CN113101079A - Intelligent wheelchair based on multiple constraint conditions, and dynamic sharing control method and system - Google Patents

Intelligent wheelchair based on multiple constraint conditions, and dynamic sharing control method and system Download PDF

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CN113101079A
CN113101079A CN202110550095.4A CN202110550095A CN113101079A CN 113101079 A CN113101079 A CN 113101079A CN 202110550095 A CN202110550095 A CN 202110550095A CN 113101079 A CN113101079 A CN 113101079A
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wheelchair
user
control instruction
head posture
autonomous navigation
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徐国政
孙星
王强
张庆松
王聪
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Nanjing University of Posts and Telecommunications
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Nanjing University of Posts and Telecommunications
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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
    • A61G5/1051—Arrangements for steering
    • 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
    • A61G5/06—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs with obstacle mounting facilities, e.g. for climbing stairs, kerbs or steps
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0234—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
    • G05D1/0236—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons in combination with a laser
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
    • 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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  • Automation & Control Theory (AREA)
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  • Health & Medical Sciences (AREA)
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  • Public Health (AREA)
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  • Electromagnetism (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention discloses an intelligent wheelchair based on multiple constraint conditions, a dynamic sharing control method and a system, wherein the method comprises the following steps: based on monitoring data acquired in the wheelchair running process, corresponding weight coefficients are dynamically acquired by synthesizing multi-aspect constraint conditions; linearly combining the weight coefficients to obtain the weight coefficients of the head posture control command and the autonomous navigation control command; determining a shared control instruction of the wheelchair according to the weight coefficients of the head posture control instruction and the autonomous navigation control instruction; performing dynamic sharing control on the wheelchair according to the sharing control instruction; wherein, the multi-aspect constraint conditions comprise the safe distance between the wheelchair and the obstacle, the fatigue degree of the neck muscles of the user and the smoothness of the head posture control wheelchair track. The invention can realize dynamic share control of the wheelchair, effectively reduce the fatigue feeling of the user, give the user as much control right as possible, and improve the safety, comfort and continuity of the user driving the wheelchair.

Description

Intelligent wheelchair based on multiple constraint conditions, and dynamic sharing control method and system
Technical Field
The invention relates to an intelligent wheelchair based on multiple constraint conditions, and a dynamic sharing control method and system, and belongs to the technical field of wheelchair control.
Background
In recent years, intelligent wheelchairs have become a means of transportation for disabled and old people. The conventional electric wheelchair controls the wheelchair using a joystick, but is difficult to implement for a user having upper limbs with dyskinesia. With only some of the user's existing skills, such as head-posture control of a wheelchair, maintaining a head posture for a long time may cause fatigue to the user. By using the intelligent wheelchair for autonomous navigation, the wheelchair can completely and autonomously move, and excessive help is provided for a user, so that the user can lose the residual skills. Under a man-machine shared control mode, a user and the intelligent wheelchair are mutually assisted to complete a mobile control task together, and the shared control key lies in how to fuse and switch a user instruction and an autonomous navigation instruction. In the conventional sharing control method, an additional switch is used for switching between different modes, which can cause unnecessary interruption in the driving process; estimating the user intention, selecting the most possible driving track according to the input of the user, only selecting the track prepared in advance, and ensuring that the user cannot obtain enough control power; the linear combination man-machine control instruction has fixed weight coefficient, does not change along with the change of driving environment and has certain potential safety hazard.
In order to solve the problems, the application provides an intelligent wheelchair based on multiple constraint conditions, and a dynamic sharing control method and system.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides an intelligent wheelchair based on multiple constraint conditions, a dynamic sharing control method and a system, wherein multiple factors are integrated, the weight coefficients distributed to a head posture control instruction and an autonomous navigation instruction are dynamically adjusted, and dynamic sharing control of the wheelchair is realized; the fatigue feeling of the user can be effectively reduced, the user can be given as much control right as possible, and the safety, comfort and continuity of the user driving the wheelchair are improved.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the invention provides a multi-constraint condition-based intelligent wheelchair dynamic sharing control method, which comprises the following steps:
based on monitoring data acquired in the wheelchair running process, corresponding weight coefficients are dynamically acquired by synthesizing multi-aspect constraint conditions;
linearly combining the weight coefficients to obtain the weight coefficients of the head posture control command and the autonomous navigation control command;
determining a shared control instruction of the wheelchair according to the weight coefficients of the head posture control instruction and the autonomous navigation control instruction;
performing dynamic sharing control on the wheelchair according to the sharing control instruction;
wherein, the multi-aspect constraint conditions comprise the safe distance between the wheelchair and the obstacle, the fatigue degree of the neck muscles of the user and the smoothness of the head posture control wheelchair track.
Preferably, the obtaining the corresponding weight coefficient includes:
obtaining the shortest distance d between the current wheelchair and the obstacle according to the monitoring data, and dynamically updating the weight coefficient k of the safety distance factordThe expression is as follows:
Figure BDA0003075107520000021
acquiring a signal value I of a real-time electromyographic signal of neck muscles of a user according to monitoring dataEMGDynamically updating the fatigue degree factor weight coefficient kfThe expression is as follows:
Figure BDA0003075107520000031
obtaining moving track data of a previous period of time according to the monitoring data, obtaining smoothness of the track according to curvature radius r in the moving track data, and dynamically updating a smoothness factor weight coefficient ksThe expression is as follows:
Figure BDA0003075107520000032
preferably, the obtaining of the weight coefficients of the head posture control command and the autonomous navigation control command includes:
the expression of the weight coefficient k of the head posture control command is as follows:
Figure BDA0003075107520000033
wherein a, b and c are weight coefficients kdWeight coefficient kfAnd a weight coefficient ksThe proportionality coefficient of (a);
the expression of the weight coefficient s of the autonomous navigation control command is as follows:
s＝1-k。
preferably, the determining the shared control instruction of the wheelchair comprises:
U(v,w)＝kU(vh,wh)+(1-k)U(vr,wr)
wherein U (v, w) represents speed information in a shared control command for a wheelchair, and U (v)h，wh) Indicating velocity information in the head attitude control command, U (v)r，wr) Representing speed information in the autonomous navigation command.
In a second aspect, the invention provides a multi-constraint condition based intelligent wheelchair dynamic sharing control system, which comprises:
the autonomous navigation control unit is used for generating an autonomous navigation control instruction;
the user head posture control unit is used for generating a head posture control instruction;
and the human-computer sharing control unit is used for generating a sharing control instruction according to the autonomous navigation control instruction and the head posture control instruction based on any one of the intelligent wheelchair dynamic sharing control methods based on the multi-constraint condition, and controlling the wheelchair to act through the sharing control instruction.
In a third aspect, the present invention provides a smart wheelchair comprising:
a wheelchair main body structure and an auxiliary structure arranged on the wheelchair main body structure;
the accessory structure comprises a depth camera and a PC controller;
the depth camera is arranged in front of the head of the user and used for acquiring a depth image of the head of the user; the PC controller acquires the head posture of the user according to the depth image of the head of the user so as to generate a head posture control instruction;
the PC controller is arranged in front of a user and used for acquiring an interactive instruction of the user so as to generate an automatic navigation control instruction;
the PC controller generates a sharing control instruction according to the autonomous navigation control instruction and the head posture control instruction based on any one of the intelligent wheelchair dynamic sharing control methods based on the multi-constraint condition, and controls the wheelchair to act through the sharing control instruction.
Preferably, the auxiliary structure further comprises a laser radar sensor, a myoelectric sensor, a track sensor and an encoder;
the laser radar sensor is arranged in front of the wheelchair main body structure and used for acquiring the distance from the wheelchair to the obstacle;
the myoelectric sensor is arranged behind the neck of the user and used for acquiring real-time myoelectric signals of neck muscles of the user;
the track sensor is arranged on the wheelchair main body structure and used for acquiring wheelchair moving track data;
the encoder is arranged on a tire of the wheelchair main body structure and used for acquiring wheelchair moving speed data.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an intelligent wheelchair based on multiple constraint conditions, a dynamic sharing control method and a system. The weight coefficients distributed to the head posture instruction and the autonomous navigation instruction are dynamically adjusted by integrating various constraint conditions such as the safe distance between the wheelchair and the obstacle, the fatigue degree of neck muscles, the head posture control wheelchair track smoothness and the like, so that the fatigue feeling of a user can be effectively reduced, the user is given control power as much as possible, and the safety, the continuity and the comfort of wheelchair driving are improved.
Drawings
FIG. 1 is a flowchart illustrating a method for dynamically sharing and controlling an intelligent wheelchair based on multiple constraints according to a first embodiment of the present invention;
FIG. 2 is a system block diagram of a multi-constraint based intelligent wheelchair dynamic sharing control system according to a second embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an intelligent wheelchair according to a third embodiment of the invention;
labeled as:
1. the system comprises a depth camera, 2, a PC controller, 3, a laser radar sensor, 4, a myoelectric sensor, 5, a track sensor, 6 and an encoder.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The first embodiment is as follows:
as shown in fig. 1, the embodiment provides a method for controlling dynamic sharing of an intelligent wheelchair based on multiple constraints, which includes the following steps:
step 1, dynamically acquiring corresponding weight coefficients by synthesizing multi-aspect constraint conditions based on monitoring data acquired in the wheelchair operation process; the multi-aspect constraint conditions comprise the safe distance between the wheelchair and the obstacle, the fatigue degree of the neck muscles of the user and the smoothness of the head posture control wheelchair track.
Step 1.1, obtaining the shortest distance d between the current wheelchair and the obstacle according to the monitoring data, and dynamically updating the weight coefficient k of the safety distance factordThe expression is as follows:
Figure BDA0003075107520000061
when the user isWhen the wheelchair is controlled to be about to collide with the barrier and d is less than the shortest safe distance of 0.2m, kdAnd if the number is 0, the user gives control power, and the intelligent wheelchair automatically avoids obstacles. The farther the wheelchair is away from the obstacle, the more convenient the obstacle avoidance is, and the larger the user instruction weight coefficient is; the closer the wheelchair is to the obstacle, the more inconvenient the obstacle avoidance is, and the smaller the user instruction weight coefficient is; when d is greater than the safety distance 1.5m, kdThe user grasps the control right and controls the movement of the wheelchair to 1.
Step 1.2, acquiring a signal value I of a real-time electromyographic signal of neck muscles of a user according to monitoring dataEMGDynamically updating the fatigue degree factor weight coefficient kfThe expression is as follows:
Figure BDA0003075107520000062
IEMGthe myoelectric value is integrated for the user's real time. I isEMGThe larger the size, the more fatigue the user feels, kfThe smaller, the less control is allocated to the user; i isEMGThe smaller the user's fatigue, the less kfThe larger the control power allocated to the user.
Step 1.3, obtaining moving track data of a previous period of time according to the monitoring data, obtaining smoothness of the track according to curvature radius r in the moving track data (and taking three points at equal intervals on the track to fit a curve y ═ f (x), using curvature at the middle point as curvature estimation of the curve to measure smoothness of the track of the previous period of time), and dynamically updating a smoothness factor weight coefficient ksThe expression is as follows:
Figure BDA0003075107520000071
r is the curvature radius of the curve at the middle point, the smaller r is, the smoother the track of the wheelchair is controlled by the head posture of the user, ksThe smaller the size, the lower the control power of the user; the larger r, the smoother the trajectory, ksThe larger the control power allocated to the user. When r is greater than 6.389m, ksIs 1.
And 2, linearly combining the weight coefficients to obtain the weight coefficients of the head posture control command and the autonomous navigation control command.
Step 2.1, the expression of the weight coefficient k of the head posture control instruction is as follows:
Figure BDA0003075107520000072
wherein a, b and c are weight coefficients kdWeight coefficient kfAnd a weight coefficient ksThe proportionality coefficient of (a); after repeated blending, a is 0.45, b is 0.32, and c is 0.23.
Step 2.2, the weight coefficient s of the autonomous navigation control instruction has the following expression:
s＝1-k。
step 3, determining a shared control instruction of the wheelchair according to the weight coefficients of the head posture control instruction and the autonomous navigation control instruction;
U(v,w)＝kU(vh,wh)+(1-k)U(vr,wr)
wherein U (v, w) represents speed information in a shared control command for a wheelchair, and U (v)h，wh) Indicating velocity information in the head attitude control command, U (v)r，wr) Representing speed information in the autonomous navigation command.
And 4, carrying out dynamic sharing control on the wheelchair according to the sharing control instruction.
And 5, dynamically updating the weight coefficient k of the head posture control instruction according to a certain frequency, and repeatedly executing the steps 1-4 until the wheelchair reaches a target point and stops moving.
Example two:
as shown in fig. 2, the present embodiment provides a multi-constraint based intelligent wheelchair dynamic sharing control system, comprising:
the autonomous navigation control unit is used for generating an autonomous navigation control instruction;
the user head posture control unit is used for generating a head posture control instruction;
and the human-computer sharing control unit is used for generating a sharing control instruction according to the autonomous navigation control instruction and the head posture control instruction based on any one of the multi-constraint condition-based intelligent wheelchair dynamic sharing control methods in the embodiment I and controlling the wheelchair to act through the sharing control instruction.
Example three:
as shown in fig. 3, the present implementation provides a smart wheelchair comprising:
a wheelchair main body structure and an auxiliary structure arranged on the wheelchair main body structure;
the accessory structure comprises a depth camera 1 and a PC controller 2
The depth camera 1 is arranged in front of the head of a user and used for acquiring a depth image of the head of the user; the PC controller 2 acquires the head posture of the user according to the depth image of the head of the user, so as to generate a head posture control instruction;
the PC controller 2 is arranged in front of a user and used for acquiring an interactive instruction of the user so as to generate an automatic navigation control instruction;
the PC controller 2 generates a sharing control instruction according to the autonomous navigation control instruction and the head posture control instruction based on any one of the intelligent wheelchair dynamic sharing control methods based on the multi-constraint condition, and controls the wheelchair to act through the sharing control instruction.
The auxiliary structure also comprises a laser radar sensor 3, a myoelectric sensor 4, a track sensor 5 and an encoder 6;
the laser radar sensor 3 is arranged in front of the wheelchair main body structure and used for acquiring the distance from the wheelchair to an obstacle;
the electromyographic sensor 4 is arranged behind the neck of the user and used for acquiring real-time electromyographic signals of the neck muscles of the user;
the track sensor 5 is arranged on the wheelchair main body structure and used for acquiring wheelchair moving track data;
the encoder 6 is arranged on the tire of the wheelchair main body structure and used for acquiring wheelchair moving speed data.
The intelligent wheelchair based on multiple constraint conditions, the dynamic sharing control method and the dynamic sharing control system provided by the invention can adjust the distribution problem of the control right of the intelligent wheelchair in real time according to the body state and the driving environment of a user. And the weight coefficients distributed to the head posture control instruction and the autonomous navigation instruction are dynamically adjusted by integrating various factors, so that the dynamic shared control of the wheelchair is realized. The dynamic sharing control method can effectively reduce the fatigue of the user, can endow the user with the control right as much as possible, and improves the safety, comfort and continuity of the user in driving the wheelchair.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (7)

1. A multi-constraint condition based intelligent wheelchair dynamic sharing control method is characterized by comprising the following steps:
based on monitoring data acquired in the wheelchair running process, corresponding weight coefficients are dynamically acquired by synthesizing multi-aspect constraint conditions;
linearly combining the weight coefficients to obtain the weight coefficients of the head posture control command and the autonomous navigation control command;
determining a shared control instruction of the wheelchair according to the weight coefficients of the head posture control instruction and the autonomous navigation control instruction;
performing dynamic sharing control on the wheelchair according to the sharing control instruction;
wherein, the multi-aspect constraint conditions comprise the safe distance between the wheelchair and the obstacle, the fatigue degree of the neck muscles of the user and the smoothness of the head posture control wheelchair track.
2. The method according to claim 1, wherein the obtaining of the corresponding weight coefficient comprises:
obtaining the shortest distance d between the current wheelchair and the obstacle according to the monitoring data, and dynamically updating the weight coefficient k of the safety distance factordThe expression is as follows:
Figure FDA0003075107510000011
acquiring a signal value I of a real-time electromyographic signal of neck muscles of a user according to monitoring dataEMGDynamically updating the fatigue degree factor weight coefficient kfThe expression is as follows:
Figure FDA0003075107510000012
obtaining moving track data of a previous period of time according to the monitoring data, obtaining smoothness of the track according to curvature radius r in the moving track data, and dynamically updating a smoothness factor weight coefficient ksThe expression is as follows:
Figure FDA0003075107510000021
3. the method according to claim 1, wherein the obtaining of the weight coefficients of the head posture control command and the autonomous navigation control command comprises:
the expression of the weight coefficient k of the head posture control command is as follows:
Figure FDA0003075107510000022
wherein a, b and c are weight coefficients kdWeight coefficient kfAnd a weight coefficient ksThe proportionality coefficient of (a);
the expression of the weight coefficient s of the autonomous navigation control command is as follows:
s＝1-k。
4. the method according to claim 3, wherein the determining the wheelchair sharing control command comprises:
U(v,w)＝kU(vh,wh)+(1-k)U(vr,wr)
wherein U (v, w) represents speed information in a shared control command for a wheelchair, and U (v)h，wh) Indicating velocity information in the head attitude control command, U (v)r，wr) Representing speed information in the autonomous navigation command.
5. A multi-constraint condition based intelligent wheelchair dynamic sharing control system is characterized by comprising:
the autonomous navigation control unit is used for generating an autonomous navigation control instruction;
the user head posture control unit is used for generating a head posture control instruction;
the human-machine sharing control unit is used for generating a sharing control instruction according to the autonomous navigation control instruction and the head posture control instruction based on the multi-constraint-condition-based intelligent wheelchair dynamic sharing control method of any one of claims 1 to 4 and controlling the wheelchair to act through the sharing control instruction.
6. An intelligent wheelchair, comprising:
a wheelchair main body structure and an auxiliary structure arranged on the wheelchair main body structure;
the accessory structure comprises a depth camera and a PC controller;
the depth camera is arranged in front of the head of the user and used for acquiring a depth image of the head of the user; the PC controller acquires the head posture of the user according to the depth image of the head of the user so as to generate a head posture control instruction;
the PC controller is arranged in front of a user and used for acquiring an interactive instruction of the user so as to generate an automatic navigation control instruction;
the PC controller generates a sharing control instruction according to the autonomous navigation control instruction and the head posture control instruction based on the intelligent wheelchair dynamic sharing control method based on the multi-constraint condition of any one of claims 1 to 4, and controls the wheelchair to act through the sharing control instruction.
7. The intelligent wheelchair as claimed in claim 6, wherein the auxiliary structure further comprises a lidar sensor, a myoelectric sensor, a track sensor and an encoder;
the laser radar sensor is arranged in front of the wheelchair main body structure and used for acquiring the distance from the wheelchair to the obstacle;
the myoelectric sensor is arranged behind the neck of the user and used for acquiring real-time myoelectric signals of neck muscles of the user;
the track sensor is arranged on the wheelchair main body structure and used for acquiring wheelchair moving track data;
the encoder is arranged on a tire of the wheelchair main body structure and used for acquiring wheelchair moving speed data.
CN202110550095.4A 2021-05-20 2021-05-20 Intelligent wheelchair based on multiple constraint conditions, and dynamic sharing control method and system Pending CN113101079A (en)

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Cited By (3)

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CN114376811A (en) * 2021-12-13 2022-04-22 深圳市优必选科技股份有限公司 Wheelchair, control method and device thereof, and computer-readable storage medium
CN114408122A (en) * 2022-01-27 2022-04-29 大连海事大学 Ship anti-collision control system and design method thereof
CN118141619A (en) * 2024-05-09 2024-06-07 中国科学院苏州生物医学工程技术研究所 Wheelchair stepless speed regulation control method based on human body posture recognition, wheelchair and medium

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