CN109318232A - A kind of polynary sensory perceptual system of industrial robot - Google Patents
A kind of polynary sensory perceptual system of industrial robot Download PDFInfo
- Publication number
- CN109318232A CN109318232A CN201811227842.5A CN201811227842A CN109318232A CN 109318232 A CN109318232 A CN 109318232A CN 201811227842 A CN201811227842 A CN 201811227842A CN 109318232 A CN109318232 A CN 109318232A
- Authority
- CN
- China
- Prior art keywords
- industrial robot
- information
- module
- industrial
- polynary
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/0005—Manipulators having means for high-level communication with users, e.g. speech generator, face recognition means
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
- B25J13/08—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
-
- 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
- B25J9/1661—Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
-
- 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
- B25J9/1666—Avoiding collision or forbidden zones
Abstract
The present invention relates to industrial robot control system technical fields, more specifically to a kind of polynary sensory perceptual system of industrial robot, by identifying received voice messaging, and generate the executable instruction of industrial robot；By acquiring the image information of industrial robot working environment, and the motor behavior of industrial robot is adjusted according to described image information in real time；By the electric current in acquisition servo motor, to obtain joint moment, carries out the control of closed loop power and drag teaching；It is applied to the external torque of industrial robot by calculating in real time, judges whether to collide；And real-time, interactive data information, and carry out the processing and control of data, so as to allow conventional industrial robot to have the teaching convenience of cooperation robot, safety in operation, while retain again its to torque, sound, the polynary perception of vision high speed and high-precision.
Description
Technical field
The present invention relates to industrial robot control system technical fields, more specifically to a kind of industrial robot
Polynary sensory perceptual system.
Background technique
Industrial robot is " jewel on manufacturing industry imperial crown top ", research and development, manufacture, using being to measure scientific and technical innovation and height
Hold the important symbol of manufacturing industry level.Constantly increase with application range with the development of science and technology, property of the people to robot
Higher and higher, the conventional industrial robot in addition to being widely used in industrial automation can be required, being also been developed can be with
The cooperation robot of people's interaction.Both robots are each advantageous, but there is also insufficient.
Conventional industrial robot is mainly used in industrial automation industry, such as spraying, stacking, polishing application are very wide
It is general.The characteristics of these applications is that movement is simple, repeatability is high, and this requires industrial robots to be completed in a relatively short time
More movements are to improve productivity.Therefore, conventional industrial robot generally has high speed, high-precision performance, this
In the case of, once it collides with people or ambient enviroment, it will cause irremediable loss；On the other hand, industrial robot
Mainly realize that the programming of robot motion track, teaching act not intuitive enough, programming efficiency by way of teaching machine teaching
It is lower.During teaching programming, it usually needs at a distance from operator and robot keep closer, pacify due to being not equipped with
Full inspection examining system, there is also some potential safety problemss；Robot cooperate due to leading man-machine collaboration, in order to guarantee safety thus
The speed of service is sacrificed, productivity is significantly limited.In addition, cooperation robot mainly realizes mesh by way of dragging teaching
The record of punctuation bit and track controls the precision of point by the eyes and hand of people in position fixing process, is unable to reach higher
Positioning accuracy.
In requirement of the industrial production to robot precision and speed higher and higher today, we need to design one kind and allow biography
System industrial robot has the teaching convenience of cooperation robot, safety in operation, while retaining its high speed, high precision again
The polynary sensory perceptual system of energy.
Summary of the invention
The present invention to overcome shortcoming and deficiency of the prior art, provides a kind of polynary perception system of industrial robot
System, the purpose of the present invention is to provide a kind of teaching conveniences for allowing conventional industrial robot to have cooperation robot, operation peace
Quan Xing, while retaining it again to torque, sound, vision with high speed, the system of high-precision polynary perception.
In order to achieve the above object, the present invention provides a kind of polynary sensory perceptual system of industrial robot, including interactive voice
Module, safety monitoring module, dragging teaching module, collision detection module and security decision module；
The voice interaction module for identifying received voice messaging, and is generated and is executed instruction；
The safety monitoring module, for acquiring the image information of industrial robot working environment, and according to described image
The motor behavior of information adjustment industrial robot；
The dragging teaching module, to obtain joint moment T, carries out closed loop for acquiring the electric current i in servo motor
Power control drags teaching, wherein T=Kt*i, kt are the torque constant of servo motor；
The collision detection module judges whether to collide for calculating the external torque for being applied to industrial robot；
The security decision module, for the voice interaction module, safety monitoring module, dragging teaching module, touch
Detection module real-time, interactive data information is hit, and carries out the processing and control of data.
Further, described to identify received voice messaging, and generate execute instruction specifically includes the following steps:
Step S11, voice messaging is converted into text information；
Step S12, the text information is converted into motion control information；
Step S13, judge whether the motion control information can be executed by industrial robot；
Step S14, according to the current state of industrial robot and outer environment state, judge to execute the motion control
Whether information is safe；
Step S15, executable, safe motion control information is compiled as executing instruction.
Further, the motion control information includes motion information, control information, IO information；
The motion information, for controlling the foundation motion of Industrial robots Mechanical's arm, and by the foundation motion parameter
It is packaged, defines common posture；
The control information, for control the starting of Industrial robots Mechanical's arm control system, pause, acceleration, deceleration and
Stop；
The IO information, for controlling and obtaining the I/O port state of Industrial robots Mechanical's arm control system.
Further, the image information of the acquisition industrial robot working environment, and worked according to the industrial robot
The motor behavior that the image information of environment adjusts industrial robot in real time specifically includes:
Step S21, depth of view information and colour information are obtained；
Step S22, three-dimensional reconstruction is carried out to industrial robot running environment, obtains the industrial robot running environment
Three-dimensional point cloud information；
Step S23, the mechanical arm point cloud information in three-dimensional point cloud information is filtered；
Step S24, three-dimensional point cloud information and mechanical arm posture information are parsed, judges that mechanical arm current operating conditions whether can
It collides；
Step S25, when judging that mechanical arm can collide, if industrial robot is currently scheduling and planning, mechanical arm subtracts
Speed operation, avoiding obstacles；If industrial robot is currently automatic running, mechanical arm is out of service.
Further, the dragging teaching module is also used to, and carries out velocity and acceleration to Industrial robots Mechanical's arm body
Sampling carries out kinetic model identification；By adjusting the damping in dragging process.
Further, the collision detection module is specifically used for, and calculates the external torque for being applied to industrial robot in real time,
Judge whether the collision that can occur；When colliding, robot is stopped running immediately；After collision warning is released from, machine
Path before people edge continues to run.
Further, the Rule of judgment that the collision warning is released from is that the collision detection module calculating is applied to industry
The external torque of robot is 0, and the safety monitoring module detects that industrial robot described in obstacle distance is more than threshold value.
The beneficial effects of the present invention are: the present invention discloses a kind of industrial sensor failure prediction method based on deep learning
And system, human-computer interaction is carried out by the way of voice, by identifying received voice messaging, and generates industrial machine
The instruction that people can be performed；The movement row of industrial robot is adjusted by acquiring the image information of industrial robot working environment
For；By the electric current in acquisition servo motor, to obtain joint moment, carries out the control of closed loop power and drag teaching；By counting in real time
The external torque for being applied to industrial robot is calculated, judges whether to collide；By real-time, interactive data information, and carry out data
Processing and control, so as to allow conventional industrial robot to have the cooperation teaching convenience of robot, safety in operation, simultaneously
Retain again its to torque, sound, the polynary perception of vision high speed and high-precision.
Detailed description of the invention
The invention will be further described with example with reference to the accompanying drawing.
Fig. 1 is a kind of block diagram of the polynary sensory perceptual system of industrial robot of the embodiment of the present invention；
Fig. 2 is the flow diagram of the polynary sensory perceptual system step S1 of industrial robot of the embodiment of the present invention a kind of；
Fig. 3 is the flow diagram of the polynary sensory perceptual system step S2 of industrial robot of the embodiment of the present invention a kind of.
Specific embodiment
With reference to Fig. 1, the present invention is described in further detail with specific embodiment with reference to the accompanying drawing.
A kind of polynary sensory perceptual system of industrial robot provided by the invention, including voice interaction module 1, safety monitoring mould
Block 2, dragging teaching module 3, collision detection module 4 and security decision module 5；
The voice interaction module 1 for identifying received voice messaging, and is generated and is executed instruction；
The voice interaction module 1 is that the software of the speech recognition algorithm exploitation based on deep learning will in the present embodiment
Speech recognition tools based on Iflytek AIUI man-machine interactive platform are applied on industrial robot, and by expanding machinery, people is grasped
Work and control mode allow operator using a kind of this more natural interactive mode of voice, robot can correctly be managed
The intention of people is solved, the intelligent interaction of people and robot is realized, completes corresponding task.Under this interactive mode, operator
Robot can be directly controlled by voice, realize that record point, trajectory reproducing etc. are simple but use frequent instruction, thus
The teaching convenience to industrial robot is realized, and ensure that the high speed and high-precision of speech recognition；
The safety monitoring module 2, for acquiring the image information of industrial robot working environment, and according to described image
Information adjusts the motor behavior of industrial robot in real time, to realize the safety in operation to industrial robot, and ensure that
The high speed and high-precision of vision-based detection；
The dragging teaching module 3, the electric current i for acquiring in servo motor are closed to obtain joint moment T
Ring power control drags teaching, wherein T=Kt*i, kt are the torque constant of servo motor, to realize the perception to torque；
The collision detection module 4 judges whether to occur for calculating the external torque for being applied to industrial robot in real time
Collision；
The security decision module 5 is used for and the voice interaction module 1, safety monitoring module 2, dragging teaching module
3,4 real-time, interactive data information of collision detection module, and the processing and control of data are carried out, further improve industrial robot
Safety in operation.
In the present embodiment, it is uniformly processed, is uniformly controlled by security decision module 5 in the data set of each module, as polynary
The decision core of sensory perceptual system, security decision module 5 are shown respectively at the voice interaction module 1, safety monitoring module 2, dragging
Teach module 3, the coupling of 4 data of collision detection module.
Further, described to identify received voice messaging with reference to Fig. 2, and generate execute instruction specifically include with
Lower step:
Step S11, voice messaging is converted into text information；The present embodiment is opened using existing Iflytek language identification
Send out platform；
Step S12, the text information is converted to by motion control information by speech recognition；
The present embodiment passes through the dynamic of the motion control of the matching algorithm acquisition demonstrator of regular expression and more characters matchings
Make information, and the parameter of control movement, to carry out intents；
Step S13, by comparing the motion control instruction in the motion control information and database, according to than
Whether the motion control information can be executed by industrial robot is judged to result, the motion control is illustrated if comparing successfully
Information can be executed by industrial robot, to carry out legitimacy analysis to the voice messaging, whether judge the voice messaging
It can be identified and be executed by industrial robot, will can be referred to by the voice messaging that industrial robot executes as legal robot control
It enables；
Step S14, it according to the current state of industrial robot and outer environment state, is limited, speed, acceleration
It checks, and carries out collision detection, to whether safely to judge to execute the motion control information；Using based on three in the present embodiment
Tie up the AABB collision detection algorithm row collision detection of environment point cloud model；
Step S15, executable, safe motion control information is compiled as executing instruction.
By the way of voice input, human-computer interaction is maximumlly facilitated, the convenience of teaching is improved；By preparatory
Legitimacy, safety judgement are carried out to input information, improve the safety of industrial robot operation.
Further, in the voice interaction module 1, voice messaging corresponds to one or more and executes instruction.In order to improve
Interactive efficiency, it is particularly significant to design a set of motion control information, motion control information described in the present embodiment include motion information,
Control information, IO information:
The motion information, for controlling the foundation motion of Industrial robots Mechanical's arm, and by the foundation motion parameter
(such as speed, acceleration) is packaged, and defines common posture (such as clear point posture)；
The control information, for controlling the basic function of Industrial robots Mechanical's arm control system, the basic function
Including starting, pause, acceleration, deceleration and stopping；
By controlling Industrial robots Mechanical's arm loading and unloading, the starting pause, acceleration-deceleration of program in the present embodiment,
Reach the basic function of control Industrial robots Mechanical's arm control system.
The IO information, for controlling and obtaining the I/O port state of Industrial robots Mechanical's arm control system.
The present embodiment is by advance corresponding I/O port number and instruction, to by instruction control and obtain IO
Mouth state.
Further, with reference to Fig. 3, the image information of the acquisition industrial robot working environment, and according to the industrial machine
The motor behavior that the image information of device people's working environment adjusts industrial robot in real time specifically includes:
Step S21, depth image information and color image information are obtained；The present embodiment is using depth of field binocular camera to work
Industry robot carries out safety monitoring, can accurately perceive the variation of external environment, safety problem occurs and promptly respond；
Step S22, it by carrying out three-dimensional reconstruction to industrial robot running environment using the point cloud information in point cloud library, obtains
Take the three-dimensional point cloud information of the industrial robot running environment；
Step S23, according to the three-dimensional point cloud of the posture information of industrial robot Current mechanical arm and the industrial robot
Information filters the mechanical arm point cloud information in the industrial robot three-dimensional point cloud information by point cloud matching；
Step S24, the industrial robot running environment is parsed by motion planning and AABB collision detection algorithm
Three-dimensional point cloud information and mechanical arm posture information, judge whether the current operating conditions of Industrial robots Mechanical's arm can be sent out
Raw collision or interference, the mechanical arm posture information are read from the controller of the industrial robot；
Step S25, when judging that Industrial robots Mechanical's arm current operating conditions can collide, if industrial machine
People is currently operator's scheduling and planning, that is, when being in collaboration mode, carries out deceleration processing, keep mechanical arm running track not
Become；If judgement carries out deceleration, processing can still encounter barrier, carry out Dynamic Programming, cut-through by motion planning
Object；If industrial robot is currently automatic running production, that is, when being in guard model, mechanical arm will directly carry out dock
Reason, guarantees safety to greatest extent.
Judge the condition that mechanical arm current operating conditions can collide are as follows:
The personnel of detecting enter safety zone；
Or detect that barrier is on robot running track.
Further, the dragging teaching module 3 is also used to, and carries out velocity and acceleration to Industrial robots Mechanical's arm body
Sampling carries out kinetic model identification；By adjusting the damping in dragging process, robot Shared control is realized；
Without adding additional torque sensor, pass is can be realized in the simple current feedback using in servo-driver
The range that power perceives is expanded to entire robot by the estimation for saving torque.
Further, the collision detection module 4 is specifically used for, and by carrying out Dynamic Modeling to robot, calculates in real time
It is applied to the external torque of industrial robot out, judges whether the collision that can occur, without torque sensor；It is touching
Zhuan Shi robot stops running immediately；After collision warning is released from, the path before Robot is continued to run, without weight
Newly power on.
Further, the Rule of judgment that the collision warning is released from is that the calculating of collision detection module 4 is applied to industry
The external torque of robot is 0, and the safety monitoring module 2 detects that industrial robot described in obstacle distance is more than threshold
Value, the threshold value are manually set according to actual size of the space.
The above, only presently preferred embodiments of the present invention, the invention is not limited to above embodiment, as long as
It reaches technical effect of the invention with identical means, all should belong to protection scope of the present invention.
Claims (7)
1. a kind of polynary sensory perceptual system of industrial robot, which is characterized in that including voice interaction module, safety monitoring module,
Drag teaching module, collision detection module and security decision module；
The voice interaction module for identifying received voice messaging, and is generated and is executed instruction；
The safety monitoring module, for acquiring the image information of industrial robot working environment, and according to described image information
Adjust the motor behavior of industrial robot；
The dragging teaching module, to obtain joint moment T, carries out the control of closed loop power for acquiring the electric current i in servo motor
Drag teaching, wherein T=Kt*i, kt are the torque constant of servo motor；
The collision detection module judges whether to collide for calculating the external torque for being applied to industrial robot；
The security decision module, for being examined with the voice interaction module, safety monitoring module, dragging teaching module, collision
Module real-time, interactive data information is surveyed, and carries out the processing and control of data.
2. a kind of polynary sensory perceptual system of industrial robot according to claim 1, which is characterized in that it is described will be received
Voice messaging identified, and generate execute instruction specifically includes the following steps:
Step S11, voice messaging is converted into text information；
Step S12, the text information is converted into motion control information；
Step S13, judge whether the motion control information can be executed by industrial robot；
Step S14, according to the current state of industrial robot and outer environment state, judge to execute the motion control information
It is whether safe；
Step S15, executable, safe motion control information is compiled as executing instruction.
3. a kind of polynary sensory perceptual system of industrial robot according to claim 2, which is characterized in that the motion control
Information includes motion information, control information, IO information；
The motion information, for controlling the foundation motion of Industrial robots Mechanical's arm, and by the parameter of the foundation motion into
Row encapsulation, defines common posture；
The control information, for controlling starting, pause, acceleration, deceleration and the stopping of Industrial robots Mechanical's arm control system；
The IO information, for controlling and obtaining the I/O port state of Industrial robots Mechanical's arm control system.
4. a kind of polynary sensory perceptual system of industrial robot according to claim 1, which is characterized in that the acquisition industry
The image information of robot working environment, and industrial machine is adjusted according to the image information of the industrial robot working environment in real time
The motor behavior of device people specifically includes:
Step S21, depth of view information and colour information are obtained；
Step S22, three-dimensional reconstruction is carried out to industrial robot running environment, obtains the three-dimensional of the industrial robot running environment
Point cloud information；
Step S23, the mechanical arm point cloud information in three-dimensional point cloud information is filtered；
Step S24, three-dimensional point cloud information and mechanical arm posture information are parsed, judges whether mechanical arm current operating conditions can occur
Collision；
Step S25, when judging that mechanical arm can collide, if industrial robot is currently scheduling and planning, mechanical arm, which slows down, to be transported
Row, avoiding obstacles；If industrial robot is currently automatic running, mechanical arm is out of service.
5. a kind of polynary sensory perceptual system of industrial robot according to claim 1, which is characterized in that the dragging teaching
Module is also used to, and is carried out velocity and acceleration sampling to Industrial robots Mechanical's arm body, is carried out kinetic model identification；Pass through
Adjust the damping in dragging process.
6. a kind of polynary sensory perceptual system of industrial robot according to claim 1, which is characterized in that the collision detection
Module is specifically used for, and calculates the external torque for being applied to industrial robot in real time, judges whether the collision that can occur；Occurring
Robot stops running immediately when collision；After collision warning is released from, the path before Robot is continued to run.
7. a kind of polynary sensory perceptual system of industrial robot according to claim 6, which is characterized in that the collision warning
The Rule of judgment being released from is that it is 0 that the collision detection module, which calculates and is applied to the external torque of industrial robot, and the peace
Full monitoring modular detects that industrial robot described in obstacle distance is more than threshold value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811227842.5A CN109318232A (en) | 2018-10-22 | 2018-10-22 | A kind of polynary sensory perceptual system of industrial robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811227842.5A CN109318232A (en) | 2018-10-22 | 2018-10-22 | A kind of polynary sensory perceptual system of industrial robot |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109318232A true CN109318232A (en) | 2019-02-12 |
Family
ID=65262665
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811227842.5A Pending CN109318232A (en) | 2018-10-22 | 2018-10-22 | A kind of polynary sensory perceptual system of industrial robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109318232A (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109866226A (en) * | 2019-04-12 | 2019-06-11 | 黄河水利职业技术学院 | A kind of polynary perception information processing system and method for industrial robot |
| CN110026984A (en) * | 2019-05-08 | 2019-07-19 | 苏州东控自动化科技有限公司 | A kind of smart collaboration control method based on large power output machine device people |
| CN110181516A (en) * | 2019-06-18 | 2019-08-30 | 苏州大学 | A kind of paths planning method of spray robot, device, system and storage medium |
| CN110757461A (en) * | 2019-11-13 | 2020-02-07 | 江苏方时远略科技咨询有限公司 | Control system and control method of industrial mobile robot |
| CN111015656A (en) * | 2019-12-19 | 2020-04-17 | 佛山科学技术学院 | Control method and device for robot to actively avoid obstacle and storage medium |
| CN111016107A (en) * | 2019-12-06 | 2020-04-17 | 深圳市山龙智控有限公司 | Injection molding machine mechanical arm demonstration system and demonstration method |
| CN112207857A (en) * | 2019-07-12 | 2021-01-12 | 上海智殷自动化科技有限公司 | Offline teaching system based on binocular vision system |
| CN112904747A (en) * | 2021-01-29 | 2021-06-04 | 成都视海芯图微电子有限公司 | Control system and control method based on intelligent sensing |
| CN114193453A (en) * | 2021-12-30 | 2022-03-18 | 浙江博采传媒有限公司 | Method for restoring camera track by using mechanical arm |
| CN114310907A (en) * | 2022-01-25 | 2022-04-12 | 佛山智能装备技术研究院 | Multi-working-condition self-adaptive industrial robot tail end vibration suppression method |
| CN114750168A (en) * | 2022-06-14 | 2022-07-15 | 苏州上舜精密工业科技有限公司 | Mechanical arm control method and system based on machine vision |
| CN114821852A (en) * | 2022-06-07 | 2022-07-29 | 国网安徽省电力有限公司宣城供电公司 | Power grid defect depth identification inspection robot control system based on characteristic pyramid |
| CN117584157A (en) * | 2024-01-17 | 2024-02-23 | 深圳威洛博机器人有限公司 | Circulation type guiding control system of industrial robot module |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014012919A1 (en) * | 2012-07-17 | 2014-01-23 | Reis Group Holding Gmbh & Co. Kg | Method for operating an industrial robot, and a secure monitoring device for carrying out said method |
| CN104057458A (en) * | 2014-06-16 | 2014-09-24 | 浙江大学 | Multi-shaft mechanical arm visual control system and method based on somatosensation and touch |
| CN104608127A (en) * | 2013-11-05 | 2015-05-13 | 库卡实验仪器有限公司 | Method for programming sequences of movements of a redundant industrial robot and associated industrial robot |
| CN106041937A (en) * | 2016-08-16 | 2016-10-26 | 河南埃尔森智能科技有限公司 | Control method of manipulator grabbing control system based on binocular stereoscopic vision |
| CN106363637A (en) * | 2016-10-12 | 2017-02-01 | 华南理工大学 | Fast teaching method and device for robot |
| CN106426186A (en) * | 2016-12-14 | 2017-02-22 | 国网江苏省电力公司常州供电公司 | Electrified operation robot autonomous operation method based on multi-sensor information fusion |
| CN106994686A (en) * | 2016-12-01 | 2017-08-01 | 遨博（北京）智能科技有限公司 | The computational methods and device, robot of joint external force torque |
| US20170320211A1 (en) * | 2016-05-09 | 2017-11-09 | Opiflex Automation AB | system and a method for programming an industrial robot |
| CN107813308A (en) * | 2017-10-20 | 2018-03-20 | 高井云 | A kind of human computer cooperation system of robot |
| CN108247654A (en) * | 2018-02-05 | 2018-07-06 | 遨博（北京）智能科技有限公司 | A kind of control method of robot, device and system |
| CN108274448A (en) * | 2018-01-31 | 2018-07-13 | 佛山智能装备技术研究院 | A kind of the robot teaching method and teaching system of human body interaction |
| CN108290296A (en) * | 2015-12-07 | 2018-07-17 | 川崎重工业株式会社 | Robot system and its method of operation |
| CN108447479A (en) * | 2018-02-02 | 2018-08-24 | 上海大学 | The robot voice control system of noisy work condition environment |
| CN108582069A (en) * | 2018-04-17 | 2018-09-28 | 上海达野智能科技有限公司 | Robot drags teaching system and method, storage medium, operating system |
-
2018
- 2018-10-22 CN CN201811227842.5A patent/CN109318232A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014012919A1 (en) * | 2012-07-17 | 2014-01-23 | Reis Group Holding Gmbh & Co. Kg | Method for operating an industrial robot, and a secure monitoring device for carrying out said method |
| CN104608127A (en) * | 2013-11-05 | 2015-05-13 | 库卡实验仪器有限公司 | Method for programming sequences of movements of a redundant industrial robot and associated industrial robot |
| CN104057458A (en) * | 2014-06-16 | 2014-09-24 | 浙江大学 | Multi-shaft mechanical arm visual control system and method based on somatosensation and touch |
| CN108290296A (en) * | 2015-12-07 | 2018-07-17 | 川崎重工业株式会社 | Robot system and its method of operation |
| US20170320211A1 (en) * | 2016-05-09 | 2017-11-09 | Opiflex Automation AB | system and a method for programming an industrial robot |
| CN106041937A (en) * | 2016-08-16 | 2016-10-26 | 河南埃尔森智能科技有限公司 | Control method of manipulator grabbing control system based on binocular stereoscopic vision |
| CN106363637A (en) * | 2016-10-12 | 2017-02-01 | 华南理工大学 | Fast teaching method and device for robot |
| CN106994686A (en) * | 2016-12-01 | 2017-08-01 | 遨博（北京）智能科技有限公司 | The computational methods and device, robot of joint external force torque |
| CN106426186A (en) * | 2016-12-14 | 2017-02-22 | 国网江苏省电力公司常州供电公司 | Electrified operation robot autonomous operation method based on multi-sensor information fusion |
| CN107813308A (en) * | 2017-10-20 | 2018-03-20 | 高井云 | A kind of human computer cooperation system of robot |
| CN108274448A (en) * | 2018-01-31 | 2018-07-13 | 佛山智能装备技术研究院 | A kind of the robot teaching method and teaching system of human body interaction |
| CN108447479A (en) * | 2018-02-02 | 2018-08-24 | 上海大学 | The robot voice control system of noisy work condition environment |
| CN108247654A (en) * | 2018-02-05 | 2018-07-06 | 遨博（北京）智能科技有限公司 | A kind of control method of robot, device and system |
| CN108582069A (en) * | 2018-04-17 | 2018-09-28 | 上海达野智能科技有限公司 | Robot drags teaching system and method, storage medium, operating system |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109866226A (en) * | 2019-04-12 | 2019-06-11 | 黄河水利职业技术学院 | A kind of polynary perception information processing system and method for industrial robot |
| CN110026984A (en) * | 2019-05-08 | 2019-07-19 | 苏州东控自动化科技有限公司 | A kind of smart collaboration control method based on large power output machine device people |
| CN110181516A (en) * | 2019-06-18 | 2019-08-30 | 苏州大学 | A kind of paths planning method of spray robot, device, system and storage medium |
| CN112207857A (en) * | 2019-07-12 | 2021-01-12 | 上海智殷自动化科技有限公司 | Offline teaching system based on binocular vision system |
| CN110757461A (en) * | 2019-11-13 | 2020-02-07 | 江苏方时远略科技咨询有限公司 | Control system and control method of industrial mobile robot |
| CN111016107A (en) * | 2019-12-06 | 2020-04-17 | 深圳市山龙智控有限公司 | Injection molding machine mechanical arm demonstration system and demonstration method |
| CN111015656A (en) * | 2019-12-19 | 2020-04-17 | 佛山科学技术学院 | Control method and device for robot to actively avoid obstacle and storage medium |
| CN112904747A (en) * | 2021-01-29 | 2021-06-04 | 成都视海芯图微电子有限公司 | Control system and control method based on intelligent sensing |
| CN114193453A (en) * | 2021-12-30 | 2022-03-18 | 浙江博采传媒有限公司 | Method for restoring camera track by using mechanical arm |
| CN114310907A (en) * | 2022-01-25 | 2022-04-12 | 佛山智能装备技术研究院 | Multi-working-condition self-adaptive industrial robot tail end vibration suppression method |
| CN114310907B (en) * | 2022-01-25 | 2024-01-16 | 佛山智能装备技术研究院 | Multi-working-condition self-adaptive industrial robot tail end vibration suppression method |
| CN114821852A (en) * | 2022-06-07 | 2022-07-29 | 国网安徽省电力有限公司宣城供电公司 | Power grid defect depth identification inspection robot control system based on characteristic pyramid |
| CN114821852B (en) * | 2022-06-07 | 2023-11-21 | 国网安徽省电力有限公司宣城供电公司 | Power grid defect depth identification inspection robot control system based on feature pyramid |
| CN114750168A (en) * | 2022-06-14 | 2022-07-15 | 苏州上舜精密工业科技有限公司 | Mechanical arm control method and system based on machine vision |
| CN114750168B (en) * | 2022-06-14 | 2022-09-20 | 苏州上舜精密工业科技有限公司 | Mechanical arm control method and system based on machine vision |
| CN117584157A (en) * | 2024-01-17 | 2024-02-23 | 深圳威洛博机器人有限公司 | Circulation type guiding control system of industrial robot module |
| CN117584157B (en) * | 2024-01-17 | 2024-04-09 | 深圳威洛博机器人有限公司 | Circulation type guiding control system of industrial robot module |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109318232A (en) | A kind of polynary sensory perceptual system of industrial robot | |
| US11396099B2 (en) | Safe operation of machinery using potential occupancy envelopes | |
| US9701014B2 (en) | Robot control device for preventing misjudgment by collision judging part | |
| JP2017080845A (en) | Robot control system | |
| US11254004B2 (en) | System identification of industrial robot dynamics for safety-critical applications | |
| US20210379762A1 (en) | Motion planning and task execution using potential occupancy envelopes | |
| CN111872936B (en) | Robot collision detection system and method based on neural network | |
| CN113021340B (en) | Robot control method, device, equipment and computer readable storage medium | |
| US11602852B2 (en) | Context-sensitive safety monitoring of collaborative work environments | |
| Ding et al. | Structured collaborative behavior of industrial robots in mixed human-robot environments | |
| Weitschat et al. | Safe and efficient human-robot collaboration part I: Estimation of human arm motions | |
| Ren et al. | Design of direct teaching behavior of collaborative robot based on force interaction | |
| US11919173B2 (en) | Motion planning and task execution using potential occupancy envelopes | |
| US20230173682A1 (en) | Context-sensitive safety monitoring of collaborative work environments | |
| CN111230854A (en) | Intelligent cooperative robot safety control software system | |
| Teke et al. | Real-time and robust collaborative robot motion control with Microsoft Kinect® v2 | |
| Wang et al. | Safety strategy in the smart manufacturing system: A human robot collaboration case study | |
| WO2020024074A1 (en) | Voice control system for operating machinery | |
| Stengel et al. | An approach for safe and efficient human-robot collaboration | |
| US10220514B2 (en) | Override-based, predictive speed capping | |
| CN111590574B (en) | Anti-theft method and system for high-intelligence robot | |
| CN208841397U (en) | A kind of intelligent machine arm system | |
| CN116330344A (en) | Cooperative robot collision detection method based on supervised learning support vector machine | |
| Wenzhong et al. | Sensorless robot collision detection based on optimized velocity deviation | |
| Popov et al. | Adaptive technique for physical human–robot interaction handling using proprioceptive sensors |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190212 |
|
| RJ01 | Rejection of invention patent application after publication |