CN107336234A - A kind of reaction type self study industrial robot and method of work - Google Patents
A kind of reaction type self study industrial robot and method of work Download PDFInfo
- Publication number
- CN107336234A CN107336234A CN201710441678.7A CN201710441678A CN107336234A CN 107336234 A CN107336234 A CN 107336234A CN 201710441678 A CN201710441678 A CN 201710441678A CN 107336234 A CN107336234 A CN 107336234A
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- China
- Prior art keywords
- robot
- self study
- pressure sensor
- neutral net
- end effector
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Classifications
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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
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
Abstract
The invention discloses a kind of reaction type self study industrial robot and method of work, including robot body, joint of robot, end effector of robot, pressure sensor, pedestal, vision sensor, support and robot base, the end of the robot body is provided with end effector of robot, pressure sensor is installed on end effector of robot, vision sensor is installed with the top of the support, by building neutral net, collection image and processing, control machine people performs relevant action.The reaction type self study industrial robot and method of work of the present invention, judge that whether end runs succeeded by pressure sensor data and provide learning outcome foundation for self learning neural networkses, learning track is provided for the self study of industrial robot, according to processing result image, in whole process, the trick relation of camera and robot need not be demarcated, can adaptive unknown object inter-related task, application greatly increases.
Description
Technical field
The present invention relates to industrial robot field, specially a kind of reaction type self study industrial robot and method of work.
Background technology
Conventional industrial robot realizes repeated work mainly by the method for pre-programmed come the motion of control machine people.Such as
Fruit does not have predefined and programming inter-related task, and robot will be unable to make corresponding judgement and work.On this basis, mark is passed through
Determine robotic vision sensor（Eye）And the end effector of robot（Hand）Between relation, i.e. trick relation, then tie
The method for closing image procossing realizes that the automatic hand-eye machine people to work automatically is used widely and developed.This robot is applicable
The work such as gripping, carrying in known object form, it can not automatically learn and unknown object is operated.
The content of the invention
It is an object of the invention to provide a kind of reaction type self study industrial robot and method of work, and having can be automatic
The advantages of learning and being operated to unknown object, to solve the problems mentioned in the above background technology.
To achieve the above object, the present invention provides following technical scheme：A kind of reaction type self study industrial robot, including
Robot body, joint of robot, end effector of robot, pressure sensor, pedestal, vision sensor, support and machine
People's base, robot base are fixedly connected on pedestal, and robot base connects robot body, machine by joint of robot
The end of human agent is provided with end effector of robot, is provided with pressure sensor on end effector of robot, on pedestal
Support is also fixedly connected with, vision sensor is installed with the top of support.
Preferably, end performs device is installed on end effector of robot.
A kind of method of work of reaction type self study industrial robot, workflow include：
Step 1：Neutral net is built, is robot posture information, the centre coordinate of object, pressure sensor data on image
As neutral net input node, whether run succeeded and be used as neutral net output node, suitable hidden node number；
Step 2：Image is gathered by vision sensor；
Step 3：Image is handled again, segmenting edge and target, obtain target dependent coordinate information such as centre coordinate；
Step 4：Then control machine people performs relevant action, if robot execution acts successfully, its pressure sensor will pass
Corresponding data is sent otherwise, to perform failure to host computer；
Step 5：The information such as posture information now, processing result image, implementing result are sent to neutral net input and output,
Meanwhile execution result back and coordinate information are to robot；
Step 6：Robot suitably adjusts pose according to the execution information of feedback；
Step 7：Repeat step 5 and 6, until end runs succeeded；
Step 8：Train neutral net；
Step 9：Step 2 is performed a plurality of times to step 8, until neutral net restrains, object space when obtaining pose and handling successfully,
The dependency relation of pressure sensor state etc., robot self study are completed；
Step 10：After completing self study, related work is performed according to neutral net result.
Compared with prior art, the beneficial effects of the invention are as follows：The reaction type self study industrial robot and work of the present invention
Make method, by pressure sensor data judge end whether run succeeded for self learning neural networkses provide learning outcome according to
According to, learning track is provided for the self study of industrial robot, it is automatic to adjust according to processing result image using reaction type mode
Whole robot pose, solves the problems, such as the Pose Control in automation study.In whole process, it is not necessary to demarcate camera and
The trick relation of robot, dependency relation therein is as described by the hidden layer of neutral net.Can adaptive unknown object phase
Pass task, application greatly increase.
Brief description of the drawings
Fig. 1 is the overall structure diagram of the present invention；
Fig. 2 is the workflow diagram of the present invention.
In figure：1 robot body, 2 joint of robot, 3 end effector of robot, 4 pressure sensors, 5 pedestals, 6 regard
Feel sensor, 7 supports, 8 robot bases.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, close Chu, complete is carried out to the technical scheme in the embodiment of the present invention
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of protection of the invention.
Refering to Fig. 1-2, the present invention provides a kind of technical scheme：A kind of reaction type self study industrial robot, including machine
Human agent 1, joint of robot 2, end effector of robot 3, pressure sensor 4, pedestal 5, vision sensor 6, support 7 and machine
Device people base 8, robot base 8 is fixedly connected on pedestal 5, and robot base 8 connects robot master by joint of robot 2
Body 1, the sitting posture of control machine people, the end of robot body 1 are provided with end effector of robot 3, and robot end performs
Pressure sensor 4 is installed, pressure sensor 4 is for detecting whether crawl known object, end effector of robot 3 on device 3
On performs device such as handgrip in end is installed, support 7 is also fixedly connected with pedestal 5, the top of support 7 is installed with vision
Sensor 6, vision sensor 6 can be observed within the working range of end effector of robot 3.
A kind of method of work of reaction type self study industrial robot, workflow include：
Step 1：Neutral net is built, is robot posture information, the centre coordinate of object, pressure sensor 4 count on image
According to as neutral net input node, whether run succeeded and be used as neutral net output node, suitable hidden node number；
Step 2：Image is gathered by vision sensor 6；
Step 3：Image is handled again, segmenting edge and target, obtain target dependent coordinate information such as centre coordinate；
Step 4：Then control machine people performs relevant action, if robot execution acts successfully, its pressure sensor 4 will pass
Corresponding data is sent otherwise, to perform failure to host computer；
Step 5：The information such as posture information now, processing result image, implementing result are sent to neutral net input and output,
Meanwhile execution result back and coordinate information are to robot；
Step 6：Robot suitably adjusts pose according to the execution information of feedback；
Step 7：Repeat step 5 and 6, until end runs succeeded；
Step 8：Train neutral net；
Step 9：Step 2 is performed a plurality of times to step 8, until neutral net restrains, object space when obtaining pose and handling successfully,
The dependency relation of the state of pressure sensor 4 etc., robot self study are completed；
Step 10：After completing self study, related work is performed according to neutral net result.
Robot can judge unknown object shape and position by autonomous learning, and as requested, it is unknown to this
Object such as is gripped, carried at the operation, and this industrial robot need not demarcate the trick relation of camera and robot,
This industrial robot uses neural net method, can automatically learn and perform inter-related task, industrial robot uses reaction type
Pose Control, it is not necessary to manual intervention, automatic running.
To sum up：The reaction type self study industrial robot and method of work of the present invention, is judged by the data of pressure sensor 4
Whether end runs succeeded provides learning outcome foundation for self learning neural networkses, is provided for the self study of industrial robot
Learning track, using reaction type mode, according to processing result image, adjust automatically machine people's pose, solves automation study
In Pose Control problem.In whole process, it is not necessary to demarcate the trick relation of camera and robot, related pass therein
System is as described by the hidden layer of neutral net.Can adaptive unknown object inter-related task, application greatly increases.
More than, it is only the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, and it is any
Those familiar with the art the invention discloses technical scope in, technique according to the invention scheme and its invention
Design is subject to equivalent substitution or change, should all be included within the scope of the present invention.
Claims (3)
1. a kind of reaction type self study industrial robot, it is characterised in that including robot body（1）, joint of robot（2）、
End effector of robot（3）, pressure sensor（4）, pedestal（5）, vision sensor（6）, support（7）And robot base
（8）, robot base（8）It is fixedly connected on pedestal（5）On, robot base（8）Pass through joint of robot（2）Connect robot
Main body（1）, robot body（1）End be provided with end effector of robot（3）, end effector of robot（3）Upper peace
Equipped with pressure sensor（4）, pedestal（5）On be also fixedly connected with support（7）, support（7）Top be installed with vision biography
Sensor（6）.
A kind of 2. reaction type self study industrial robot according to claim 1, it is characterised in that end effector of robot
（3）On end performs device is installed.
3. a kind of method of work of reaction type self study industrial robot, it is characterised in that workflow includes：
Step 1：Neutral net is built, is robot posture information, the centre coordinate of object, pressure sensor on image（4）
Whether data run succeeded as neutral net input node and are used as neutral net output node, suitable hidden node number；
Step 2：By vision sensor（6）Gather image；
Step 3：Image is handled again, segmenting edge and target, obtain target dependent coordinate information such as centre coordinate；
Step 4：Then control machine people performs relevant action, if robot execution acts successfully, its pressure sensor（4）Will
Corresponding data is transmitted to host computer, otherwise, performs failure；
Step 5：The information such as posture information now, processing result image, implementing result are sent to neutral net input and output,
Meanwhile execution result back and coordinate information are to robot；
Step 6：Robot suitably adjusts pose according to the execution information of feedback；
Step 7：Repeat step 5 and 6, until end runs succeeded；
Step 8：Train neutral net；
Step 9：Step 2 is performed a plurality of times to step 8, until neutral net restrains, object space when obtaining pose and handling successfully,
Pressure sensor（4）The dependency relation of state etc., robot self study are completed；
Step 10：After completing self study, related work is performed according to neutral net result.
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| CN108772840A (en) * | 2018-07-02 | 2018-11-09 | 常州普旺科技有限公司 | A kind of adaptive sorting system and method based on computer vision and machine learning |
| CN109040688A (en) * | 2018-08-23 | 2018-12-18 | 顺德职业技术学院 | The method and system that the industrial robot operation video of a kind of pair of acquisition is stored |
| CN109079786A (en) * | 2018-08-17 | 2018-12-25 | 上海非夕机器人科技有限公司 | Mechanical arm grabs self-learning method and equipment |
| CN110302981A (en) * | 2019-06-17 | 2019-10-08 | 华侨大学 | A kind of solid waste sorts online grasping means and system |
| CN111003380A (en) * | 2019-12-25 | 2020-04-14 | 深圳蓝胖子机器人有限公司 | Method, system and equipment for intelligently recycling garbage |
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| CN108772840A (en) * | 2018-07-02 | 2018-11-09 | 常州普旺科技有限公司 | A kind of adaptive sorting system and method based on computer vision and machine learning |
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| CN110302981A (en) * | 2019-06-17 | 2019-10-08 | 华侨大学 | A kind of solid waste sorts online grasping means and system |
| CN111003380A (en) * | 2019-12-25 | 2020-04-14 | 深圳蓝胖子机器人有限公司 | Method, system and equipment for intelligently recycling garbage |
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