CN113467468B - Intelligent robot obstacle avoidance system and method based on embedded robot - Google Patents
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- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
- G05D1/0251—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision
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- G05D1/02—Control of position or course in two dimensions
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- 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
- G05D1/0285—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using signals transmitted via a public communication network, e.g. GSM network
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Abstract
The invention discloses an intelligent obstacle avoidance system and method based on an embedded robot, relates to the technical field of robot control, and solves the technical problem that in the existing scheme, the robot cannot acquire obstacle information of a visual field blind area in the moving process, so that the planned path is low in accuracy; the system comprises an embedded processor, a data storage module, a terminal control module, an environment acquisition module, an execution control module and a visual field acquisition module; the invention is provided with the environment acquisition module and the visual field acquisition module, not only can identify the obstacle in the visual field of the robot, but also can identify the obstacle in the blind area of the visual field of the robot, and the obstacle in the moving process of the robot is comprehensively considered, so that the accuracy and timeliness of obstacle avoidance of the robot are improved; the invention sets the execution control module to adjust the speed of the robot in real time according to the movement control label in the moving process of the robot, and reduces the probability of collision between the robot and the obstacle.
Description
Technical Field
The invention belongs to the field of robot control, relates to an intelligent obstacle avoidance technology of a robot, and particularly relates to an intelligent obstacle avoidance system and method based on an embedded robot.
Background
With the continuous development of science and technology, robots can realize functions of voice interaction, visual detection, obstacle avoidance and the like. At present, the avoidance obstacle of the robot can be realized through a vibration sensor or an ultrasonic sensor, and also can be realized through technologies such as visual detection, voice interaction and the like, but the two schemes cannot achieve the balance between cost and accuracy.
The invention patent with publication number of CN112171667A discloses an intelligent obstacle avoidance system and an obstacle avoidance method based on an embedded picking robot, wherein the system comprises an embedded processor, a terminal control system, a sensor, a camera and a robot driving device, and the sensor and an image recognition technology are combined to sense the working environment so as to realize the obstacle avoidance control of the robot.
The scheme can implement monitoring, improves the accuracy of robot path planning and reduces the time cost, but only considers the obstacle information seen by the 'visual field' of the robot when the path planning is carried out, can not predict the obstacle information in the blind area of the visual field of the robot, and is easy to cause accidents or reduce the working efficiency; therefore, a need exists for a robot intelligent obstacle avoidance system and method.
Disclosure of Invention
The invention provides an intelligent obstacle avoidance system and method based on an embedded robot, which are used for solving the technical problem that the accuracy of a planned path is low because obstacle information of a visual field blind area cannot be acquired in the moving process of the robot in the existing scheme.
The aim of the invention can be achieved by the following technical scheme: an intelligent obstacle avoidance system based on an embedded robot comprises an embedded processor and a data storage module; the data storage module is used for storing data generated in the running process of the system;
the embedded processor is respectively in communication and/or electrical connection with the terminal control module, the environment acquisition module and the execution control module; the environment acquisition module is in communication and/or electrical connection with the visual field acquisition module;
the terminal control module is used for sending the target position to the embedded processor; the visual field acquisition module is in communication and/or electrical connection with a high-definition camera of a robot working area;
when the embedded processor receives the target position, planning a path of the robot by combining the current position of the robot, and marking the path as a planned path;
the environment acquisition module acquires environment data through an environment sensor and analyzes the environment data to obtain an environment analysis tag; wherein the environmental analysis tag comprises a first type tag and a second type tag;
when the environment analysis tag is a first type tag, performing obstacle warning through a terminal control module; when the environment analysis tag is a second type tag, the visual field blind area analysis is carried out by combining the visual field acquisition module, and a mobile control tag is set;
and controlling the robot to run according to the mobile control tag through the execution control module.
Preferably, the obtaining of the environmental analysis tag includes:
acquiring a planned path, acquiring a real-time image of the advancing direction of the robot through a high-definition camera, and acquiring an obstacle in the real-time image through an image recognition technology;
when no obstacle exists in the real-time image or the obstacle is not in the preset range of the robot, setting the environment analysis tag to be 2, namely a second type tag;
when the obstacle of the real-time image is in the preset range of the robot, the environment analysis tag is set to be 1, namely the first type tag.
Preferably, the preset range is a safety space for movement of the robot, and the shape of the preset range includes a circle and a sphere.
Preferably, when the environmental analysis tag is a second type tag, the view blind zone analysis includes:
dividing a planned path into a plurality of path segments;
respectively acquiring the vibration intensity and the sound intensity of the next path segment in the advancing direction through a vibration sensor and an ultrasonic sensor, and respectively marking the vibration intensity and the sound intensity as ZQ and SQ; obtaining an environment evaluation coefficient HPX by the formula hpx=α1×zq+α2×sq; wherein, alpha 1 and alpha 2 are both proportionality coefficients greater than 0;
when the environment evaluation coefficient HPX is larger than the evaluation coefficient threshold value, acquiring a visual field image through a high-definition camera of a robot working area; wherein the evaluation coefficient threshold is a real number greater than 0;
and acquiring the obstacle of the visual field image through an image recognition technology, when the distance between the obstacle and the boundary of the preset range is smaller than a distance threshold value, judging that the obstacle in the path segment can influence the movement of the robot, setting the movement control label of the corresponding path segment to be 1, and otherwise, setting the movement control label of the corresponding path segment to be 2.
Preferably, the execution control module controls the robot to move, including:
acquiring a mobile control tag of a path segment in real time, and controlling the robot to move according to a planned path according to a set speed of the robot when the mobile control tag is 2;
when the control tag 1 is moved, the moving speed of the robot is adjusted to pass through the corresponding path segment.
Preferably, the environment sensor comprises at least two high-definition cameras, a vibration sensor and an ultrasonic sensor; the high-definition cameras in the environment sensor are arranged on the robot, and the vibration sensor and the ultrasonic sensor are arranged on the robot or on the moving path of the robot.
Preferably, the data processing module is respectively in communication and/or electrical connection with the embedded processor and the terminal control module; the environment acquisition module is respectively in communication and/or electric connection with the terminal control module and the execution control module.
An intelligent obstacle avoidance method based on an embedded robot comprises the following steps:
the method comprises the steps that a target position is sent to an embedded processor through a terminal control module, and the embedded processor obtains a planning path according to the target position and the current position of a robot;
the environment acquisition module acquires a real-time image of the advancing direction of the robot and identifies obstacles in the real-time image; setting an environment analysis tag according to the obstacle recognition result; when the environment analysis tag is a first type tag, performing obstacle warning through a terminal control module;
when the environment analysis tag is a second type tag, dividing the planned path into a plurality of path segments; respectively acquiring the vibration intensity and the sound intensity of the next path segment in the advancing direction through a vibration sensor and an ultrasonic sensor, and respectively marking the vibration intensity and the sound intensity as ZQ and SQ; obtaining an environment evaluation coefficient HPX by the formula hpx=α1×zq+α2×sq; wherein, alpha 1 and alpha 2 are both proportionality coefficients greater than 0;
when the environment evaluation coefficient HPX is larger than the evaluation coefficient threshold value, acquiring a visual field image through a high-definition camera of a robot working area; acquiring an obstacle of a visual field image through an image recognition technology, judging that the obstacle in a path segment can influence the movement of a robot when the distance between the obstacle and the boundary of a preset range is smaller than a distance threshold, setting a movement control tag of a corresponding path segment to be 1, otherwise, setting the movement control tag of the corresponding path segment to be 2; wherein the evaluation coefficient threshold is a real number greater than 0;
acquiring a mobile control tag of a path segment in real time, and controlling the robot to move according to a planned path according to a set speed of the robot when the mobile control tag is 2; when the control tag 1 is moved, the moving speed of the robot is adjusted to pass through the corresponding path segment.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is provided with an environment acquisition module and a visual field acquisition module; the environment acquisition module acquires a real-time image of the advancing direction of the robot and identifies obstacles in the real-time image; setting an environment analysis tag according to the obstacle recognition result; when the environment analysis tag is a first type tag, performing obstacle warning, when the environment analysis tag is a second type tag, acquiring an environment evaluation coefficient of a path segment, when the environment evaluation coefficient is larger than an evaluation coefficient threshold, acquiring a visual field image through a high-definition camera of a robot working area, and when the distance between an obstacle and a preset range boundary is smaller than a distance threshold, judging that the obstacle in the path segment can influence the movement of the robot, setting a movement control tag of the corresponding path segment to be 1, otherwise, setting the movement control tag of the corresponding path segment to be 2; the arrangement of the environment acquisition module and the visual field acquisition module can not only identify the obstacle in the visual field of the robot, but also identify the obstacle in the blind area of the visual field of the robot, and the obstacle in the moving process of the robot is comprehensively considered, so that the accuracy and timeliness of obstacle avoidance of the robot are improved.
2. The invention is provided with an execution control module; acquiring a mobile control tag of a path segment in real time, and controlling the robot to move according to a planned path according to a set speed of the robot when the mobile control tag is 2; when the control tag 1 is moved, the moving speed of the robot is adjusted to pass through the corresponding path segment; the execution control module can adjust the speed of the robot in real time according to the movement control label in the moving process of the robot, and the probability of collision between the robot and an obstacle is reduced.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terminology used herein is for the purpose of describing embodiments and is not intended to limit and/or restrict the disclosure; it should be noted that the singular forms "a", "an" and "the" include plural forms as well, unless the context clearly indicates otherwise; moreover, although the terms "first," "second," etc. may be used herein to describe various elements, the elements are not limited by these terms, and these terms are merely used to distinguish one element from another element.
Referring to fig. 1, an intelligent obstacle avoidance system based on an embedded robot includes:
the method comprises the steps that a target position is sent to an embedded processor through a terminal control module, and the embedded processor obtains a planning path according to the target position and the current position of a robot; the terminal control module comprises a smart phone, a tablet personal computer and a common controller.
The path planning in the embodiment performs planning according to a drawing of a working area or three-dimensional modeling, so as to avoid accidents caused by the fact that a robot encounters an object such as a storage rack in the moving process, wherein the path planning algorithm comprises a simulated annealing algorithm, a manual potential field method, a fuzzy logic algorithm, a tabu search algorithm, a C-space method, a grid method, a free space method, a voronoi diagram method, an ant colony algorithm, a neural network algorithm, a particle swarm algorithm and a genetic algorithm; in other preferred embodiments, when the work area does not have an object such as a storage rack, the planned path can be obtained directly according to the path planning algorithm without referring to the work area drawing or model.
The environment acquisition module acquires a real-time image of the advancing direction of the robot and identifies obstacles in the real-time image; setting an environment analysis tag according to the obstacle recognition result; when the environment analysis tag is a first type tag, performing obstacle warning through a terminal control module; and when the environment analysis tag is a second type tag, performing visual field blind area analysis by combining the visual field acquisition module, and setting a mobile control tag. In this embodiment, a real-time image of a forward direction in a planned path of a robot is acquired first, and when an obstacle exists in the real-time image, an environmental analysis tag is set to be a first type tag, and obstacle early warning is performed through a terminal control module, wherein the obstacle may be a static obstacle, such as a scaffold, piled goods, or a dynamic obstacle, such as a moving cart and a worker. The real-time image in this embodiment is obtained by a high-definition camera disposed on the robot body.
When the environment analysis tag is a second type tag, dividing the planned path into a plurality of path segments, acquiring environment evaluation coefficients of the plurality of path segments, and setting a mobile control tag in combination with the view image. In this embodiment, it is mainly considered that when the robot advances along the planned path, the obstacle is moved out from between the two storage frames, and therefore, the obstacle is moved by the high-definition camera of the working area, and the movement control tag is set according to the distance between the obstacle and the boundary of the preset range. The preset range in the embodiment is specifically a regular range including a robot, and may be circular or spherical; when the preset range is round or spherical, the center of gravity of the robot is used as the center of a circle or sphere center, and a fixed value, such as 1 meter, is used as the radius to acquire a corresponding round or sphere; but may also be rectangular or cubic.
And acquiring a movement control tag of the next path segment in the advancing direction of the robot in real time, and controlling the movement speed of the robot according to the movement control tag. In this embodiment, the control of the moving speed includes acceleration, deceleration and stopping, so that the collision between the robot and the obstacle can be effectively avoided in time.
Next, the symbol of the technical solution in the present application is materialized to further explain the workflow thereof:
the method comprises the steps that a target position is sent to an embedded processor through a terminal control module, the embedded processor obtains a planned path according to the target position and the current position of a robot, and the planned path is sent to an environment acquisition module;
acquiring a real-time image of the advancing direction of the robot according to the planned path through a high-definition camera, identifying an obstacle in the real-time image through an image identification technology, setting an environment analysis tag as a second type tag when the obstacle does not exist in the real-time image or is not in a preset range of the robot, and setting the environment analysis tag as a first type tag when the obstacle in the real-time image is in the preset range of the robot; when the environment analysis tag is a first type tag, performing obstacle warning through a terminal control module;
when the environment analysis tag is a second type tag, dividing the planned path into a plurality of path segments; respectively acquiring the vibration intensity and the sound intensity of the next path segment in the advancing direction through a vibration sensor and an ultrasonic sensor, wherein the vibration intensity is 1 and the sound intensity is 1; the environment evaluation coefficient hpx=2 is obtained by the formula hpx=1×1+1×1;
when the evaluation coefficient threshold is 1, the environment evaluation coefficient HPX is larger than the evaluation coefficient threshold, and a visual field image is obtained through a high-definition camera of a robot working area; the high-definition camera in this embodiment is disposed on the top of the working area or on each moving track.
Acquiring an obstacle of a view image through an image recognition technology, when the distance between the obstacle and a boundary of a preset range is smaller than a distance threshold, determining that the obstacle in a path segment can influence the movement of a robot, wherein the distance between the obstacle and the boundary of the preset range is the shortest distance between the obstacle and the boundary of the preset range, in other optimal embodiments, the distance between the obstacle and the center of the robot can be the distance between the obstacle and the boundary of the preset range, if the distance between the obstacle and the boundary of the preset range is 1, and when the distance threshold is 2, determining that the obstacle in the path segment can influence the movement of the robot, and setting a movement control label of the corresponding path segment to be 1; when the distance threshold is 0.5, the movement control flag of the corresponding path segment is set to 2.
Acquiring a mobile control tag of a path segment in real time, and controlling the robot to move according to a planned path according to a set speed of the robot when the mobile control tag is 2; when the control tag 1 is moved, the moving speed of the robot is adjusted to pass through the corresponding path segment. The set speed in this embodiment is the optimal speed for the robot to operate, and the adjustment of the moving speed of the robot includes:
marking the distance from the obstacle to the boundary of the preset range of the robot as JL;
the moving speed SD can be obtained by the formula sd=β1×1/JL, where β1 is a scaling factor greater than 0; as the distance JL is smaller, the moving speed of the robot is slower.
The moving speed is obtained in real time and is adjustable, so that the robot can avoid the obstacle to the greatest extent, and the moving safety of the robot is improved.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the method comprises the steps that a target position is sent to an embedded processor through a terminal control module, and the embedded processor obtains a planning path according to the target position and the current position of a robot;
the environment acquisition module acquires a real-time image of the advancing direction of the robot and identifies obstacles in the real-time image; setting an environment analysis tag according to the obstacle recognition result; when the environment analysis tag is a first type tag, performing obstacle warning through a terminal control module;
when the environment analysis tag is a second type tag, dividing the planned path into a plurality of path segments; respectively acquiring the vibration intensity and the sound intensity of the next path segment in the advancing direction through a vibration sensor and an ultrasonic sensor, and acquiring an environment evaluation coefficient through a formula;
when the environment evaluation coefficient is larger than the evaluation coefficient threshold, acquiring a visual field image through a high-definition camera of a robot working area; acquiring an obstacle of a visual field image through an image recognition technology, judging that the obstacle in a path segment can influence the movement of a robot when the distance between the obstacle and the boundary of a preset range is smaller than a distance threshold, setting a movement control tag of a corresponding path segment to be 1, otherwise, setting the movement control tag of the corresponding path segment to be 2;
acquiring a mobile control tag of a path segment in real time, and controlling the robot to move according to a planned path according to a set speed of the robot when the mobile control tag is 2; when the control tag 1 is moved, the moving speed of the robot is adjusted to pass through the corresponding path segment.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, 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 present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (4)
1. The intelligent obstacle avoidance system based on the embedded robot comprises an embedded processor and a data storage module, and is characterized in that the embedded processor is respectively in communication and/or electric connection with a terminal control module, an environment acquisition module and an execution control module; the environment acquisition module is in communication and/or electrical connection with the visual field acquisition module;
the terminal control module is used for sending the target position to the embedded processor; the visual field acquisition module is in communication and/or electrical connection with a high-definition camera of a robot working area;
when the embedded processor receives the target position, planning a path of the robot by combining the current position of the robot, and marking the path as a planned path;
the environment acquisition module acquires environment data through an environment sensor and analyzes the environment data to obtain an environment analysis tag; wherein the environmental analysis tag comprises a first type tag and a second type tag;
when the environment analysis tag is a first type tag, performing obstacle warning through a terminal control module; when the environment analysis tag is a second type tag, the visual field blind area analysis is carried out by combining the visual field acquisition module, and a mobile control tag is set;
controlling the robot to run according to the mobile control tag through the execution control module;
the obtaining of the environment analysis tag comprises the following steps:
acquiring a planned path, acquiring a real-time image of the advancing direction of the robot through a high-definition camera, and acquiring an obstacle in the real-time image through an image recognition technology;
when no obstacle exists in the real-time image or the obstacle is not in the preset range of the robot, setting the environment analysis tag to be 2, namely a second type tag;
when the obstacle of the real-time image is in the preset range of the robot, setting the environment analysis tag as 1, namely a first type tag;
when the environmental analysis tag is a second type tag, the view blind zone analysis includes:
dividing a planned path into a plurality of path segments;
respectively acquiring the vibration intensity and the sound intensity of the next path segment in the advancing direction through a vibration sensor and an ultrasonic sensor, and respectively marking the vibration intensity and the sound intensity as ZQ and SQ; obtaining an environment evaluation coefficient HPX by the formula hpx=α1×zq+α2×sq; wherein, alpha 1 and alpha 2 are both proportionality coefficients greater than 0;
when the environment evaluation coefficient HPX is larger than the evaluation coefficient threshold value, acquiring a visual field image through a high-definition camera of a robot working area; wherein the evaluation coefficient threshold is a real number greater than 0;
acquiring an obstacle of a visual field image through an image recognition technology, judging that the obstacle in a path segment can influence the movement of a robot when the distance between the obstacle and the boundary of a preset range is smaller than a distance threshold, setting a movement control tag of a corresponding path segment to be 1, otherwise, setting the movement control tag of the corresponding path segment to be 2; wherein the distance threshold is a real number greater than 0.
2. The intelligent obstacle avoidance system of claim 1 wherein the predetermined range is a safety space in which the robot moves and the shape of the predetermined range comprises a circle and a sphere.
3. The intelligent obstacle avoidance system of claim 1 wherein the execution control module controls robot movement, comprising:
acquiring a mobile control tag of a path segment in real time, and controlling the robot to move according to a planned path according to a set speed of the robot when the mobile control tag is 2;
when the control tag 1 is moved, the moving speed of the robot is adjusted to pass through the corresponding path segment.
4. An embedded robot-based intelligent obstacle avoidance method applied to the embedded robot-based intelligent obstacle avoidance system of any one of claims 1 to 3, characterized in that the robot-based intelligent obstacle avoidance method comprises the following steps:
the method comprises the steps that a target position is sent to an embedded processor through a terminal control module, and the embedded processor obtains a planning path according to the target position and the current position of a robot;
the environment acquisition module acquires a real-time image of the advancing direction of the robot and identifies obstacles in the real-time image; setting an environment analysis tag according to the obstacle recognition result; when the environment analysis tag is a first type tag, performing obstacle warning through a terminal control module;
when the environment analysis tag is a second type tag, dividing the planned path into a plurality of path segments; respectively acquiring the vibration intensity and the sound intensity of the next path segment in the advancing direction through a vibration sensor and an ultrasonic sensor, and respectively marking the vibration intensity and the sound intensity as ZQ and SQ; obtaining an environment evaluation coefficient HPX by the formula hpx=α1×zq+α2×sq; wherein, alpha 1 and alpha 2 are both proportionality coefficients greater than 0;
when the environment evaluation coefficient HPX is larger than the evaluation coefficient threshold value, acquiring a visual field image through a high-definition camera of a robot working area; acquiring an obstacle of a visual field image through an image recognition technology, judging that the obstacle in a path segment can influence the movement of a robot when the distance between the obstacle and the boundary of a preset range is smaller than a distance threshold, setting a movement control tag of a corresponding path segment to be 1, otherwise, setting the movement control tag of the corresponding path segment to be 2; wherein the evaluation coefficient threshold is a real number greater than 0;
acquiring a mobile control tag of a path segment in real time, and controlling the robot to move according to a planned path according to a set speed of the robot when the mobile control tag is 2; when the control tag 1 is moved, the moving speed of the robot is adjusted to pass through the corresponding path segment.
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| CN202110836637.4A CN113467468B (en) | 2021-07-23 | 2021-07-23 | Intelligent robot obstacle avoidance system and method based on embedded robot |
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