Cleaning robot control method, cleaning robot, and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100611328B1 (en) * | 2005-06-30 | 2006-08-11 | 고려대학교 산학협력단 | Method and apparatus for building of a thinning-based topological map, method and apparatus for building of thinning-based topological map using topological exploration for a mobile robot |
| CN105739504A (en) * | 2016-04-13 | 2016-07-06 | 上海物景智能科技有限公司 | Working area ranking method and ranking system for robot |
| CN109947114A (en) * | 2019-04-12 | 2019-06-28 | 南京华捷艾米软件科技有限公司 | Robot complete coverage path planning method, device and equipment based on grating map |
| CN110595478A (en) * | 2019-09-16 | 2019-12-20 | 北京华捷艾米科技有限公司 | Robot full-coverage path planning method, device and equipment based on off-line map |
| CN110833361A (en) * | 2018-08-17 | 2020-02-25 | 速感科技（北京）有限公司 | Cleaning robot and multi-zone cleaning method thereof |
| CN110974091A (en) * | 2020-02-27 | 2020-04-10 | 深圳飞科机器人有限公司 | Cleaning robot, control method thereof, and storage medium |
-
2020
- 2020-08-27 CN CN202010879964.3A patent/CN112068557A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100611328B1 (en) * | 2005-06-30 | 2006-08-11 | 고려대학교 산학협력단 | Method and apparatus for building of a thinning-based topological map, method and apparatus for building of thinning-based topological map using topological exploration for a mobile robot |
| CN105739504A (en) * | 2016-04-13 | 2016-07-06 | 上海物景智能科技有限公司 | Working area ranking method and ranking system for robot |
| CN110833361A (en) * | 2018-08-17 | 2020-02-25 | 速感科技（北京）有限公司 | Cleaning robot and multi-zone cleaning method thereof |
| CN109947114A (en) * | 2019-04-12 | 2019-06-28 | 南京华捷艾米软件科技有限公司 | Robot complete coverage path planning method, device and equipment based on grating map |
| CN110595478A (en) * | 2019-09-16 | 2019-12-20 | 北京华捷艾米科技有限公司 | Robot full-coverage path planning method, device and equipment based on off-line map |
| CN110974091A (en) * | 2020-02-27 | 2020-04-10 | 深圳飞科机器人有限公司 | Cleaning robot, control method thereof, and storage medium |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112764418A (en) * | 2020-12-25 | 2021-05-07 | 珠海市一微半导体有限公司 | Clean entrance position determination method based on path finding cost, chip and robot |
| CN112799398A (en) * | 2020-12-25 | 2021-05-14 | 珠海市一微半导体有限公司 | Cleaning path planning method based on path finding cost, chip and cleaning robot |
| CN112650252A (en) * | 2020-12-25 | 2021-04-13 | 珠海市一微半导体有限公司 | Path-finding cost obtaining method and chip for searching initial cleaning position |
| CN112650252B (en) * | 2020-12-25 | 2024-05-07 | 珠海一微半导体股份有限公司 | Method and chip for acquiring path searching cost for searching initial cleaning position |
| CN112764418B (en) * | 2020-12-25 | 2024-04-02 | 珠海一微半导体股份有限公司 | Cleaning entrance position determining method based on path searching cost, chip and robot |
| WO2022134483A1 (en) * | 2020-12-25 | 2022-06-30 | 珠海一微半导体股份有限公司 | Pathfinding cost-based cleaning path planning method, chip, and cleaning robot |
| WO2023019873A1 (en) * | 2021-08-18 | 2023-02-23 | 上海仙途智能科技有限公司 | Cleaning route planning |
| CN113534822A (en) * | 2021-09-14 | 2021-10-22 | 深圳市元鼎智能创新有限公司 | Sweeping robot and path control method and device thereof |
| CN114397889B (en) * | 2021-12-22 | 2024-03-26 | 深圳银星智能集团股份有限公司 | Full-coverage path planning method based on unit decomposition and related equipment |
| CN114397889A (en) * | 2021-12-22 | 2022-04-26 | 深圳市银星智能科技股份有限公司 | Full-coverage path planning method based on unit decomposition and related equipment |
| CN114600622A (en) * | 2022-03-14 | 2022-06-10 | 未岚大陆(北京)科技有限公司 | Traveling path planning method, control device, mower and self-moving system |
| CN115211765A (en) * | 2022-07-19 | 2022-10-21 | 深圳胡杨智能创新有限公司 | Cleaning robot control method, cleaning robot, and storage medium |
| CN115211765B (en) * | 2022-07-19 | 2024-06-07 | 深圳胡杨智能创新有限公司 | Cleaning robot control method, cleaning robot, and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112068557A (en) | Mobile robot full-coverage path planning method, chip and robot | |
| CN105739504B (en) | A kind of sort method and ordering system of robot work region | |
| CN109240312B (en) | Cleaning control method and chip of robot and cleaning robot | |
| CN110338715B (en) | Method and chip for cleaning floor by intelligent robot and cleaning robot | |
| CN110362079B (en) | Traversal control method and chip of robot and cleaning robot | |
| JP4298917B2 (en) | Route planning method for mobile unit for surface work | |
| US20230393584A1 (en) | Cleaning Path Planning Method Based on Pathfinding cost, Chip, and Cleaning Robot | |
| WO2023155371A1 (en) | Stable movement global path planning method for indoor mobile robot | |
| CN111185899B (en) | Robot control method and robot system | |
| CN107807649A (en) | A kind of sweeping robot and its cleaning method, device | |
| CN109298717A (en) | The cleaning method and chip and Intelligent cleaning robot of intelligent robot | |
| CN112161629B (en) | Path planning method and device for cleaning robot, cleaning robot and medium | |
| CN109528090A (en) | The area coverage method and chip and clean robot of a kind of robot | |
| CN110477813B (en) | Laser type cleaning robot and control method thereof | |
| CN114035572B (en) | Obstacle avoidance tour method and system for mowing robot | |
| CN107478232A (en) | The searching method and chip in robot navigation path | |
| KR100874259B1 (en) | Cleaning robot unit and cleaning method using the cleaning robot unit | |
| CN114531903A (en) | Traveling control method and path planning method for mobile robot and mobile robot | |
| CN108189039A (en) | The mode of progression and device of a kind of mobile robot | |
| CN112764418B (en) | Cleaning entrance position determining method based on path searching cost, chip and robot | |
| CN112237403B (en) | Covering path generation method for cleaning device and cleaning device | |
| CN113219995A (en) | Path planning method and cleaning robot | |
| CN110731734B (en) | Control method and chip for planning and cleaning of intelligent robot and cleaning robot | |
| CN113467482A (en) | Cleaning path planning method of self-cleaning robot and cleaning robot | |
| CN109298716B (en) | Planning cleaning method and chip for robot |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 519000 2706, No. 3000, Huandao East Road, Hengqin new area, Zhuhai, Guangdong Applicant after: Zhuhai Yiwei Semiconductor Co.,Ltd. Address before: Room 105-514, No.6 Baohua Road, Hengqin New District, Zhuhai City, Guangdong Province Applicant before: AMICRO SEMICONDUCTOR Co.,Ltd. |
|
| CB02 | Change of applicant information |