CN114131618A - Intelligent robot keeps away barrier system based on thing networking - Google Patents
Intelligent robot keeps away barrier system based on thing networking Download PDFInfo
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- CN114131618A CN114131618A CN202111654330.9A CN202111654330A CN114131618A CN 114131618 A CN114131618 A CN 114131618A CN 202111654330 A CN202111654330 A CN 202111654330A CN 114131618 A CN114131618 A CN 114131618A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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Abstract
The invention discloses an intelligent robot obstacle avoidance system based on the Internet of things, which belongs to the technical field of robots and comprises a path module, an acquisition module, a server, a storage module and an obstacle module, wherein high-definition images of alternative paths and transfer paths are acquired, backgrounds in the high-definition images are segmented to obtain background-free images, image outlines in the background-free images are extracted, an obstacle outline library is established, obstacle information corresponding to the obstacle outlines in the obstacle outline library is set, the extracted image outlines in the background-free images are matched with the obstacle outline library to obtain obstacle information, position stamps and time stamps are printed on the obstacle information, the obstacle information is sent to the server, and then the obstacle information is sent to the storage module to be stored by the server; the method has the advantages that the environmental information on the alternative path and the transfer path is collected in advance, when the main path is blocked and cannot pass through, the alternative path without barriers can be quickly obtained, the working efficiency is improved, and long-time waiting is avoided.
Description
Technical Field
The invention belongs to the technical field of robots; in particular to an intelligent robot obstacle avoidance system based on the Internet of things.
Background
With the continuous progress of science and technology, the field of intelligent robots is rapidly developed. Because intelligent robot can replace the workman and carry the material, be favorable to using manpower sparingly, reduce cost improves handling efficiency to make intelligent robot wide application in logistics storage and intelligent factory production line. However, the robot often encounters an obstacle to block the movement of the robot in the process of traveling, and the working efficiency of the robot is affected, so that an intelligent robot obstacle avoidance system based on the internet of things is urgently needed to be provided, and the problem that the robot avoids obstacles is solved.
Disclosure of Invention
The invention aims to provide an intelligent robot obstacle avoidance system based on the Internet of things, and the problem that a robot avoids obstacles is solved. Acquiring environmental information on an alternative path and a transfer path through an acquisition module, acquiring high-definition images of the alternative path and the transfer path, segmenting a background in the high-definition images to acquire background-free images, extracting image outlines in the background-free images, establishing an obstacle outline library, setting corresponding obstacle information for obstacle outlines in the obstacle outline library, matching the extracted image outlines in the background-free images with the obstacle outline library to acquire obstacle information, stamping position stamps and time stamps on the obstacle information, sending the obstacle information to a server, and sending the obstacle information to a storage module for storage through the server; the method has the advantages that the environmental information on the alternative path and the transfer path is collected in advance, when the main path is blocked and cannot pass through, the alternative path without barriers can be quickly obtained, the working efficiency is improved, and long-time waiting is avoided.
The purpose of the invention can be realized by the following technical scheme:
the utility model provides an intelligent robot keeps away barrier system based on thing networking, includes route module, collection module, server, storage module and obstacle module, the route module is used for planning the removal route of robot, and the concrete method includes: acquiring a drawing of a working area of the robot, establishing a three-dimensional model according to the acquired drawing of the working area, setting a working range of the robot, marking the working range of the robot to a corresponding position in the three-dimensional model, acquiring model parameters of the robot, establishing a data model of the robot according to the model parameters of the robot, inputting the data model of the robot into the three-dimensional model, setting selectable moving paths of the robot according to the size of the robot and the path size in the working range, scoring the selectable moving paths, selecting the path with the highest score as a main selection path from the selectable moving paths, selecting N alternative paths according to scoring sequence, and setting a transfer path between the alternative paths and the main selection path;
the acquisition module is used for acquiring environment information on the alternative path and the transfer path; the obstacle module is used for avoiding obstacles in the moving process of the robot, and the specific method comprises the following steps: scanning obstacles on an advancing route in real time, setting an early warning area, and not operating when the obstacles are not scanned; when the obstacle is scanned, the type of the obstacle is identified, when the obstacle is a person, an alarm sound is given out to prompt a crowd to leave the traveling route of the robot, when the crowd does not leave and enters an early warning area, crowd images are collected, time stamps and position stamps are printed on the crowd images, the crowd images are sent to a server, the server sends obstacle information to a storage module for storage, an alternative path without the obstacle is obtained, an alternative path is selected as a temporary main path according to path scores, and the temporary main path is moved to the temporary main path through a transfer path; when the obstacle is an article, acquiring an article image, stamping a time stamp and a position stamp on the article image, sending the article image to an administrator, acquiring an alternative path without the obstacle, selecting an alternative path as a temporary main path according to the path score, and moving the alternative path to the temporary main path through a transfer path.
Further, the method for acquiring the environmental information on the alternative path and the transfer path by the acquisition module comprises the following steps: the method comprises the steps of obtaining high-definition images of an alternative path and a transfer path, segmenting a background in the high-definition images to obtain background-free images, extracting image outlines in the background-free images, establishing an obstacle outline library, setting corresponding obstacle information for the obstacle outlines in the obstacle outline library, matching the extracted image outlines in the background-free images with the obstacle outline library to obtain obstacle information, stamping position stamps and time stamps on the obstacle information, sending the obstacle information to a server, and sending the obstacle information to a storage module for storage.
Further, the method for scoring the selectable movement path comprises the following steps: marking the selectable paths as i, wherein i is 1, 2, … …, n, and n is the number of the selectable paths; obtaining the length of the selectable path, marking the length of the selectable path as Pi, obtaining the width of the selectable path, scoring the width of the selectable path, marking the width score of the selectable path as Li, obtaining the movement difficulty score of the selectable path, marking the movement difficulty score of the selectable path as Ki, removing dimensions of the selectable path, the length of the selectable path, the width score of the selectable path and the movement difficulty score of the selectable path, and taking the values to calculate, obtaining the path score Qi according to a formula Qi ═ lambda [ b2 ═ Li/(b1 × Pi + b3 × Ki +1) ], wherein b1, b2 and b3 are all proportional coefficients, the value range is 1< b1 ≦ 2, 0< b2<1, 0< b3<1, lambda is a correction factor, and the value range is 1< lambda ≦ 2; the path scores Qi are ranked from large to small.
Further, the method of obtaining a background-free image includes: the method comprises the steps of preprocessing an image, marking the image after image preprocessing as a gray image, establishing an image gray value three-dimensional coordinate system by taking the center of the image as an origin, inputting the gray value of the image into the gray value three-dimensional coordinate system, connecting adjacent gray value points of the same image by using a smooth curve to form a gray value curved surface, acquiring background images of an alternative path and a transfer path, preprocessing the background images, marking the image after image preprocessing as a background gray image, inputting the background gray image into the gray value three-dimensional coordinate system, segmenting the background in the image according to the gray value, and marking the segmented image as a background-free image.
Further, when an alternative path without an obstacle is obtained, when the alternative path has obstacles, obtaining obstacle information, sequencing the alternative paths according to the mobility of the obstacles in the obstacle information, sequentially sending warning information to the obstacles on the alternative path, collecting environment information on the alternative path in real time through a collection module, when the obstacle on the alternative path is removed, changing the corresponding alternative path into a temporary main path, and informing other alternative paths that the alternative path switching is completed; and when no barrier on the alternative path moves away, generating a trap signal and sending the trap signal to an administrator.
The invention has the beneficial effects that: planning a moving path of the robot through a path module, acquiring a drawing of a working area of the robot, establishing a three-dimensional model according to the acquired drawing of the working area, setting a working range of the robot, marking the working range of the robot to a corresponding position in the three-dimensional model, acquiring model parameters of the robot, establishing a data model of the robot according to the model parameters of the robot, inputting the data model of the robot into the three-dimensional model, setting an optional moving path of the robot according to the size of the robot and the path size in the working range, grading the optional moving path, selecting the path with the highest grade from the optional moving paths as a main selecting path, selecting N alternative paths according to grading sequencing, setting a transferring path between the alternative paths and the main selecting path, and transferring the path to other paths through the transferring path when the path cannot pass, the problem of waiting for a long time when the path cannot pass is solved, and the working efficiency can be greatly improved by setting the alternative path;
acquiring environmental information on an alternative path and a transfer path through an acquisition module, acquiring high-definition images of the alternative path and the transfer path, segmenting a background in the high-definition images to acquire background-free images, extracting image outlines in the background-free images, establishing an obstacle outline library, setting corresponding obstacle information for obstacle outlines in the obstacle outline library, matching the extracted image outlines in the background-free images with the obstacle outline library to acquire obstacle information, stamping position stamps and time stamps on the obstacle information, sending the obstacle information to a server, and sending the obstacle information to a storage module for storage through the server; the method has the advantages that the environmental information on the alternative path and the transfer path is collected in advance, when the main path is blocked and cannot pass through, the alternative path without barriers can be quickly obtained, the working efficiency is improved, and long-time waiting is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
As shown in fig. 1, an intelligent robot obstacle avoidance system based on the internet of things includes a path module, an acquisition module, a server, a storage module, and an obstacle module.
The path module is used for planning the moving path of the robot, and the specific method comprises the following steps: the method comprises the steps of obtaining a drawing of a working area of a robot, establishing a three-dimensional model according to the obtained drawing of the working area, setting a working range of the robot, marking the working range of the robot to a corresponding position in the three-dimensional model, obtaining model parameters of the robot, wherein the model parameters are design parameters of the robot and comprise parameters such as size, speed and the like, establishing a data model of the robot according to the model parameters of the robot, zooming the data model and the three-dimensional model of the robot according to the same proportion, inputting the data model of the robot into the three-dimensional model, setting selectable moving paths of the robot according to the size of the robot and the path size in the working range, wherein the selectable moving paths are multiple, as long as the paths capable of ensuring the movement of the robot can be used as the selectable moving paths, scoring the selectable moving paths, selecting the path with the highest score as a main selection path from the selectable moving paths, then N alternative paths are selected according to the grading sequence, N is a proportionality coefficient, and N is more than or equal to 8 and more than or equal to 3; and a transfer path is arranged between the alternative path and the main path, and the transfer path is used for transferring to other paths through the transfer path when the path cannot pass through.
The method for scoring the optional moving path comprises the following steps: marking the selectable paths as i, wherein i is 1, 2, … …, n, and n is the number of the selectable paths; obtaining the length of the selectable path, marking the length of the selectable path as Pi, obtaining the width of the selectable path, wherein the width of the selectable path is influenced by the path size in the working range of the robot, the path size in the working range is large, the width of the selectable path is scored, the scoring of the width of the selectable path is scored according to the path size in the working range of the robot, the scoring of the width of the selectable path is marked as Li, and the scoring of the movement difficulty of the selectable path is obtained, because some paths are straight and some paths are in a broken line form, obstacles pass through a contact movement channel, so the movement difficulty of the robot is different, the scoring of the movement difficulty of the selectable path is carried out according to the difference of the movement difficulty, the scoring of the movement difficulty of the selectable path is marked as Ki, and the scoring of the movement difficulty of the selectable path, the length of the selectable path, the width of the selectable path and the scoring of the movement difficulty of the selectable path are subjected to removal measurement, and the numerical calculation is carried out, obtaining a path score Qi according to a formula Qi-lambda [ b 2-Li/(b 1-Pi + b 3-Ki +1) ], wherein b1, b2 and b3 are all proportional coefficients, the value range is 1< b1 or less than 2, 0< b2<1, 0< b3<1, lambda is a correction factor, and the value range is 1< lambda or less than 2; the path scores Qi are ranked from large to small.
The acquisition module is used for acquiring environment information on the alternative path and the transfer path, wherein the environment information is whether obstacles are added on the path, and the specific method comprises the following steps: acquiring high-definition images of the alternative path and the transfer path, segmenting a background in the high-definition images to acquire background-free images, extracting image contours in the background-free images, establishing an obstacle contour library, storing contour information according to obstacles possibly appearing in the working range of the robot, corresponding obstacle information is set for the obstacle outline in the obstacle outline library, the obstacle information comprises the name of the obstacle and the mobility, the mobility means that the obstacle is inconvenient to move, for example, when the obstacle is a person, the obstacle is convenient to move, the mobility is high, the image contour in the extracted background-free image is matched with the obstacle contour library to obtain obstacle information, the obstacle information is printed with a position stamp and a time stamp, the obstacle information is sent to the server, and the server sends the obstacle information to the storage module for storage.
The method for obtaining the background-free image comprises the following steps: the method comprises the steps of preprocessing an image, marking the image after image preprocessing as a gray image, wherein the image preprocessing comprises image segmentation, image denoising, image enhancement and gray conversion, establishing an image gray value three-dimensional coordinate system by taking an image center as an origin, inputting image gray values into the gray value three-dimensional coordinate system, connecting adjacent gray value points of the same image by using a smooth curve to form a gray value curved surface, obtaining a background image of an alternative path and a transfer path, wherein the background image is a path image without an obstacle, preprocessing the background image, marking the image after image preprocessing as the background gray image, inputting the background gray image into the gray value three-dimensional coordinate system, segmenting the background in the image according to the gray values, and marking the segmented image as the background-free image.
The obstacle module is used for avoiding obstacles in the moving process of the robot, and the specific method comprises the following steps: scanning obstacles on an advancing route in real time, and setting an early warning area, wherein the early warning area is set according to the running parameters of the robot, the running parameters of the robot comprise speed, and when the obstacles are not scanned, the operation is not carried out; when an obstacle is scanned, the obstacle type is identified, the obstacle type can be judged through infrared scanning, whether the obstacle is a person or an article is judged, when the obstacle is a person, an alarm sound is sent out to prompt a crowd to leave a robot traveling route, when the crowd does not leave and enters an early warning area, crowd images are collected, time stamps and position stamps are applied to the crowd images, the crowd images are sent to a server, the server sends obstacle information to a storage module for storage, an alternative path without the obstacle is obtained, an alternative path is selected as a temporary main path according to path scores, and the temporary main path is moved to the temporary main path through a transfer path; when the obstacle is an article, acquiring an article image, stamping a time stamp and a position stamp on the article image, sending the article image to an administrator, acquiring an alternative path without the obstacle, selecting an alternative path as a temporary main path according to the path score, and moving the alternative path to the temporary main path through a transfer path.
Further, when an alternative path without an obstacle is obtained, when the alternative path has obstacles, obtaining obstacle information, sequencing the alternative paths according to the mobility of the obstacles in the obstacle information, sequentially sending warning information to the obstacles on the alternative path, collecting environment information on the alternative path in real time through a collection module, when the obstacle on the alternative path is removed, changing the corresponding alternative path into a temporary main path, and informing other alternative paths that the alternative path switching is completed; when no barrier on the alternative path is removed, a trapping signal is generated and sent to an administrator, the administrator wears the mobile terminal, namely the trapping signal is sent to the mobile terminal, and a traveling path is cleared out in a manual dredging mode.
The above formulas are all calculated by removing dimensions and taking values thereof, the formula is one closest to the real situation obtained by collecting a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
When the invention is used, the moving path of the robot is planned, the drawing of the working area of the robot is obtained, establishing a three-dimensional model according to the obtained working area drawing, setting the working range of the robot, marking the working range of the robot to the corresponding position in the three-dimensional model, obtaining the model parameters of the robot, establishing a data model of the robot according to the model parameters of the robot, inputting the data model of the robot into the three-dimensional model, the selectable movement path of the robot is set according to the size of the robot and the path size in the working range, scoring the selectable moving paths, selecting the path with the highest score as a main path from the selectable moving paths, selecting N alternative paths according to the score sequence, a transfer path is arranged between the alternative path and the main path, and the transfer path is used for transferring to other paths through the transfer path when the path cannot pass through; the path scores Qi are obtained according to the formula Qi ═ λ ═ b2 ═ Li/(b1 × Pi + b3 × Ki +1), and the path scores Qi are arranged from large to small.
Acquiring environment information on an alternative path and a transfer path, acquiring high-definition images of the alternative path and the transfer path, segmenting a background in the high-definition images, acquiring background-free images, extracting image outlines in the background-free images, establishing an obstacle outline library, setting corresponding obstacle information for obstacle outlines in the obstacle outline library, matching the extracted image outlines in the background-free images with the obstacle outline library to acquire obstacle information, stamping position stamps and time stamps on the obstacle information, sending the obstacle information to a server, and sending the obstacle information to a storage module by the server for storage; the method for obtaining the background-free image comprises the following steps: the method comprises the steps of preprocessing an image, marking the image after image preprocessing as a gray image, establishing an image gray value three-dimensional coordinate system by taking the center of the image as an origin, inputting the gray value of the image into the gray value three-dimensional coordinate system, connecting adjacent gray value points of the same image by using a smooth curve to form a gray value curved surface, acquiring background images of an alternative path and a transfer path, preprocessing the background images, marking the image after image preprocessing as a background gray image, inputting the background gray image into the gray value three-dimensional coordinate system, segmenting the background in the image according to the gray value, and marking the segmented image as a background-free image.
The obstacle module is used for avoiding obstacles in the moving process of the robot, and the specific method comprises the following steps: scanning obstacles on an advancing route in real time, setting an early warning area, and not operating when the obstacles are not scanned; when the obstacle is scanned, the type of the obstacle is identified, when the obstacle is a person, an alarm sound is given out to prompt a crowd to leave the traveling route of the robot, when the crowd does not leave and enters an early warning area, crowd images are collected, time stamps and position stamps are printed on the crowd images, the crowd images are sent to a server, the server sends obstacle information to a storage module for storage, an alternative path without the obstacle is obtained, an alternative path is selected as a temporary main path according to path scores, and the temporary main path is moved to the temporary main path through a transfer path; when the obstacle is an article, acquiring an article image, stamping a time stamp and a position stamp on the article image, sending the article image to an administrator, acquiring an alternative path without the obstacle, selecting one alternative path as a temporary main path according to a path score, and moving the alternative path to the temporary main path through a transfer path; when an alternative path without obstacles is obtained, when the alternative path has obstacles, obtaining obstacle information, sequencing the alternative paths according to the mobility of the obstacles in the obstacle information, sequentially sending warning information to the obstacles on the alternative path, acquiring environmental information on the alternative path in real time through an acquisition module, changing the corresponding alternative path into a temporary main path when the obstacles on the alternative path are removed, and informing other alternative paths that alternative path switching is completed; and when no barrier on the alternative path moves away, generating a trap signal and sending the trap signal to an administrator.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. An intelligent robot obstacle avoidance system based on the Internet of things is characterized by comprising a path module, an acquisition module, a server, a storage module and an obstacle module;
the path module is used for planning a moving path of the robot, and specifically comprises the following steps: acquiring a drawing of a working area of the robot, establishing a three-dimensional model according to the acquired drawing of the working area, setting a working range of the robot, marking the working range of the robot to a corresponding position in the three-dimensional model, acquiring model parameters of the robot, establishing a data model of the robot according to the model parameters of the robot, inputting the data model of the robot into the three-dimensional model, setting selectable moving paths of the robot according to the size of the robot and the path size in the working range, scoring the selectable moving paths, selecting the path with the highest score as a main selection path from the selectable moving paths, selecting N alternative paths according to scoring sequence, and setting a transfer path between the alternative paths and the main selection path;
the acquisition module is used for acquiring environment information on the alternative path and the transfer path;
the obstacle module is used for the robot to avoid the obstacle in the removal process, specifically is: scanning obstacles on an advancing route in real time, setting an early warning area, and not operating when the obstacles are not scanned; when the obstacle is scanned, the type of the obstacle is identified, when the obstacle is a person, an alarm sound is given out to prompt a crowd to leave the traveling route of the robot, when the crowd does not leave and enters an early warning area, crowd images are collected, time stamps and position stamps are printed on the crowd images, the crowd images are sent to a server, the server sends obstacle information to a storage module for storage, an alternative path without the obstacle is obtained, an alternative path is selected as a temporary main path according to path scores, and the temporary main path is moved to the temporary main path through a transfer path; when the obstacle is an article, acquiring an article image, stamping a time stamp and a position stamp on the article image, sending the article image to an administrator, acquiring an alternative path without the obstacle, selecting an alternative path as a temporary main path according to the path score, and moving the alternative path to the temporary main path through a transfer path.
2. The intelligent robot obstacle avoidance system based on the internet of things as claimed in claim 1, wherein the method for the acquisition module to acquire the environmental information on the alternative path and the transfer path comprises: the method comprises the steps of obtaining high-definition images of an alternative path and a transfer path, segmenting a background in the high-definition images to obtain background-free images, extracting image outlines in the background-free images, establishing an obstacle outline library, setting corresponding obstacle information for the obstacle outlines in the obstacle outline library, matching the extracted image outlines in the background-free images with the obstacle outline library to obtain obstacle information, stamping position stamps and time stamps on the obstacle information, sending the obstacle information to a server, and sending the obstacle information to a storage module for storage.
3. The intelligent robot obstacle avoidance system based on the internet of things as claimed in claim 1, wherein the method for scoring the selectable movement path comprises: marking the selectable path as i, obtaining the length of the selectable path, marking the length of the selectable path as Pi, obtaining the width of the selectable path, scoring the width of the selectable path, marking the width score of the selectable path as Li, obtaining the movement difficulty score of the selectable path, marking the movement difficulty score of the selectable path as Ki, removing dimensions of the selectable path, the length of the selectable path, the width score of the selectable path and the movement difficulty score of the selectable path, obtaining the numerical value of the numerical value for calculation, obtaining the path score Qi according to a formula Qi-lambda [ b2 Li/(b1 Pi + b3 Ki +1) ], and arranging the path scores Qi from large to small.
4. The intelligent robot obstacle avoidance system based on the internet of things as claimed in claim 2, wherein the method for obtaining the background-free image comprises: the method comprises the steps of preprocessing an image, marking the image after image preprocessing as a gray image, establishing an image gray value three-dimensional coordinate system by taking the center of the image as an origin, inputting the gray value of the image into the gray value three-dimensional coordinate system, connecting adjacent gray value points of the same image by using a smooth curve to form a gray value curved surface, acquiring background images of an alternative path and a transfer path, preprocessing the background images, marking the image after image preprocessing as a background gray image, inputting the background gray image into the gray value three-dimensional coordinate system, segmenting the background in the image according to the gray value, and marking the segmented image as a background-free image.
5. The intelligent robot obstacle avoidance system based on the Internet of things according to claim 1, characterized in that when alternative paths without obstacles are obtained, when the alternative paths all have obstacles, obstacle information is obtained, the alternative paths are sequenced according to the mobility of the obstacles in the obstacle information, warning information is sequentially sent to the obstacles on the alternative paths, environmental information on the alternative paths is collected through the collection module in real time, when the obstacles on the alternative paths are removed, the corresponding alternative paths are changed into temporary main paths, and other alternative paths are informed that alternative path switching is completed; and when no barrier on the alternative path moves away, generating a trap signal and sending the trap signal to an administrator.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114905180A (en) * | 2022-06-30 | 2022-08-16 | 中船黄埔文冲船舶有限公司 | Obstacle avoidance welding path optimization method and device for intermediate assembly welding line |
| CN118331282A (en) * | 2024-06-13 | 2024-07-12 | 四川大学 | Barrier avoiding method, device and system for desert tree planting robot |
-
2021
- 2021-12-30 CN CN202111654330.9A patent/CN114131618A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114905180A (en) * | 2022-06-30 | 2022-08-16 | 中船黄埔文冲船舶有限公司 | Obstacle avoidance welding path optimization method and device for intermediate assembly welding line |
| CN118331282A (en) * | 2024-06-13 | 2024-07-12 | 四川大学 | Barrier avoiding method, device and system for desert tree planting robot |
| CN118331282B (en) * | 2024-06-13 | 2024-08-20 | 四川大学 | Barrier avoiding method, device and system for desert tree planting robot |
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Application publication date: 20220304 |