CN106726209A - A kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence - Google Patents
A kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence Download PDFInfo
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- CN106726209A CN106726209A CN201611049200.1A CN201611049200A CN106726209A CN 106726209 A CN106726209 A CN 106726209A CN 201611049200 A CN201611049200 A CN 201611049200A CN 106726209 A CN106726209 A CN 106726209A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G5/00—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs
- A61G5/10—Parts, details or accessories
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G5/00—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs
- A61G5/04—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs motor-driven
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/10—General characteristics of devices characterised by specific control means, e.g. for adjustment or steering
- A61G2203/18—General characteristics of devices characterised by specific control means, e.g. for adjustment or steering by patient's head, eyes, facial muscles or voice
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- Life Sciences & Earth Sciences (AREA)
- Animal Behavior & Ethology (AREA)
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- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The present invention relates to a kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence, its technical characterstic includes:Measuring electrode is laid over the individual's scalp, the EEG signals of user are accessed by form wirelessly or non-wirelessly, the motion control information of user is obtained by brain-machine interface method, according to laser radar build environment map, obstacle information is obtained using the method for ultrasonic ranging and/or camera, avoiding obstacles simultaneously generate trajectory path planning, control the motion of wheelchair, and realize the feedback of self adaptation and self study using machine learning method in motion control.The present invention can not only help user to realize the safely and effectively control function of wheelchair, the control custom that user can be also based on realizes the controlled output of self study and self adaptation, and camera or other sensors need not be arranged in use environment, artificial intelligence Collaborative Control can be completed by the camera and sensor on wheelchair, the range of application of brain control intelligent wheel chair is expanded.
Description
Technical field
The invention belongs to brain-computer interface technology and field of artificial intelligence, especially it is a kind of based on brain-computer interface with it is artificial
The method for controlling intelligent wheelchair of intelligence.
Background technology
Current China disabled person sum is about 85,000,000 people, and 90,000,000 people are up to the year two thousand twenty, wherein 27% is limbs
It is disabled.The accessory outfit rate of physical disabilities patient allows of no optimist.In areas of well-being, accessory outfit rate is about 20%, miserably
Area is even below 5%.Therefore, not only market potential is huge for the accessory such as wheelchair, and is worth with prominent social application.However,
There is considerable part physical disabilities and paralytic in reality due to traditional manual/electric wheelchair cannot be manipulated, to life and
Prognosis rehabilitation causes difficulty.The reason for causing this difficult essentially consists in:1st, patient cannot manipulate the joystick of wheelchair and send
Instruction;2nd, patient is considered as the motion of control wheelchair that cannot be safe.
For problem 1, the brain-computer interface technology for currently reaching its maturity has been realized in high speed, reliable man-machine interaction hand
Section, but simple brain-computer interface technology is only relied only on, still suffer from following problem:(1) brain-computer interface needs user highly
Focus on, it is difficult to use continuously for a long time;(2) although the transfer rate of brain-computer interface is higher, work as and obstacle occur
During the emergencies such as thing, quick, reliable reaction is still difficult to, it is difficult to substitute the prompt operation of control stick.Therefore, individually according to
Rely brain-computer interface technology, it is difficult to the safety issue in solve problem 2.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, there is provided a kind of reasonable in design, control is flexible, safe and reliable
The method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence.
The present invention solves its technical problem and takes following technical scheme to realize:
A kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence, comprises the following steps:
Step 1, measuring electrode is laid over the individual's scalp, by wired or wireless form by the brain electricity of user
Signal is accessed;
Step 2, the Laser Radar Scanning current scene by being fixed on wheelchair, obtain the preliminary mapping of current scene,
And constantly real-time circulation scanning refreshes newest scene information;
Step 3, the camera by being fixed on wheelchair surrounding and/or ultrasonic range finder obtain the photo of all directions
And/or range information, so that the barrier location information of all directions is obtained, and real-time circulation scanning refreshes newest barrier
Location information;
Step 4, the movement instruction sent by brain-computer interface acquisition user;
Step 5, the movable information sent according to user, the newest scene information obtained according to step 2 and step 3 and most
New barrier location information, carries out analysis and path planning, generates wheel chair sport control instruction;
Step 6:Wheel chair sport control instruction is dealt into wheelchair control mechanism, by wheelchair control mechanism controls wheel chair sport;
In wheel chair sport, simultaneously conduct is fed back for real-time collecting scene information and barrier location information and wheel chair sport velocity information,
There is barrier when wheel chair sport, fall or during excessive velocities factor, it is automatic to implement to slow down, avoid or stop operation, also, receive
The information and scene information, barrier location information, wheel chair sport velocity information of collection user's control wheelchair are used as feeding back and make
With machine learning method concluded and trained, feed back input when being generated as wheel chair sport control instruction next time.
The step 2 through the following steps that realize:
Step 2.1, laser radar obtain the range information of all directions, and build environment map;
Step 2.2, wheelchair self-position is mapped in environmental map, realizes the positioning of wheelchair.
The step 3 is realized by the following method:
When using camera, the image information in all directions is obtained by camera, known by image processing method
Other object information and depth information, according to object information and depth information, be calculated in all directions possible barrier and
The distance of barrier and wheelchair;
When using ultrasonic range finder, the object distance information in all directions, meter are obtained by ultrasonic range finder
Calculation obtains the distance of possible barrier and barrier and wheelchair in all directions;
When simultaneously using camera and ultrasonic range finder, the obstacle information and ultrasonic wave that image procossing can be obtained
The obstacle information for obtaining of finding range carries out synthesis, meanwhile, the safety priority of ultrasonic range finder could be arranged to higher than shooting
Head.
The step 5 through the following steps that realize:
Step 5.1, the operating instruction obtained according to step 4, wheelchair is generated in environmental map will be transported according to movement instruction
The destination locations for moving, and various possible movement locus are generated using path planning algorithm, in the generation of movement locus
, it is necessary to the safety priority of reference environment map, camera and/or ultrasonic range finder in journey, wherein, safety priority is pre-
First set, or change in operation;
Step 5.2, the scene information and obstacle information that are obtained according to step 2 and step 3, precalculate movement locus
Feasibility and the obstacle information being likely encountered, when movement locus infeasible or movement instruction completely will cause to immediately encounter obstacle
During thing, judge that this movement instruction is invalid, barrier will not be immediately encountered after it there is feasible movement locus and movement instruction execution
When hindering thing, wheel chair sport control instruction is generated according to this movement instruction.
The step 6 is using the method that machine learning method concluded and trained:For the control of user
Pattern and desired output build Mathematical Modeling, or based on the passing control custom of user and mode and wheelchair and surrounding
Environment, the relation of barrier and wheelchair speed build artificial neural network and are trained, and the wheel chair sport control for obtaining optimization is defeated
Go out scheme.
Advantages and positive effects of the present invention are:
The present invention utilizes integrated use brain-machine interface method and artificial intelligence approach, by the laser thunder being arranged on wheelchair
Up to, range sensor and camera, the method for controlling intelligent wheelchair of composition sensor network and brain-computer interface Collaborative Control, not only
Inconvenience can be helped to operate the user of wheelchair to realize the safely and effectively control of wheelchair using limbs, can also be based on the control of user
System custom realizes the controlled output of self study and self adaptation, and camera or other sensings need not be arranged in use environment
Device, artificial intelligence Collaborative Control can be completed by the camera and sensor on wheelchair, expand the application of brain control intelligent wheel chair
Scope.
Brief description of the drawings
Fig. 1 is process chart of the invention.
Specific embodiment
The embodiment of the present invention is further described below in conjunction with accompanying drawing:
A kind of method for controlling intelligent wheelchair based on brain-computer interface and artificial intelligence is based on people fast-developing in recent years
Work intellectual technology.Artificial intelligence technology has been demonstrated to be realized effectively and reliable by computer vision, sensor network means
Man-machine interaction miscellaneous function.By artificial intelligence technology, on the one hand it is capable of the liberation user of part in brain-computer interface control
Upper required continuous notice concentrates duration, it is often more important that, additionally it is possible to effective auxiliary mechanism is provided, ensures user in control
Security during ratch chair.In fact, the security of artificial intelligence auxiliary travelling has been obtained for fully in automatic Pilot field
Checking.Therefore, by artificial intelligence technology and brain-computer interface technological incorporation, it is possible to provide effective, reliable cooperating type fusion
Control method, realizes the control of intelligent wheel chair.
Method for controlling intelligent wheelchair of the invention, as shown in figure 1, comprising the following steps:
Step 1:Measuring electrode is laid over the individual's scalp, in a wireless or wired way connects user's EEG signals
Enter.
In this step, the detection of user's EEG signals is to be used as sensor pickup skin brain telecommunications by external electrode
Number.It should be noted that electrode type, lead mode are not limited to the situation cited by the present embodiment.This area
Those skilled in the art it is to be appreciated that it is all provide EEG signals sampling electrode go for it is described in the invention
System and its implementation.Electrode type and lead mode provided in example be not intended as to use scope of the invention or
Function proposes any limitation.
Step 2:By the Laser Radar Scanning current scene being fixed on wheelchair, the preliminary mapping of current scene is obtained,
And constantly real-time circulation scanning refreshes newest scene information, specific method is as follows:
Step 2.1:Laser radar obtains the range information of all directions, and build environment map.Wherein, laser radar
Scanning can be directed to particular region of interest, or 360 degree of scanning processes of full angle, sweeping based on range information
Retouch, the range information corresponding relation on each border in wheelchair and environment can be generated, wheelchair position can be mapped to based on this relation
In environment, environmental map is obtained.
Step 2.2:After environmental map is obtained, location information of the wheelchair in environmental map is obtained.
Step 3:The photo of all directions is obtained by the camera and/or ultrasonic range finder that are fixed on wheelchair surrounding
And/or range information, so that the barrier location information of all directions is obtained, and constantly real-time circulation scanning refreshes newest barrier
Hinder thing location information.It should be noted that camera and ultrasonic range finder need not be realized in a specific implementation simultaneously
In example, can realize relying solely on camera according to different situations or rely solely on the embodiment of ultrasonic range finder, it is also possible to
The method based on camera and ultrasonic range finder is realized in one embodiment simultaneously, specific method is as follows:
Step 3.1:When using camera, the image information in all directions is obtained by camera, at image
Reason method recognizes object information and depth information, according to object information and depth information, is calculated possible in all directions
The distance of barrier and barrier and wheelchair.When using ultrasonic range finder, all directions are obtained by ultrasonic range finder
On object distance information, be calculated the distance of possible barrier and barrier and wheelchair in all directions.In a tool
In the embodiment of body, the direction number of camera and/or ultrasonic range finder detection is not specific, can be around wheelchair four
The four direction, or the more direction around wheelchair surrounding in week, can also be directed to particular region of interest, such as before wheelchair
Side or rear, set detection direction.
Step 3.2:When simultaneously using camera and ultrasonic range finder, the obstacle information that image procossing can be obtained
The obstacle information obtained with ultrasonic ranging carries out synthesis, meanwhile, the safety priority of ultrasonic range finder could be arranged to
Higher than camera;In a specific embodiment, ultrasonic range finder, camera, the safety priority of environmental map also may be used
To change in operation.
Step 4:The movement instruction that user sends is obtained by brain-computer interface technology.
In a specific embodiment, the method that brain-computer interface is realized is flexile, can be thought based on motion
The brain-computer interface of elephant, or the brain-computer interface based on electro photoluminescence, can also be based on regarding, the brain-computer interface of acoustic stimuli;
Step 5:According to the movable information that user sends, according to step 2, the 3 newest scene informations and newest barrier for obtaining
Hinder thing information, carry out analysis and path planning, generate wheel chair sport control instruction.Specific method is as follows:
Step 5.1:According to the movement instruction obtained from step 4, wheelchair is generated in environmental map will according to movement instruction
The destination locations for moving to, and various possible movement locus are generated using path planning algorithm, in the generation of movement locus
During, it is necessary to the safety priority of reference environment map, camera and/or ultrasonic range finder, wherein, safety priority can
Being set in advance, it is also possible to change in operation;
Step 5.2:According to step 2,3 scene informations and obstacle information for obtaining, the feasible of movement locus is precalculated
Property and the obstacle information that is likely encountered, when movement locus infeasible or movement instruction completely will cause to immediately encounter barrier
When, judge that this movement instruction is invalid, will not immediately encounter obstacle after it there is feasible movement locus and movement instruction execution
During thing, wheel chair sport control instruction is generated according to this movement instruction;
Step 6:Wheel chair sport control instruction is dealt into wheelchair control mechanism, makes wheel chair sport, and in wheel chair sport,
Keep real-time collecting scene information and barrier location information and wheel chair sport velocity information and as feedback, work as wheel chair sport
There is barrier, fall or during the unsafe factor such as excessive velocities, it is automatic to implement to slow down, avoid or stop operation, also, collect
The information and scene information, barrier location information of user's control wheelchair, wheel chair sport velocity information and used as feedback
Machine learning method is concluded and trained.
In a specific embodiment, machine learning method can be directed to the control model and desired output structure of user
Mathematical Modeling is built, be can also be based on the passing control custom of user and mode and wheelchair and surrounding environment, barrier
Relation and wheelchair speed build artificial neural network and are trained, and obtain the wheel chair sport controlled output scheme of optimization, so as to
Following wheel chair sport control of enough optimization, realizes being accustomed to user steady, the safe and reliable controlled output of self adaptation.
By above step, realize some targets of the invention and obtain other favourable outcomes.
Execution or the realization order of the above method not necessarily, unless otherwise.That is, the element of method can be used and appointed
What is sequentially performed, and unless otherwise, and method may include than more or less element disclosed herein.Can recognize
Before another element, simultaneously or afterwards to perform or realizing that element-specific is within the scope of the present invention.
When the element of the explanation present invention or embodiment, article " ", " one ", " being somebody's turn to do " and " described " refer to have one
Individual or multiple elements." including ", "comprising", " having " be intended to inclusive, and mean may be used also in addition to listed element
To there is other elements.
Due to various changes can be made in the said goods and method without departing from the scope of the invention, therefore
The all the elements for being included in description above and being shown in the drawings should all be interpreted illustrative and not restrictive.
Claims (5)
1. a kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence, it is characterised in that comprise the following steps:
Step 1, measuring electrode is laid over the individual's scalp, by wired or wireless form by the EEG signals of user
Access;
Step 2, the Laser Radar Scanning current scene by being fixed on wheelchair, obtain the preliminary mapping of current scene, not
Disconnected real-time circulation scanning refreshes newest scene information;
Step 3, the camera by being fixed on wheelchair surrounding and/or ultrasonic range finder obtain all directions photo and/or
Range information, so that the barrier location information of all directions is obtained, and real-time circulation scanning refreshes newest barrier positioning
Information;
Step 4, the movement instruction sent by brain-computer interface acquisition user;
Step 5, the movable information sent according to user, according to newest scene information and newest barrier that step 2 and step 3 are obtained
Hinder thing location information, carry out analysis and path planning, generate wheel chair sport control instruction;
Step 6:Wheel chair sport control instruction is dealt into wheelchair control mechanism, by wheelchair control mechanism controls wheel chair sport;In wheel
In chair motion, real-time collecting scene information and barrier location information and wheel chair sport velocity information work as wheel simultaneously as feedback
There is barrier, falls or during excessive velocities factor in chair motion, automatic to implement to slow down, avoid or stop operation, also, collection makes
The information and scene information, barrier location information, wheel chair sport velocity information of user's control wheelchair are used as feeding back and use machine
Device learning method concluded and trained, feed back input when being generated as wheel chair sport control instruction next time.
2. a kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence according to claim 1, its feature
It is:The step 2 through the following steps that realize:
Step 2.1, laser radar obtain the range information of all directions, and build environment map;
Step 2.2, wheelchair self-position is mapped in environmental map, realizes the positioning of wheelchair.
3. a kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence according to claim 1, its feature
It is:The step 3 is realized by the following method:
When using camera, the image information in all directions is obtained by camera, thing is recognized by image processing method
Body information and depth information, according to object information and depth information, are calculated possible barrier and obstacle in all directions
The distance of thing and wheelchair;
When using ultrasonic range finder, the object distance information in all directions is obtained by ultrasonic range finder, calculated
The distance of possible barrier and barrier and wheelchair on to all directions;
When simultaneously using camera and ultrasonic range finder, can be by the obstacle information of image procossing acquisition and ultrasonic ranging
The obstacle information of acquisition carries out synthesis, meanwhile, the safety priority of ultrasonic range finder could be arranged to higher than camera.
4. a kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence according to claim 1, its feature
It is:The step 5 through the following steps that realize:
Step 5.1, the operating instruction obtained according to step 4, generation wheelchair will be moved to according to movement instruction in environmental map
Destination locations, and generate various possible movement locus using path planning algorithm, in the generating process of movement locus,
The safety priority of environmental map, camera and/or ultrasonic range finder is needed to refer to, wherein, safety priority is to set in advance
Fixed, or change in operation;
Step 5.2, the scene information and obstacle information that are obtained according to step 2 and step 3, precalculate the feasible of movement locus
Property and the obstacle information that is likely encountered, when movement locus infeasible or movement instruction completely will cause to immediately encounter barrier
When, judge that this movement instruction is invalid, will not immediately encounter obstacle after it there is feasible movement locus and movement instruction execution
During thing, wheel chair sport control instruction is generated according to this movement instruction.
5. a kind of method for controlling intelligent wheelchair based on brain-computer interface Yu artificial intelligence according to claim 1, its feature
It is:The step 6 is using the method that machine learning method concluded and trained:For the control model of user
Mathematical Modeling is built with desired output, or based on the passing control custom of user and mode and wheelchair and surrounding ring
Border, the relation of barrier and wheelchair speed build artificial neural network and are trained, and obtain the wheel chair sport controlled output of optimization
Scheme.
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Cited By (15)
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CN107174418A (en) * | 2017-06-28 | 2017-09-19 | 歌尔股份有限公司 | A kind of intelligent wheel chair and its control method |
CN107320279A (en) * | 2017-07-07 | 2017-11-07 | 袁艳荣 | Intelligent crossing method |
CN107320809A (en) * | 2017-07-06 | 2017-11-07 | 杜昭钦 | Multifunctional children transfusion chair |
CN107432789A (en) * | 2017-07-20 | 2017-12-05 | 赵家琦 | Booster type stretcher |
CN107432811A (en) * | 2017-07-07 | 2017-12-05 | 袁艳荣 | Interactive dental chair |
CN107536677A (en) * | 2017-07-28 | 2018-01-05 | 北京航空航天大学 | The dynamic control electric wheelchair accessory system of High Paraplegia head |
CN107553491A (en) * | 2017-09-15 | 2018-01-09 | 华南理工大学 | A kind of brain control wheelchair mechanical arm |
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CN107320809B (en) * | 2017-07-06 | 2018-05-08 | 青岛大学附属医院 | Multifunctional children transfusion chair |
CN107320809A (en) * | 2017-07-06 | 2017-11-07 | 杜昭钦 | Multifunctional children transfusion chair |
CN107875472A (en) * | 2017-07-06 | 2018-04-06 | 杜昭钦 | The application method of multifunctional children transfusion chair |
CN107432811A (en) * | 2017-07-07 | 2017-12-05 | 袁艳荣 | Interactive dental chair |
CN107320279A (en) * | 2017-07-07 | 2017-11-07 | 袁艳荣 | Intelligent crossing method |
CN107432789A (en) * | 2017-07-20 | 2017-12-05 | 赵家琦 | Booster type stretcher |
CN107536677A (en) * | 2017-07-28 | 2018-01-05 | 北京航空航天大学 | The dynamic control electric wheelchair accessory system of High Paraplegia head |
CN107553491A (en) * | 2017-09-15 | 2018-01-09 | 华南理工大学 | A kind of brain control wheelchair mechanical arm |
CN108536154A (en) * | 2018-05-14 | 2018-09-14 | 重庆师范大学 | Low speed automatic Pilot intelligent wheel chair construction method based on bioelectrical signals control |
CN109366508A (en) * | 2018-09-25 | 2019-02-22 | 中国医学科学院生物医学工程研究所 | A kind of advanced machine arm control system and its implementation based on BCI |
CN110315553A (en) * | 2019-06-23 | 2019-10-11 | 大国重器自动化设备(山东)股份有限公司 | A kind of dining room robot collision avoidance system and method |
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CN110956701A (en) * | 2019-10-24 | 2020-04-03 | 中国人民解放军军事科学院国防科技创新研究院 | Life support system and life support method |
CN112089559A (en) * | 2020-08-18 | 2020-12-18 | 西安交通大学 | Auxiliary standing device and method based on indoor positioning and artificial intelligence |
CN112089559B (en) * | 2020-08-18 | 2021-06-01 | 西安交通大学 | Auxiliary standing device and method based on indoor positioning and artificial intelligence |
CN112089541A (en) * | 2020-09-21 | 2020-12-18 | 深兰科技(上海)有限公司 | Intelligent wheelchair control system and method |
CN114046796A (en) * | 2021-11-04 | 2022-02-15 | 南京理工大学 | Intelligent wheelchair autonomous walking algorithm, device and medium |
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