U.S. patent application number 16/629251 was filed with the patent office on 2020-04-30 for a method and device for control of a mobility device.
This patent application is currently assigned to Nimbus Robotics, Inc.. The applicant listed for this patent is Nimbus Robotics, Inc.. Invention is credited to Anand Kapadia, Xunjie Zhang.
Application Number | 20200129843 16/629251 |
Document ID | / |
Family ID | 65001490 |
Filed Date | 2020-04-30 |
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United States Patent
Application |
20200129843 |
Kind Code |
A1 |
Zhang; Xunjie ; et
al. |
April 30, 2020 |
A Method and Device for Control of a Mobility Device
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.
Inventors: |
Zhang; Xunjie; (Pittsburgh,
PA) ; Kapadia; Anand; (Annandale, VA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Nimbus Robotics, Inc. |
Pittsburgh |
PA |
US |
|
|
Assignee: |
Nimbus Robotics, Inc.
Pittsburgh
PA
|
Family ID: |
65001490 |
Appl. No.: |
16/629251 |
Filed: |
July 9, 2018 |
PCT Filed: |
July 9, 2018 |
PCT NO: |
PCT/US18/41343 |
371 Date: |
January 7, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62530177 |
Jul 8, 2017 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B60L 2200/24 20130101;
A63C 2203/12 20130101; B60L 2240/42 20130101; A61H 1/02 20130101;
A61B 5/11 20130101; A61H 3/00 20130101; A61B 2562/0219 20130101;
A63C 2203/24 20130101; A63C 2203/18 20130101; A61B 5/112 20130101;
A63C 17/12 20130101; B60L 15/2009 20130101; A61B 5/7267
20130101 |
International
Class: |
A63C 17/12 20060101
A63C017/12; B60L 15/20 20060101 B60L015/20 |
Claims
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.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit under 35 U.S.C. .sctn.
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
[0002] Not applicable.
BACKGROUND OF THE INVENTION
[0003] 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.
[0004] 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
[0005] 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
[0006] FIG. 1 depicts a mobility device with an embedded
controller, according to one embodiment.
[0007] FIG. 2 is a block diagram of a control system according to
one embodiment.
[0008] FIG. 3 shows the steps of the method of control, utilizing
the controller depicted in FIG. 2.
DETAILED DESCRIPTION
[0009] 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.
[0010] 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.
[0011] 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.
[0012] 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.
[0013] 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.
[0014] 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.
[0015] 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.
[0016] 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.
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