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US20200129843A1 - A Method and Device for Control of a Mobility Device - Google Patents

A Method and Device for Control of a Mobility Device Download PDF

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Publication number
US20200129843A1
US20200129843A1 US16/629,251 US201816629251A US2020129843A1 US 20200129843 A1 US20200129843 A1 US 20200129843A1 US 201816629251 A US201816629251 A US 201816629251A US 2020129843 A1 US2020129843 A1 US 2020129843A1
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US
United States
Prior art keywords
motion command
gait
user
mobility device
data
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Abandoned
Application number
US16/629,251
Inventor
Xunjie Zhang
Anand Kapadia
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Shift Robotics Inc
Original Assignee
Nimbus Robotics Inc
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Publication date
Application filed by Nimbus Robotics Inc filed Critical Nimbus Robotics Inc
Priority to US16/629,251 priority Critical patent/US20200129843A1/en
Publication of US20200129843A1 publication Critical patent/US20200129843A1/en
Assigned to NIMBUS ROBOTICS, INC. reassignment NIMBUS ROBOTICS, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ZHANG, Xunjie
Assigned to NIMBUS ROBOTICS, INC. reassignment NIMBUS ROBOTICS, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: KAPADIA, Anand
Assigned to SHIFT ROBOTICS, INC. reassignment SHIFT ROBOTICS, INC. MERGER (SEE DOCUMENT FOR DETAILS). Assignors: NIMBUS ROBOTICS, INC.
Abandoned legal-status Critical Current

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    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63C—SKATES; SKIS; ROLLER SKATES; DESIGN OR LAYOUT OF COURTS, RINKS OR THE LIKE
    • A63C17/00—Roller skates; Skate-boards
    • A63C17/12—Roller skates; Skate-boards with driving mechanisms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/112—Gait analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A—HUMAN NECESSITIES
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    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
    • B60L15/2009—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed for braking
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/32—Control or regulation of multiple-unit electrically-propelled vehicles
    • B60L15/38—Control or regulation of multiple-unit electrically-propelled vehicles with automatic control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/082—Selecting or switching between different modes of propelling
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63C—SKATES; SKIS; ROLLER SKATES; DESIGN OR LAYOUT OF COURTS, RINKS OR THE LIKE
    • A63C2203/00—Special features of skates, skis, roller-skates, snowboards and courts
    • A63C2203/12—Electrically powered or heated
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63C—SKATES; SKIS; ROLLER SKATES; DESIGN OR LAYOUT OF COURTS, RINKS OR THE LIKE
    • A63C2203/00—Special features of skates, skis, roller-skates, snowboards and courts
    • A63C2203/18—Measuring a physical parameter, e.g. speed, distance
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63C—SKATES; SKIS; ROLLER SKATES; DESIGN OR LAYOUT OF COURTS, RINKS OR THE LIKE
    • A63C2203/00—Special features of skates, skis, roller-skates, snowboards and courts
    • A63C2203/24—Processing or storing data, e.g. with electronic chip
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2200/00—Type of vehicles
    • B60L2200/24—Personal mobility vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/42—Drive Train control parameters related to electric machines
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0014—Adaptive controllers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0062—Adapting control system settings
    • B60W2050/0063—Manual parameter input, manual setting means, manual initialising or calibrating means
    • B60W2050/0064—Manual parameter input, manual setting means, manual initialising or calibrating means using a remote, e.g. cordless, transmitter or receiver unit, e.g. remote keypad or mobile phone
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

Definitions

  • the invention relates to a mobility device. More specifically, the invention relates to a control system and method of controlling a mobility device having an electric motor that is worn on the feet of a user to provide mobility assistance.
  • Commuters and other travelers often have to walk the final leg of their trip, regardless of whether they traveled by car, bus, train, or other means. Depending on the distance, the time needed to complete this final leg of the journey can comprise a significant amount of the total duration of the trip. While bikes or scooters can be used, they are bulky and require skill and a minimum level of fitness to operate. Powered systems, such as moving walkways, suffer from a lack of mobility. Other mobility solutions suffer the same drawbacks or lack the ability to adapt to a particular user. Therefore, it would be advantageous to develop a control system for a mobility device that does not require any special skills or user training and can adapt to the individual needs of a particular user.
  • a sensor obtains data about the gait of a user and transmits the data to a processor.
  • the processor analyzes the gait of a user and then uses the gait data to develop motion commands for each mobility device.
  • the mobility device may comprise a motor, gearing, and wheels.
  • the mobility devices When worn on the feet of a user, the mobility devices allow a user to walk at an increased rate of speed for a given cadence and stride length, as compared to their speed without the mobility devices.
  • the control system adapts to a user so no learning or other control inputs are required by the user.
  • FIG. 1 depicts a mobility device with an embedded controller, according to one embodiment.
  • FIG. 2 is a block diagram of a control system according to one embodiment.
  • FIG. 3 shows the steps of the method of control, utilizing the controller depicted in FIG. 2 .
  • a mobility device 100 comprises a plurality of wheels 101 , with at least one of the wheels 101 connected to an electric motor 102 . Further shown in FIG. 1 is an onboard controller 111 and an optional remote controller 112 .
  • a user will wear two mobility devices 100 , one on each foot.
  • the mobility device 100 enables a pedestrian to walk faster than a normal walking pace by adding torque to the wheels 101 of the mobility device 100 worn on the foot in contact with the ground. In this manner, the user experiences an effect similar to that of walking on a moving walkway.
  • the control system 110 of the present invention enables a user to maintain a normal walking motion by adapting the control of the motor 102 to the movements of the user.
  • the speed at which the wheels 101 spin, through a torque applied by the motor 102 is controlled in part by an analysis of the user's gait.
  • FIG. 2 depicts the components of the onboard controller 111 , which comprises at least one inertial measurement unit 113 , a processor 114 , a motor driver 115 , and a wireless communication module 116 .
  • the control system 110 may also include a remote controller 112 , which is capable of sending commands to each of the onboard controllers 111 .
  • both the left and right mobility devices 100 receive command speeds from the remote controller 112 , which can be in the form of a hand-held controller, a computer, or a mobile phone, and actuate the mobility devices at the specified command speeds.
  • the control system 110 is used to collect data and analyze the gait of a user.
  • the onboard processor 114 reads gait dynamic data, comprising acceleration, gyroscopic data, and quaternion data of each mobility device 100 from the inertial measurement unit 113 .
  • both onboard controllers 111 send the gait dynamic data to the remote controller 112 and, in return, receive a motion command from the remote controller 112 .
  • the motion command comprises, for example, acceleration to a set speed, braking, deceleration to a set speed, and holding at a constant speed.
  • additional data can be included in the motion command.
  • the motion command may be generated by the onboard controllers 111 .
  • the onboard processor 114 Upon receiving the motion command, the onboard processor 114 along with the motor driver 115 converts the motion command into a motor driving signal and drives the motor system 102 , thereby affecting the speed of the wheels 101 .
  • the motor driver 115 receives a speed command and drives the motor 102 at the command speed via a feedback loop control.
  • the flow diagram shown in FIG. 3 depicts the method of gait-based motion control, according to one embodiment, comprising the steps of receiving gait dynamic data 301 , determining the user gait 302 , and determining the motion command 303 .
  • step 301 the remote controller receives gait dynamic data from both onboard controllers 111 .
  • the gait dynamic data includes data collected from the inertial measurement unit 113 .
  • step 302 the user gait is determined in step 302 by testing data through the machine learning model. More specifically, the remote controller receives the gait data and predicts the user's gait based on a trained model.
  • step 302 comprises feeding the gait dynamic data from a prior step into the beginning of a fixed size data buffer. When new data is received, the oldest data is discarded from the data buffer.
  • the size of the buffer can be sufficiently large to cover at least one full gait cycle of the gait dynamic data.
  • the data buffer is then fed into a pre-trained machine learning model to determine the user gait.
  • the machine learning model is a support vector machine.
  • alternative machine learning models can be used.
  • the machine learning model is trained based on the user performing various gaits on mobility devices 100 and signaling her current gait to the control system 110 via an input on the remote controller 112 .
  • the motion command is generated based on the determined gait.
  • the remote controller 112 checks if any user input has been registered.
  • the user input can be in various forms such as pressing a button or moving the remote controller 112 in a certain trajectory.
  • the user input may press a button indicating that the user wants forward motion.
  • the forward motion command received from the user can override the motion command provided by the controller 112 based on the machine learning model.
  • a motion command is generated and sent by the remote controller 112 to both onboard controllers 111 .
  • the final motion command is replaced with the user input before being sent to the onboard controllers 111 .
  • each onboard controller 111 generates a motion command and sends the motion command signal to the other controller 111 for cross-validation in step 305 .
  • the motion command may include acceleration to a set speed, braking, deceleration to a set speed, and holding at a constant speed.
  • the processor 114 along with the motor driver 115 convert the motion command into a motor driving signal and drive the motor system.
  • cross validation compares the motion commands generated for each of the two mobility devices 100 . For example, the motor driver 115 will only command motor speed when both commands are similar and will brake when the speed commands are inconsistent.

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Abstract

A system for control of a mobility device comprising a controller for analyzing data from at least one sensor on the mobility device, wherein the data is used to determine the gait of user. The gait data is then used to provide motion command to an electric motor on the mobility device.

Description

    CROSS-REFERENCE TO RELATED APPLICATIONS
  • This application claims the benefit under 35 U.S.C. § 119 of U.S. Provisional Application No. 62/530,177, filed Jul. 8, 2017, which is incorporated herein by reference.
    • STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH
  • Not applicable.
    • BACKGROUND OF THE INVENTION
  • The invention relates to a mobility device. More specifically, the invention relates to a control system and method of controlling a mobility device having an electric motor that is worn on the feet of a user to provide mobility assistance.
  • Commuters and other travelers often have to walk the final leg of their trip, regardless of whether they traveled by car, bus, train, or other means. Depending on the distance, the time needed to complete this final leg of the journey can comprise a significant amount of the total duration of the trip. While bikes or scooters can be used, they are bulky and require skill and a minimum level of fitness to operate. Powered systems, such as moving walkways, suffer from a lack of mobility. Other mobility solutions suffer the same drawbacks or lack the ability to adapt to a particular user. Therefore, it would be advantageous to develop a control system for a mobility device that does not require any special skills or user training and can adapt to the individual needs of a particular user.
    • BRIEF SUMMARY
  • According to embodiments of the present invention is system and method of controlling a mobility device, wherein the mobility device is worn on each foot of a user. A sensor obtains data about the gait of a user and transmits the data to a processor. The processor analyzes the gait of a user and then uses the gait data to develop motion commands for each mobility device. The mobility device may comprise a motor, gearing, and wheels. When worn on the feet of a user, the mobility devices allow a user to walk at an increased rate of speed for a given cadence and stride length, as compared to their speed without the mobility devices. Further, the control system adapts to a user so no learning or other control inputs are required by the user.
    • BRIEF SUMMARY OF THE SEVERAL VIEWS OF THE DRAWINGS
  • FIG. 1 depicts a mobility device with an embedded controller, according to one embodiment.
  • FIG. 2 is a block diagram of a control system according to one embodiment.
  • FIG. 3 shows the steps of the method of control, utilizing the controller depicted in FIG. 2.
    •  DETAILED DESCRIPTION
  • As shown in FIG. 1, a mobility device 100, according to one embodiment, comprises a plurality of wheels 101, with at least one of the wheels 101 connected to an electric motor 102. Further shown in FIG. 1 is an onboard controller 111 and an optional remote controller 112. During typical use, a user will wear two mobility devices 100, one on each foot. The mobility device 100 enables a pedestrian to walk faster than a normal walking pace by adding torque to the wheels 101 of the mobility device 100 worn on the foot in contact with the ground. In this manner, the user experiences an effect similar to that of walking on a moving walkway. More specifically, the control system 110 of the present invention enables a user to maintain a normal walking motion by adapting the control of the motor 102 to the movements of the user. As will be discussed in greater detail, the speed at which the wheels 101 spin, through a torque applied by the motor 102, is controlled in part by an analysis of the user's gait.
  • FIG. 2 depicts the components of the onboard controller 111, which comprises at least one inertial measurement unit 113, a processor 114, a motor driver 115, and a wireless communication module 116. Two onboard controllers 111 are shown in FIG. 2 since each mobility device (i.e. one for each foot of the user) will house an onboard controller 111. In an alternative embodiment, the control system 110 may also include a remote controller 112, which is capable of sending commands to each of the onboard controllers 111. In this particular embodiment, both the left and right mobility devices 100 receive command speeds from the remote controller 112, which can be in the form of a hand-held controller, a computer, or a mobile phone, and actuate the mobility devices at the specified command speeds.
  • The control system 110 is used to collect data and analyze the gait of a user. For example, the onboard processor 114 reads gait dynamic data, comprising acceleration, gyroscopic data, and quaternion data of each mobility device 100 from the inertial measurement unit 113. In one embodiment, both onboard controllers 111 send the gait dynamic data to the remote controller 112 and, in return, receive a motion command from the remote controller 112. The motion command comprises, for example, acceleration to a set speed, braking, deceleration to a set speed, and holding at a constant speed. In alternative embodiments, additional data can be included in the motion command. Alternatively, the motion command may be generated by the onboard controllers 111. Upon receiving the motion command, the onboard processor 114 along with the motor driver 115 converts the motion command into a motor driving signal and drives the motor system 102, thereby affecting the speed of the wheels 101. In one embodiment, the motor driver 115 receives a speed command and drives the motor 102 at the command speed via a feedback loop control.
  • The flow diagram shown in FIG. 3 depicts the method of gait-based motion control, according to one embodiment, comprising the steps of receiving gait dynamic data 301, determining the user gait 302, and determining the motion command 303.
  • In step 301, the remote controller receives gait dynamic data from both onboard controllers 111. The gait dynamic data includes data collected from the inertial measurement unit 113. Next, at step 302, the user gait is determined in step 302 by testing data through the machine learning model. More specifically, the remote controller receives the gait data and predicts the user's gait based on a trained model. In one embodiment, step 302 comprises feeding the gait dynamic data from a prior step into the beginning of a fixed size data buffer. When new data is received, the oldest data is discarded from the data buffer. The size of the buffer can be sufficiently large to cover at least one full gait cycle of the gait dynamic data. The data buffer is then fed into a pre-trained machine learning model to determine the user gait. According to one example embodiment, the machine learning model is a support vector machine. However, alternative machine learning models can be used. The machine learning model is trained based on the user performing various gaits on mobility devices 100 and signaling her current gait to the control system 110 via an input on the remote controller 112. At step 303, the motion command is generated based on the determined gait.
  • However, in optional step 304, the remote controller 112 checks if any user input has been registered. The user input can be in various forms such as pressing a button or moving the remote controller 112 in a certain trajectory. For example, the user input may press a button indicating that the user wants forward motion. Thus, the forward motion command received from the user can override the motion command provided by the controller 112 based on the machine learning model. After checking for a user input at step 304, a motion command is generated and sent by the remote controller 112 to both onboard controllers 111. However, if the user input is received from step 304, the final motion command is replaced with the user input before being sent to the onboard controllers 111.
  • In an alternative embodiment, each onboard controller 111 generates a motion command and sends the motion command signal to the other controller 111 for cross-validation in step 305. The motion command may include acceleration to a set speed, braking, deceleration to a set speed, and holding at a constant speed. Upon validating the motion command, the processor 114 along with the motor driver 115 convert the motion command into a motor driving signal and drive the motor system. Stated differently, in step 305, cross validation compares the motion commands generated for each of the two mobility devices 100. For example, the motor driver 115 will only command motor speed when both commands are similar and will brake when the speed commands are inconsistent.
  • While the disclosure has been described in detail and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes and modification can be made therein without departing from the spirit and scope of the embodiments. Thus, it is intended that the present disclosure cover the modifications and variations of this disclosure provided they come within the scope of the appended claims and their equivalents.

Claims (8)

What is claimed is:
1. A method of controlling a mobility device having an electric motor, the system comprising:
receiving gait data from at least one inertial measurement unit,
determining the gait of a user based on the gait data and a pre-configured machine learning model; and
generating a motion command using the determined gait.
2. The method of claim 1, wherein the gait data is selected from the group consisting of acceleration, gyroscopic data, and quaternion data.
3. The method of claim 1, wherein determining the gait of a user comprises testing the gait of a user through a machine learning model.
4. The method of claim 3, further comprising:
training the machine learning model by having a user perform various gaits on the mobility device and signaling the various gaits to a control system.
5. The method of claim 1, further comprising cross validating the motion command between two mobility devices worn by a user.
6. The method of claim 5, wherein the step of cross validating the motion command comprises:
converting the motion command into a motor driving signal if the motion command of a first mobility device is similar to a motion command of a second mobility device.
7. The method of claim 5, wherein the step of cross validating the motion command comprises:
converting the motion command into a braking signal if the motion command of a first mobility device is not similar to a motion command of a second mobility device.
8. The method of claim 1, further comprising:
checking for user input from a remote controller, and
overriding the motion command based on the user input.
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