CN112894804A - Garbage collection platform control method and system based on Internet of things and readable storage medium - Google Patents
Garbage collection platform control method and system based on Internet of things and readable storage medium Download PDFInfo
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- CN112894804A CN112894804A CN202011593096.9A CN202011593096A CN112894804A CN 112894804 A CN112894804 A CN 112894804A CN 202011593096 A CN202011593096 A CN 202011593096A CN 112894804 A CN112894804 A CN 112894804A
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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
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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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- 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
- B25J9/1679—Programme controls characterised by the tasks executed
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Abstract
The invention relates to a garbage collection platform control method, a system and a readable storage medium based on the Internet of things, wherein the method comprises the following steps: collecting motion space information and establishing a three-dimensional space coordinate system; generating initial position information of the tail end of the mechanical arm; acquiring parameter information of a mechanical arm, establishing mechanical arm joint mark points, generating mark point information, acquiring position information of the garbage can, and generating mark point bending posture information; establishing a mechanical arm motion model, and comparing initial position information of the tail end of the mechanical arm with position information of the garbage can to obtain a first distance; if the first distance is larger than a preset first threshold value, the tail end of the mechanical arm moves in a stretching mode at a constant speed according to first speed information; setting a sampling interval, acquiring current position information of the tail end of the mechanical arm, and comparing the current position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a second distance; and if the second distance is smaller than a preset second threshold value, generating deceleration information, and gradually reducing the moving speed of the tail end of the mechanical arm from the first speed.
Description
Technical Field
The invention relates to a garbage collection platform control method, in particular to a garbage collection platform control method and system based on the Internet of things and a readable storage medium.
Background
The garbage is solid waste generated in daily life and production of human beings, has large discharge amount, complex and various components, pollution, resource and socialization, needs harmless, resource, reduction and socialization treatment, and can pollute the environment, influence the environmental sanitation, waste resources, destroy the safety of production and life and destroy the social harmony if the garbage cannot be properly treated. The garbage disposal is to rapidly remove the garbage, perform harmless treatment and finally reasonably utilize the garbage. The garbage disposal methods widely used today are sanitary landfills, high temperature composting and incineration. The purpose of garbage treatment is harmlessness, resource utilization and reduction. All in the garbage disposal process is in the garbage truck is unified to be poured into to rubbish in the garbage bin in each region through the garbage truck in, along with waste classification's popularization, traditional garbage collection mode is in order can't to satisfy waste classification's demand, consequently need an intelligent vehicle to unify the transportation to appointed place to rubbish to the garbage bin and handle, along with the rapid development of thing networking, in carrying out the garbage bin collection process, carry out intelligence through the arm cooperation and snatch the garbage bin, in order to realize the intellectuality of garbage collection platform.
In order to be able to carry out intelligent collection to the garbage bin and realize accurate control, a section needs to be developed and is controlled with its assorted system, this system gathers motion space information, establish three-dimensional space coordinate system, the arm moves along the movement track, arm terminal position is provided with the manipulator, compare terminal initial position information of arm and garbage bin position information, when the distance is great, carry out at the uniform velocity according to first speed and move to preset position, when the distance between arm terminal position and the garbage bin position was less than the second threshold value this moment, and the terminal manipulator moving speed of arm reduces gradually, prevent that the manipulator from moving the in-process and striking the garbage bin, but in carrying out control process, when how to realize accurate control, the intelligent collection that realizes rubbish all is the urgent problem that can not solve.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a garbage collection platform control method and system based on the Internet of things and a readable storage medium.
In order to achieve the purpose, the invention adopts the technical scheme that: a garbage collection platform control method based on the Internet of things comprises the following steps:
collecting motion space information and establishing a three-dimensional space coordinate system;
acquiring initial position coordinates of the tail end of the mechanical arm according to a three-dimensional space coordinate system, and generating initial position information of the tail end of the mechanical arm;
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
comparing the initial position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a first distance;
if the first distance is greater than a preset first threshold value, generating first speed information, and enabling the tail end of the mechanical arm to move telescopically at a constant speed according to the first speed information;
setting sampling interval, collecting current position information of the tail end of the mechanical arm,
comparing the current position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a second distance;
and if the second distance is smaller than a preset second threshold value, generating deceleration information, and gradually reducing the moving speed of the tail end of the mechanical arm from the first speed.
In a preferred embodiment of the present invention, the robot includes a first robot arm and a second robot arm, the first robot arm has at least one first mark point at a joint, the second robot arm has at least one second mark point, the first mark point has a first sensor disposed thereon, the second mark point has a second sensor disposed thereon, the first sensor is configured to monitor attitude information of the first robot arm, and the second sensor is configured to monitor attitude information of the second robot arm.
In a preferred embodiment of the present invention, the method further comprises:
acquiring initial position information of a first mechanical arm, generating a positive displacement signal,
generating a forward displacement of the first mechanical arm according to the forward displacement signal;
acquiring initial position information of the second mechanical arm, generating a negative displacement signal,
generating a negative displacement of the second mechanical arm according to the negative displacement signal;
carrying out absolute value difference calculation on the positive displacement of the first mechanical arm and the negative displacement of the second mechanical arm to obtain result information;
judging whether the result information is smaller than a preset threshold value,
if the clamping information is smaller than the first clamping information, clamping information of the first mechanical arm and the second mechanical arm is generated, and the garbage can is clamped and moved through the clamping information;
and if so, generating displacement compensation information, and compensating the positive displacement of the first mechanical arm or/and the negative displacement of the second mechanical arm through the displacement compensation information.
In a preferred embodiment of the present invention, the method further comprises:
acquiring the position information of the garbage can, extracting the position information of the edge line of the garbage can,
acquiring initial position information of a first mechanical arm and initial position information of a second mechanical arm,
comparing the initial position information of the first mechanical arm with the edge line position information of the garbage can to obtain a first deviation rate;
comparing the initial position information of the second mechanical arm with the edge line position information of the garbage can to obtain a second deviation rate;
if the first deviation rate is smaller than the second deviation rate, generating a priority sequence, wherein the motion priority of the first mechanical arm is larger than that of the second mechanical arm;
and if the first deviation rate is greater than the second deviation rate, generating a priority sequence, wherein the motion priority of the first mechanical arm is less than that of the second mechanical arm.
In a preferred embodiment of the present invention, the method further comprises: acquiring the position information of the garbage can, calculating an optimal path of the mechanical arm movement according to a map algorithm, and generating path information;
establishing a manipulator grabbing model, generating a grabbing mode and obtaining manipulator grabbing mode information;
identifying color information of the trash can, acquiring chroma information of the trash can, and generating trash classification information according to the chroma information of the trash can;
establishing a garbage can formation model according to the garbage classification information;
performing queue coding on the garbage cans according to the garbage can formation model to generate garbage can coding information;
generating a manipulator grabbing sequence according to the garbage can coding information,
and sequentially grabbing the garbage cans according to the grabbing mode information of the mechanical arms and the grabbing sequence of the mechanical arms.
In a preferred embodiment of the present invention, the method further comprises:
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
generating a motion mode according to the mechanical arm motion model to obtain mechanical arm motion amount information;
performing adaptive motion of the mechanical arm according to the motion amount information of the mechanical arm;
the adaptive motion of the mechanical arm comprises one of mechanical arm clamping, mechanical arm rotation, mechanical arm obstacle avoidance, mechanical arm uniform-speed movement, mechanical arm deceleration movement, mechanical arm acceleration movement, mechanical arm resetting motion, mechanical arm joint bending amount and mechanical arm joint bending direction.
The second aspect of the present invention also provides a garbage collection platform control system based on the internet of things, including: the garbage collection platform control method based on the Internet of things comprises a memory and a processor, wherein the memory comprises a garbage collection platform control method program based on the Internet of things, and when the garbage collection platform control method program based on the Internet of things is executed by the processor, the following steps are realized:
collecting motion space information and establishing a three-dimensional space coordinate system;
acquiring initial position coordinates of the tail end of the mechanical arm according to a three-dimensional space coordinate system, and generating initial position information of the tail end of the mechanical arm;
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
comparing the initial position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a first distance;
if the first distance is greater than a preset first threshold value, generating first speed information, and enabling the tail end of the mechanical arm to move telescopically at a constant speed according to the first speed information;
setting sampling interval, collecting current position information of the tail end of the mechanical arm,
comparing the current position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a second distance;
and if the second distance is smaller than a preset second threshold value, generating deceleration information, and gradually reducing the moving speed of the tail end of the mechanical arm from the first speed.
In a preferred embodiment of the present invention, the robot includes a first robot arm and a second robot arm, the first robot arm has at least one first mark point at a joint, the second robot arm has at least one second mark point, the first mark point has a first sensor disposed thereon, the second mark point has a second sensor disposed thereon, the first sensor is configured to monitor attitude information of the first robot arm, and the second sensor is configured to monitor attitude information of the second robot arm.
In a preferred embodiment of the present invention, the method further comprises:
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
generating a motion mode according to the mechanical arm motion model to obtain mechanical arm motion amount information;
performing adaptive motion of the mechanical arm according to the motion amount information of the mechanical arm;
the adaptive motion of the mechanical arm comprises one of mechanical arm clamping, mechanical arm rotation, mechanical arm obstacle avoidance, mechanical arm uniform-speed movement, mechanical arm deceleration movement, mechanical arm acceleration movement, mechanical arm resetting motion, mechanical arm joint bending amount and mechanical arm joint bending direction.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a garbage collection platform control method based on the internet of things, and when the program of the garbage collection platform control method based on the internet of things is executed by a processor, the steps of the garbage collection platform control method based on the internet of things described above are implemented.
The invention solves the defects in the background technology, and has the following beneficial effects:
(1) the method comprises the steps of collecting motion space information, establishing a three-dimensional space coordinate system, obtaining initial position coordinates of two mechanical arms according to the three-dimensional space coordinate system, establishing a matching rule of the two mechanical arms according to the motion information, automatically generating a motion track and a mutual matching relation between the two mechanical arms according to a matching model, and enabling the mechanical arms to move along the motion track with high precision.
(2) In carrying out the centre gripping in-process to the garbage bin through the robotic arm, through first arm and second arm relative motion, first arm carries out positive displacement, the second arm carries out negative displacement, in order to realize the centre gripping, through judging the difference between the absolute value of first arm and second arm positive displacement volume and negative displacement volume, carry out the centre gripping with the garbage bin of cooperation different width and remove, when the deviation appears great, compensate the displacement volume of first arm or second arm through compensation information, guarantee when not extrudeing the garbage bin, can the centre gripping garbage bin remove.
(3) The garbage can edge position information is acquired, the distances between the garbage can and the first mechanical arm and the distance between the garbage can and the second mechanical arm are respectively judged, the mechanical arms which are closer to each other are firstly moved to the positions near the garbage can, the priority motion sequence of the mechanical arms is generated, and the mechanical arms are accurately and flexibly controlled.
(4) The mark points are arranged at the joints of the mechanical arm, the gesture information of the mechanical arm is monitored at the mark points through the sensor, the gesture information monitored at the mark points is closer to the actual motion information of the mechanical arm, the monitoring precision is higher, and the planning of the motion trail of the mechanical arm is facilitated.
(5) The mechanical arm tail end position is provided with the manipulator, compares terminal initial position information of mechanical arm with garbage bin positional information, when the distance is great, carries out at the uniform velocity according to first speed and moves to preset position, and when the distance between terminal position of mechanical arm and the garbage bin position was less than the second threshold value this moment, and the manipulator moving speed at the mechanical arm end reduced gradually, prevented that the manipulator from removing the in-process striking garbage bin.
(6) The garbage bin of different colours is used for collecting different types of rubbish, realizes the categorised collection of rubbish, establishes the formation model to the garbage bin of different colours, carries out automatic formation to the garbage bin to serial number the garbage bin, carrying out the garbage collection in-process, according to the garbage bin serial number that the collection order corresponds, carry out garbage collection according to predetermined order, realize the classification of rubbish.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow chart of a garbage collection platform control method based on the Internet of things according to the invention;
FIG. 2 shows a flowchart of a robot arm displacement compensation method;
FIG. 3 illustrates a flow chart of a robot arm movement prioritization method;
FIG. 4 shows a flowchart of a trash can grabbing method;
FIG. 5 shows a block diagram of a garbage collection platform control system based on the Internet of things;
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a flowchart of a garbage collection platform control method based on the internet of things according to the present invention.
As shown in fig. 1, a first aspect of the present invention provides a garbage collection platform control method based on the internet of things, including:
s102, collecting motion space information and establishing a three-dimensional space coordinate system;
s104, acquiring initial position coordinates of the tail end of the mechanical arm according to a three-dimensional space coordinate system, and generating initial position information of the tail end of the mechanical arm;
s106, acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
s108, collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
s110, establishing a mechanical arm motion model according to the mark point bending posture information,
s112, comparing the initial position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a first distance, if the first distance is greater than a preset first threshold value, generating first speed information, and enabling the tail end of the mechanical arm to move telescopically at a constant speed according to the first speed information;
s114, setting a sampling interval, collecting the current position information of the tail end of the mechanical arm,
and S116, comparing the current position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a second distance, if the second distance is smaller than a preset second threshold value, generating deceleration information, and gradually reducing the moving speed of the tail end of the mechanical arm from the first speed.
It should be noted that, the mechanical arm is arranged at the tail end of the mechanical arm, the initial position information of the tail end of the mechanical arm is compared with the position information of the garbage can, when the distance is large, the mechanical arm moves to a preset position at a constant speed according to a first speed, and when the distance between the tail end position of the mechanical arm and the position of the garbage can is smaller than a second threshold value, the moving speed of the mechanical arm at the tail end of the mechanical arm is gradually reduced, so that the garbage can is prevented from being impacted by the mechanical arm.
The method comprises the steps of collecting motion space information, establishing a three-dimensional space coordinate system, obtaining initial position coordinates of two mechanical arms according to the three-dimensional space coordinate system, establishing a matching rule of the two mechanical arms according to the motion information, automatically generating a motion track and a mutual matching relation between the two mechanical arms according to a matching model, and enabling the mechanical arms to move along the motion track with high precision. The method for generating the motion trail according to the matching model comprises one of a visual graph method, a grid decomposition method, a random road sign algorithm and a rapid random tree expansion method, wherein the visual graph method firstly establishes a visual graph in an operation space, the path planning is to search the visual graph to obtain a path which does not pass through the barrier from a starting point to an end point, and the grid decomposition method decomposes the working space of the robot into a plurality of grids. The grids form a connected graph, a path from a starting grid to a target grid is searched on the connected graph, a random road sign algorithm is a quick and effective path planning algorithm, generally, random sampling is carried out in a configuration space, preprocessing is carried out, a group of random road sign graphs are obtained to represent a free space of the robot system operation, and then a feasible path is searched for the robot system in the graph. The fast random expanding tree method is one incremental forward search algorithm, and each planning process includes taking one initial point in state space as root node, and generating one random expanding tree in random sampling mode with gradually increased leaf nodes. When the leaf nodes of the random tree contain the target point or a point in the target area, an reachable path from the initial point to the target point is found in the random tree, which is composed of leaf nodes.
According to an embodiment of the present invention, the robot arm includes a first robot arm and a second robot arm, at least one first mark point is disposed at a joint of the first robot arm, at least one second mark point is disposed on the second robot arm, a first sensor is disposed on the first mark point, a second sensor is disposed on the second mark point, the first sensor is configured to monitor posture information of the first robot arm, and the second sensor is configured to monitor posture information of the second robot arm.
It should be noted that, by setting the mark points at the joints of the mechanical arm, the gesture information of the mechanical arm is monitored at the mark points through the sensor, the gesture information monitored at the mark points is closer to the actual motion information of the mechanical arm, the monitoring precision is higher, and the planning of the motion track of the mechanical arm is facilitated.
As shown in fig. 2, the present invention discloses a flow chart of a mechanical arm displacement compensation method;
according to the embodiment of the invention, the method further comprises the following steps:
s202, acquiring initial position information of the first mechanical arm, generating a forward displacement signal, and generating a forward displacement of the first mechanical arm according to the forward displacement signal;
s204, acquiring initial position information of the second mechanical arm, generating a negative displacement signal, and generating a negative displacement of the second mechanical arm according to the negative displacement signal;
s206, carrying out absolute value difference calculation on the positive displacement of the first mechanical arm and the negative displacement of the second mechanical arm to obtain result information;
s208, judging whether the result information is smaller than a preset threshold value,
s210, if the clamping information is smaller than the clamping information, clamping information of the first mechanical arm and the second mechanical arm is generated, and the garbage can is clamped and moved through the clamping information;
and S212, if the positive displacement is larger than the negative displacement, generating displacement compensation information, and compensating the positive displacement of the first mechanical arm or/and the negative displacement of the second mechanical arm through the displacement compensation information.
It should be noted that, in the process of clamping the trash can through the mechanical arm, the first mechanical arm and the second mechanical arm move relatively, the first mechanical arm carries out positive displacement, the second mechanical arm carries out negative displacement, so as to realize clamping, the trash can be clamped and moved by matching with trash cans of different widths by judging the difference between the absolute values of the positive displacement and the negative displacement of the first mechanical arm and the second mechanical arm, when the deviation is large, the displacement of the first mechanical arm or the second mechanical arm is compensated through compensation information, and the trash can is guaranteed to be clamped and moved while the trash can is not squeezed.
As shown in FIG. 3, the present invention discloses a flow chart of a robot arm movement prioritization method;
according to the embodiment of the invention, the method further comprises the following steps:
s302, obtaining the position information of the garbage can, extracting the position information of the edge line of the garbage can,
s304, acquiring the initial position information of the first mechanical arm and the initial position information of the second mechanical arm,
s306, comparing the initial position information of the first mechanical arm with the edge line position information of the garbage can to obtain a first deviation rate;
s308, comparing the initial position information of the second mechanical arm with the position information of the edge line of the garbage can to obtain a second deviation rate;
s310, if the first deviation rate is smaller than the second deviation rate, generating a priority sequence, wherein the motion priority of the first mechanical arm is larger than that of the second mechanical arm;
s312, if the first deviation ratio is greater than the second deviation ratio, a priority ranking is generated, and the priority of the first robot arm motion is less than the priority of the second robot arm motion.
It should be noted that, the edge position information of the trash can is acquired, the distances between the trash can and the first mechanical arm and the distance between the trash can and the second mechanical arm are respectively judged, the mechanical arms with the shorter distances move to the positions near the trash can at first, the priority motion sequence of the mechanical arms is generated, and the mechanical arms are controlled accurately and flexibly.
As shown in FIG. 4, the present invention discloses a flow chart of a trash can grabbing method;
according to the embodiment of the invention, the method further comprises the following steps:
s402, acquiring position information of the garbage can, calculating an optimal path of the mechanical arm movement according to a map algorithm, and generating path information;
s404, establishing a manipulator grabbing model, generating a grabbing mode and obtaining manipulator grabbing mode information;
s406, identifying the color information of the trash can, acquiring the chroma information of the trash can, and generating trash classification information according to the chroma information of the trash can;
s408, establishing a garbage can formation model according to the garbage classification information;
s410, performing queue coding on the garbage can according to the garbage can formation model to generate garbage can coding information;
s412, according to the garbage can coding information, generating a manipulator grabbing sequence,
and S414, sequentially grabbing the garbage cans according to the manipulator grabbing mode information and the manipulator grabbing sequence.
It should be noted that the garbage cans with different colors are used for collecting different types of garbage to achieve classified collection of the garbage, a formation model is established for the garbage cans with different colors, the garbage cans are automatically formed into a formation, the garbage cans are numbered, and in the garbage collection process, the garbage collection is performed according to the garbage can numbers corresponding to the collection sequence and the preset sequence to achieve classified treatment of the garbage.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
generating a motion mode according to the mechanical arm motion model to obtain mechanical arm motion amount information;
performing adaptive motion of the mechanical arm according to the motion amount information of the mechanical arm;
the adaptive motion of the mechanical arm comprises one of mechanical arm clamping, mechanical arm rotation, mechanical arm obstacle avoidance, mechanical arm uniform-speed movement, mechanical arm deceleration movement, mechanical arm acceleration movement, mechanical arm resetting motion, mechanical arm joint bending amount and mechanical arm joint bending direction.
As shown in fig. 5, the invention discloses a garbage collection platform control system block diagram based on the internet of things;
the second aspect of the present invention also provides a garbage collection platform control system based on the internet of things, including: the garbage collection platform control method based on the Internet of things comprises a memory and a processor, wherein the memory comprises a garbage collection platform control method program based on the Internet of things, and when the garbage collection platform control method program based on the Internet of things is executed by the processor, the following steps are realized:
collecting motion space information and establishing a three-dimensional space coordinate system;
acquiring initial position coordinates of the tail end of the mechanical arm according to a three-dimensional space coordinate system, and generating initial position information of the tail end of the mechanical arm;
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
comparing the initial position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a first distance;
if the first distance is greater than a preset first threshold value, generating first speed information, and enabling the tail end of the mechanical arm to move telescopically at a constant speed according to the first speed information;
setting sampling interval, collecting current position information of the tail end of the mechanical arm,
comparing the current position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a second distance;
and if the second distance is smaller than a preset second threshold value, generating deceleration information, and gradually reducing the moving speed of the tail end of the mechanical arm from the first speed.
It should be noted that, the mechanical arm is arranged at the tail end of the mechanical arm, the initial position information of the tail end of the mechanical arm is compared with the position information of the garbage can, when the distance is large, the mechanical arm moves to a preset position at a constant speed according to a first speed, and when the distance between the tail end position of the mechanical arm and the position of the garbage can is smaller than a second threshold value, the moving speed of the mechanical arm at the tail end of the mechanical arm is gradually reduced, so that the garbage can is prevented from being impacted by the mechanical arm.
The method comprises the steps of collecting motion space information, establishing a three-dimensional space coordinate system, obtaining initial position coordinates of two mechanical arms according to the three-dimensional space coordinate system, establishing a matching rule of the two mechanical arms according to the motion information, automatically generating a motion track and a mutual matching relation between the two mechanical arms according to a matching model, and enabling the mechanical arms to move along the motion track with high precision. The method for generating the motion trail according to the matching model comprises one of a visual graph method, a grid decomposition method, a random road sign algorithm and a rapid random tree expansion method, wherein the visual graph method firstly establishes a visual graph in an operation space, the path planning is to search the visual graph to obtain a path which does not pass through the barrier from a starting point to an end point, and the grid decomposition method decomposes the working space of the robot into a plurality of grids. The grids form a connected graph, a path from a starting grid to a target grid is searched on the connected graph, a random road sign algorithm is a quick and effective path planning algorithm, generally, random sampling is carried out in a configuration space, preprocessing is carried out, a group of random road sign graphs are obtained to represent a free space of the robot system operation, and then a feasible path is searched for the robot system in the graph. The fast random expanding tree method is one incremental forward search algorithm, and each planning process includes taking one initial point in state space as root node, and generating one random expanding tree in random sampling mode with gradually increased leaf nodes. When the leaf nodes of the random tree contain the target point or a point in the target area, an reachable path from the initial point to the target point is found in the random tree, which is composed of leaf nodes.
According to an embodiment of the present invention, the robot arm includes a first robot arm and a second robot arm, at least one first mark point is disposed at a joint of the first robot arm, at least one second mark point is disposed on the second robot arm, a first sensor is disposed on the first mark point, a second sensor is disposed on the second mark point, the first sensor is configured to monitor posture information of the first robot arm, and the second sensor is configured to monitor posture information of the second robot arm.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
generating a motion mode according to the mechanical arm motion model to obtain mechanical arm motion amount information;
performing adaptive motion of the mechanical arm according to the motion amount information of the mechanical arm;
the adaptive motion of the mechanical arm comprises one of mechanical arm clamping, mechanical arm rotation, mechanical arm obstacle avoidance, mechanical arm uniform-speed movement, mechanical arm deceleration movement, mechanical arm acceleration movement, mechanical arm resetting motion, mechanical arm joint bending amount and mechanical arm joint bending direction.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring initial position information of a first mechanical arm, generating a positive displacement signal,
generating a forward displacement of the first mechanical arm according to the forward displacement signal;
acquiring initial position information of the second mechanical arm, generating a negative displacement signal,
generating a negative displacement of the second mechanical arm according to the negative displacement signal;
carrying out absolute value difference calculation on the positive displacement of the first mechanical arm and the negative displacement of the second mechanical arm to obtain result information;
judging whether the result information is smaller than a preset threshold value,
if the clamping information is smaller than the first clamping information, clamping information of the first mechanical arm and the second mechanical arm is generated, and the garbage can is clamped and moved through the clamping information;
and if so, generating displacement compensation information, and compensating the positive displacement of the first mechanical arm or/and the negative displacement of the second mechanical arm through the displacement compensation information.
It should be noted that, in the process of clamping the trash can through the mechanical arm, the first mechanical arm and the second mechanical arm move relatively, the first mechanical arm carries out positive displacement, the second mechanical arm carries out negative displacement, so as to realize clamping, the trash can be clamped and moved by matching with trash cans of different widths by judging the difference between the absolute values of the positive displacement and the negative displacement of the first mechanical arm and the second mechanical arm, when the deviation is large, the displacement of the first mechanical arm or the second mechanical arm is compensated through compensation information, and the trash can is guaranteed to be clamped and moved while the trash can is not squeezed.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring the position information of the garbage can, extracting the position information of the edge line of the garbage can,
acquiring initial position information of a first mechanical arm and initial position information of a second mechanical arm,
comparing the initial position information of the first mechanical arm with the edge line position information of the garbage can to obtain a first deviation rate;
comparing the initial position information of the second mechanical arm with the edge line position information of the garbage can to obtain a second deviation rate;
if the first deviation rate is smaller than the second deviation rate, generating a priority sequence, wherein the motion priority of the first mechanical arm is larger than that of the second mechanical arm;
and if the first deviation rate is greater than the second deviation rate, generating a priority sequence, wherein the motion priority of the first mechanical arm is less than that of the second mechanical arm.
It should be noted that, the edge position information of the trash can is acquired, the distances between the trash can and the first mechanical arm and the distance between the trash can and the second mechanical arm are respectively judged, the mechanical arms with the shorter distances move to the positions near the trash can at first, the priority motion sequence of the mechanical arms is generated, and the mechanical arms are controlled accurately and flexibly.
According to the embodiment of the invention, the position information of the garbage can is obtained, and the optimal path of the mechanical arm movement is calculated according to a map algorithm to generate the path information;
establishing a manipulator grabbing model, generating a grabbing mode and obtaining manipulator grabbing mode information;
identifying color information of the trash can, acquiring chroma information of the trash can, and generating trash classification information according to the chroma information of the trash can;
establishing a garbage can formation model according to the garbage classification information;
performing queue coding on the garbage cans according to the garbage can formation model to generate garbage can coding information;
generating a manipulator grabbing sequence according to the garbage can coding information,
and sequentially grabbing the garbage cans according to the grabbing mode information of the mechanical arms and the grabbing sequence of the mechanical arms.
It should be noted that the garbage cans with different colors are used for collecting different types of garbage to achieve classified collection of the garbage, a formation model is established for the garbage cans with different colors, the garbage cans are automatically formed into a formation, the garbage cans are numbered, and in the garbage collection process, the garbage collection is performed according to the garbage can numbers corresponding to the collection sequence and the preset sequence to achieve classified treatment of the garbage.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a garbage collection platform control method based on the internet of things, and when the program of the garbage collection platform control method based on the internet of things is executed by a processor, the steps of the garbage collection platform control method based on the internet of things described above are implemented.
The method comprises the steps of collecting motion space information, establishing a three-dimensional space coordinate system, obtaining initial position coordinates of two mechanical arms according to the three-dimensional space coordinate system, establishing a matching rule of the two mechanical arms according to the motion information, automatically generating a motion track and a mutual matching relation between the two mechanical arms according to a matching model, and enabling the mechanical arms to move along the motion track with high precision.
In carrying out the centre gripping in-process to the garbage bin through the robotic arm, through first arm and second arm relative motion, first arm carries out positive displacement, the second arm carries out negative displacement, in order to realize the centre gripping, through judging the difference between the absolute value of first arm and second arm positive displacement volume and negative displacement volume, carry out the centre gripping with the garbage bin of cooperation different width and remove, when the deviation appears great, compensate the displacement volume of first arm or second arm through compensation information, guarantee when not extrudeing the garbage bin, can the centre gripping garbage bin remove.
The garbage can edge position information is acquired, the distances between the garbage can and the first mechanical arm and the distance between the garbage can and the second mechanical arm are respectively judged, the mechanical arms which are closer to each other are firstly moved to the positions near the garbage can, the priority motion sequence of the mechanical arms is generated, and the mechanical arms are accurately and flexibly controlled.
The mark points are arranged at the joints of the mechanical arm, the gesture information of the mechanical arm is monitored at the mark points through the sensor, the gesture information monitored at the mark points is closer to the actual motion information of the mechanical arm, the monitoring precision is higher, and the planning of the motion trail of the mechanical arm is facilitated.
The mechanical arm tail end position is provided with the manipulator, compares terminal initial position information of mechanical arm with garbage bin positional information, when the distance is great, carries out at the uniform velocity according to first speed and moves to preset position, and when the distance between terminal position of mechanical arm and the garbage bin position was less than the second threshold value this moment, and the manipulator moving speed at the mechanical arm end reduced gradually, prevented that the manipulator from removing the in-process striking garbage bin.
The garbage bin of different colours is used for collecting different types of rubbish, realizes the categorised collection of rubbish, establishes the formation model to the garbage bin of different colours, carries out automatic formation to the garbage bin to serial number the garbage bin, carrying out the garbage collection in-process, according to the garbage bin serial number that the collection order corresponds, carry out garbage collection according to predetermined order, realize the classification of rubbish.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of a unit is only one logical function division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, 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.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A garbage collection platform control method based on the Internet of things is characterized by comprising the following steps:
collecting motion space information and establishing a three-dimensional space coordinate system;
acquiring initial position coordinates of the tail end of the mechanical arm according to a three-dimensional space coordinate system, and generating initial position information of the tail end of the mechanical arm;
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
comparing the initial position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a first distance;
if the first distance is greater than a preset first threshold value, generating first speed information, and enabling the tail end of the mechanical arm to move telescopically at a constant speed according to the first speed information;
setting sampling interval, collecting current position information of the tail end of the mechanical arm,
comparing the current position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a second distance;
and if the second distance is smaller than a preset second threshold value, generating deceleration information, and gradually reducing the moving speed of the tail end of the mechanical arm from the first speed.
2. The internet of things-based garbage collection platform control method according to claim 1, wherein the mechanical arm comprises a first mechanical arm and a second mechanical arm, at least one first mark point is arranged at a joint of the first mechanical arm, at least one second mark point is arranged on the second mechanical arm, a first sensor is arranged on the first mark point, a second sensor is arranged on the second mark point, the first sensor is used for monitoring posture information of the first mechanical arm, and the second sensor is used for monitoring posture information of the second mechanical arm.
3. The internet of things-based garbage collection platform control method according to claim 2, further comprising:
acquiring initial position information of a first mechanical arm, generating a positive displacement signal,
generating a forward displacement of the first mechanical arm according to the forward displacement signal;
acquiring initial position information of the second mechanical arm, generating a negative displacement signal,
generating a negative displacement of the second mechanical arm according to the negative displacement signal;
carrying out absolute value difference calculation on the positive displacement of the first mechanical arm and the negative displacement of the second mechanical arm to obtain result information;
judging whether the result information is smaller than a preset threshold value,
if the clamping information is smaller than the first clamping information, clamping information of the first mechanical arm and the second mechanical arm is generated, and the garbage can is clamped and moved through the clamping information;
and if so, generating displacement compensation information, and compensating the positive displacement of the first mechanical arm or/and the negative displacement of the second mechanical arm through the displacement compensation information.
4. The internet of things-based garbage collection platform control method according to claim 3, further comprising:
acquiring the position information of the garbage can, extracting the position information of the edge line of the garbage can,
acquiring initial position information of a first mechanical arm and initial position information of a second mechanical arm,
comparing the initial position information of the first mechanical arm with the edge line position information of the garbage can to obtain a first deviation rate;
comparing the initial position information of the second mechanical arm with the edge line position information of the garbage can to obtain a second deviation rate;
if the first deviation rate is smaller than the second deviation rate, generating a priority sequence, wherein the motion priority of the first mechanical arm is larger than that of the second mechanical arm;
and if the first deviation rate is greater than the second deviation rate, generating a priority sequence, wherein the motion priority of the first mechanical arm is less than that of the second mechanical arm.
5. The internet of things-based garbage collection platform control method according to claim 1, further comprising:
acquiring the position information of the garbage can, calculating an optimal path of the mechanical arm movement according to a map algorithm, and generating path information;
establishing a manipulator grabbing model, generating a grabbing mode and obtaining manipulator grabbing mode information;
identifying color information of the trash can, acquiring chroma information of the trash can, and generating trash classification information according to the chroma information of the trash can;
establishing a garbage can formation model according to the garbage classification information;
performing queue coding on the garbage cans according to the garbage can formation model to generate garbage can coding information;
generating a manipulator grabbing sequence according to the garbage can coding information,
and sequentially grabbing the garbage cans according to the grabbing mode information of the mechanical arms and the grabbing sequence of the mechanical arms.
6. The internet of things-based garbage collection platform control method according to claim 1, further comprising:
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
generating a motion mode according to the mechanical arm motion model to obtain mechanical arm motion amount information;
performing adaptive motion of the mechanical arm according to the motion amount information of the mechanical arm;
the adaptive motion of the mechanical arm comprises one of mechanical arm clamping, mechanical arm rotation, mechanical arm obstacle avoidance, mechanical arm uniform-speed movement, mechanical arm deceleration movement, mechanical arm acceleration movement, mechanical arm resetting motion, mechanical arm joint bending amount and mechanical arm joint bending direction.
7. A garbage collection platform control system based on the Internet of things is characterized by comprising: the garbage collection platform control method based on the Internet of things comprises a memory and a processor, wherein the memory comprises a garbage collection platform control method program based on the Internet of things, and when the garbage collection platform control method program based on the Internet of things is executed by the processor, the following steps are realized: collecting motion space information and establishing a three-dimensional space coordinate system;
acquiring initial position coordinates of the tail end of the mechanical arm according to a three-dimensional space coordinate system, and generating initial position information of the tail end of the mechanical arm;
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
comparing the initial position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a first distance;
if the first distance is greater than a preset first threshold value, generating first speed information, and enabling the tail end of the mechanical arm to move telescopically at a constant speed according to the first speed information;
setting sampling interval, collecting current position information of the tail end of the mechanical arm,
comparing the current position information of the tail end of the mechanical arm with the position information of the garbage can to obtain a second distance;
and if the second distance is smaller than a preset second threshold value, generating deceleration information, and gradually reducing the moving speed of the tail end of the mechanical arm from the first speed.
8. The internet of things-based garbage collection platform control system according to claim 7, wherein the mechanical arm comprises a first mechanical arm and a second mechanical arm, at least one first mark point is arranged at a joint of the first mechanical arm, at least one second mark point is arranged on the second mechanical arm, a first sensor is arranged on the first mark point, a second sensor is arranged on the second mark point, the first sensor is used for monitoring posture information of the first mechanical arm, and the second sensor is used for monitoring posture information of the second mechanical arm.
9. The internet of things based garbage collection platform control system according to claim 7, further comprising:
acquiring mechanical arm parameter information, establishing mechanical arm joint mark points, and generating mark point information;
collecting the position information of the garbage can, and generating the bending posture information of the mark point according to the position information of the garbage can;
according to the information of the bending posture of the mark point, a mechanical arm motion model is established,
generating a motion mode according to the mechanical arm motion model to obtain mechanical arm motion amount information;
performing adaptive motion of the mechanical arm according to the motion amount information of the mechanical arm;
the adaptive motion of the mechanical arm comprises one of mechanical arm clamping, mechanical arm rotation, mechanical arm obstacle avoidance, mechanical arm uniform-speed movement, mechanical arm deceleration movement, mechanical arm acceleration movement, mechanical arm resetting motion, mechanical arm joint bending amount and mechanical arm joint bending direction.
10. A computer-readable storage medium, wherein the computer-readable storage medium includes a program of a garbage collection platform control method based on internet of things, and when the program of the garbage collection platform control method based on internet of things is executed by a processor, the steps of the garbage collection platform control method based on internet of things according to any one of claims 1 to 6 are implemented.
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| CN202011593096.9A CN112894804A (en) | 2020-12-29 | 2020-12-29 | Garbage collection platform control method and system based on Internet of things and readable storage medium |
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| CN202011593096.9A CN112894804A (en) | 2020-12-29 | 2020-12-29 | Garbage collection platform control method and system based on Internet of things and readable storage medium |
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Application publication date: 20210604 |