This application also claims priority to Taiwan Patent Application No. 104139717 filed in the Taiwan Patent Office on Nov. 27, 2015, the entire content of which is incorporated herein by reference.
The present disclosure relates to a method for estimating posture of a robotic walking aid, and more particularly, to a method for estimating posture of a robotic walking aid for further use in remote service.
Considering the global trend of aging population and low fertility rate, many countries had already suffered a serious shortage of manpower, and thus had to postpone their statutory retirement age. For overcoming such manpower shortage, many developed countries have invested many resources into the development and integration of robotic technology and information-and-communication technology (ICT) for producing industrial robots to be used in many automation applications, such as a robotic walking aid which is especially being commonly configured in a form of exoskeleton robot system. It is noted that a good robotic walking aid not only can have reducing the working load of manual labor, but also can be used for providing quality assurance of long-term care and walking assistance to the elderly. By enabling a robotic walking aid to detect the body movement of a user, the robotic walking aid is able to provide power to assist the body movement, so that the overall power supporting the body movement of the user is increased, and in some extreme case, the robotic walking aid can even help a paralyzed user to stand up. Nowadays, the most commercially successful and commonly used robotic walking aid is the lower-limb exoskeleton robot, such as the Rewalk™ by Argo Medical Technologies in Israel, the Ekso™ by Ekso Biobics in U.S.A., the HAL by Cyberdyne in Japan, the ITRI-EXO by ITEI in Taiwan, and the Stride Management Assist Device by Honda in Japan. Generally, with the help of a walking stick or other waling aids, a robotic walking aid can help a user to accomplish many ritual activities in his/her daily life, such as getting up, sitting down, walking uphill and downhill, and walking upstairs and downstairs. Since such robotic waling aids are designed for people with difficulties in mobility and for elderly people, safety concern in usage is the most important issue and that is also the essential part of study in the development of robotic walking aid that is lack of technological support.
In one prior art, there is already a safety mechanism available for determining when the user is in a safe position from which to take a step. Operationally, posture information of a user is obtained using measurements of angular orientation with respect to gravity provided by an inertial measurement unit that is mounted on a shank of the user, and pressure center of the user is calculated and obtained using a pressure sensor that is arranged at the sole of a foot, and then the posture information and the calculated pressure center are used in a calculation for determining whether the user is in a safe position from which to take a step. In another prior art, there is another safety mechanism for determining when the user is in a safe position from which to take a step, in which measurements of angular orientation with respect to gravity are provided by the use of some angular sensors that are affixed to the trunk of a user while the angular orientation measurements are used for determining whether the user is in a safe position from which to take a step.
Nevertheless, in prior arts or other disclosed research documentations, there is no applications employing aforesaid information in remote service, which may include topography feedback, danger prompting, falling alert and distress call, exercise amount estimation, walking distance estimation, behavior monitoring, activity record, rehabilitation feedback, and so on.
Therefore, the robotic walking aids in prior arts still have many imperfections.
In one embodiment, the present disclosure provides a method for estimating posture of a robotic walking aid, which comprises the steps of:
Further scope of applicability of the present application will become more apparent from the detailed description given hereinafter. However, it should be understood that the detailed description and specific examples, while indicating exemplary embodiments of the disclosure, are given by way of illustration only, since various changes and modifications within the spirit and scope of the disclosure will become apparent to those skilled in the art from this detailed description.
The present disclosure will become more fully understood from the detailed description given herein below and the accompanying drawings which are given by way of illustration only, and thus are not limitative of the present disclosure and wherein:
In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the disclosed embodiments. It will be apparent, however, that one or more embodiments may be practiced without these specific details. In other instances, well-known structures and devices are schematically shown in order to simplify the drawing. Please refer to
Please refer to
In this embodiment, at each of the right and left hip joints, and the right and left knee joints of a robotic walking aid 1, there are a motor controller 50, a motor encoder 71 and a motor 70 to be mounted respectively thereat; and there is an inertial sensor 60 to be mounted on the upper body 40 of the robotic walking aid 1, whereas the motor controllers 50, the motor encoders 71, the motors 70 and the inertial sensor 60 are coupled to a control unit 80. Thereby, by the use of a cloud computing means 130, the robotic walking aid 1 is able to connect to a mobile communication device 90 via the control unit 80. It is noted that the mobile communication device 90 can be a smart phone, a tablet computer or a smart watch, whichever is built with GPS function. Therefore, the mobile communication device 90 is able to for provide the GPS coordinates of the user with the robotic walking aid installed on so as to be used in an activity motoring, and moreover, while working cooperatively with the inertial sensor 60, the mobile communication device 90 can provide indoor positioning information for monitoring any user wearing the mobile communication device 90. In addition, the control unit 80 is further connected to a database 120 for allowing information to be transmitted between the control unit 80, the mobile communication device 90 and the database 90 via the cloud computing means 130 for future used in remote service, and the remote service can include a topography feedback process, a danger prompting process, a falling alert and distress call process, an exercise amount estimation process, a walking distance estimation process, a behavior monitoring process, an activity record process, and a rehabilitation feedback process. The robotic walking aid 1 is designed to be worn by a user for helping the user to walk. Moreover, there can be a power source for providing power to the robotic walking aid 1.
Although the control unit 80 is connected to the robotic walking aid 1 in a wireless manner in this embodiment, it can be connected to the robotic walking aid 1 in a wired manner, or in another embodiment, the control unit 80 can be installed directly on the robotic walking aid 1.
The inertial sensor 60 can be the composition of an accelerometer, a gyroscope, a magnetometer, and an angle gauge, whichever can perform a posture estimation algorithm for estimating upper body posture of a user, estimating walking steps of a user and for indoor positioning, and so on. In an embodiment, the inertial sensor 60 is a 9-degree-of-freedom inertial measurement unit (9D IMU), which is generally an assembly including a three-axis accelerometer, a gyroscope and a magnetometer, and is used for estimating an inertial motion of an object, or for calculating a transformation matrix for the coordinate of the inertial sensor corresponding to a reference coordinate system. The accelerometer is a device that will measure acceleration forces, whereas these forces may be static, like the constant force of gravity, or they could be dynamic, caused by moving or vibrating the accelerometer. The gyroscope is a device capable of measuring the angular rate of an object, and while working cooperatively with an accelerometer, the gyroscope can measure moment of inertial that is not detectable by the accelerometer, so that the dimension of detection as well as the system frequency are enhanced. The magnetometer is a device capable of direction of the magnetic field at a point in space, and can be used as an electronic compass that can work cooperatively with an accelerometer and a gyroscope for estimating a yaw angle of an object.
Please refer to
In the following description, the step 114 of
Consequently, Rr1 is substantially a transformation matrix for the transformation from sub-coordinate frame 1 to the reference frame; R12 is substantially a transformation matrix for the transformation from the sub-coordinate frame 2 to the sub-coordinate frame 1, R23 is substantially a transformation matrix for the transformation from the sub-coordinate frame 3 to the sub-coordinate frame 2, R34 is substantially a transformation matrix for the transformation from the sub-coordinate frame 4 to the sub-coordinate frame 3, R45 is substantially a transformation matrix for the transformation from the sub-coordinate frame 5 to the sub-coordinate frame 4, R16 is substantially a transformation matrix for the transformation from the sub-coordinate frame 6 to the sub-coordinate frame 1, R67 is substantially a transformation matrix for the transformation from the sub-coordinate frame 7 to the sub-coordinate frame 6, R78 is substantially a transformation matrix for the transformation from the sub-coordinate frame 8 to the sub-coordinate frame 7, and R89 is substantially a transformation matrix for the transformation from the sub-coordinate frame 9 to the sub-coordinate frame 8.
For instance, for obtaining the transformation relationship of the third end point P3 corresponding to the reference frame, it can be obtained using the following formula:
p
3
=R
r1
·R
12
·R
23·[0 0 0 1]T;
and similarly, the other end points can be obtained in the following formulas:
p
b
=R
r1
·[0 H
body 0 1]T p1=Rr1·[0 0 0 1]T
p
2
=R
r1
·R
12·[0 0 0 1]T
p
4
=R
r1
·R
12
·R
23
·R
34·[0 0 0 1]T
p
5
=R
r1
·R
12
·R
23
·R
34
·R
45
·[0001]hu T
p
6
=R
r1
·R
16·[0 0 0 1]T p7=Rr1·R16·R67·[0 0 0 1]T
p
8
=R
r1
·R
16
·R
67
·R
78·[0 0 0 1]T
p
9
=R
r1
·R
16
·R
67
·R
78
·R
89·[0 0 0 1]T
Therefore, as shown in
Moreover, a base of support B can be constructed by projecting a plane formed by the connection of the fourth end point P4, the fifth end point P5, the eighth end point P8, and the ninth end point P9. Thereafter, the mass center of the user wearing the robotic walking aid 1 can be calculated. First, the center coordinates of those links are obtained using the following formulas:
Then, after obtaining the ratio of each linkage rate corresponding to the overall weight of the user by the use of the Dempster's coefficient, the spatial coordinate corresponding to the center of gravity of the robotic walking aid can be obtained as following:
Consequently, the center of gravity is projected to the base of support B for obtaining the required spatial relationship.
In addition, after the angular orientation of the user with respect to gravity is detected and provided by the inertial sensor 60, the motion model can be modified accordingly and then to be used in mapping marks via the GPS positioning function of the mobile communication device 90 for next user.
Accordingly, after the using of the motion model to calculate a spatial coordinate for each end point is performed, as disclosed in
The steps performed in
In
In the topography feedback process, the GPS coordinates of the user is matched to a map, e.g. Google map, for identifying terrains of specific topographic marks, and when a user approaches any of those specific topographic marks, a remote prompting is issued for suggesting the user to alter his/her walking mode for adapting to the terrain of the approached topographic mark.
In the danger prompting process, the GPS coordinates of the user is matched to a map, e.g. Google map, for identifying dangerous locations, and when a user approaches any of those dangerous locations, a remote prompting is issued for alerting the user to cope with the coming danger.
In the falling alert and distress call process, the posture of the user is obtained using the angles relating to the upper body and the aforesaid joints of the robotic walking aid, and when the posture is determined to be abnormal, a call is made to find out the condition of the user, and if there is no response from the user, an active distress call is issued to an emergency medical unit that is located nearest to the user according to the GPS coordinates of the user.
In the exercise amount estimation process, an exercise amount is calculated and obtained using the flowing formula:
(mr+mh)×g×d=Wr+Wh;
wherein mr is the mass of the robotic walking aid;
It is noted that the masses of the robotic walking aid 1 and the user can be obtained by any common weight measurement device, and the walking distance can be estimated and obtained according to the information detected by the inertial sensor 60 relating to the amount of walking steps of the robotic walking aid 1. In addition, the mechanical energy consumed by the robotic walking aid 1 can be estimated according to the battery residual capacity. However, the energy conversion efficiency for converting electrical energy into mechanical energy must be identified first, and then mechanical energy consumed by the robotic walking aid 1 can be estimated according to the battery residual capacity accordingly. After obtaining the mechanical energy consumed by the robotic walking aid 1, the physiological cost of the user can be calculated by the use of the aforesaid formula. Therefore, in this embodiment, the energy conversion efficiency for converting electrical energy into mechanical energy is identified as following:
Wr=Wmechanical=ηWelectrical;
Moreover, the exercise amount can be estimated by the use of a vision-based motion analysis system, such as the VICON motion analysis system that is operated cooperatively with a force plate. During the estimation of the exercise amount, the overall energy consumed in the movement, including the kinetic energy and potential energy, is calculated, and a physiological cost measurement is performed by the use of a oxygen consumption measurement device, such as Cosmed K2, and thereby, an energy conversion efficiency database for the robotic walking aid under various walking conditions can be established so as to be used in the exercise amount calculation. Thus, the exercise amount can be obtained using the following formula:
W
h=(mr+mh)×g×d−ηWelectrical
In the walking distance estimation process, a posture of the user is obtained remotely using the angles relating to the upper body and the aforesaid joints of the robotic walking aid and a step length of the user is estimated so as to be used for estimating and recording the walking distance.
In the behavior monitoring process, postures of the user are obtained remotely using the angles relating to the upper body and the aforesaid joints of the robotic walking aid, and the postures of the user are classified into different behaviors according to a classification rule to be recorded.
In the activity record process, the GPS coordinates of the user are matched to a map, e.g. Google map, for identifying and recording places where the user perform his/her daily activities.
In the rehabilitation feedback process, the postures, step length, step frequency, and exercise amount are recorded and provided remotely to a rehabilitation therapist for constructing a rehabilitation treatment accordingly.
To sum up, the present disclosure provides a method for estimating posture of a robotic walking aid, using which a safety control and instant posture adjustment mechanism for the robotic walking aid are enabled via the cooperation between inertial sensor and motor encoders; an indoor and outdoor GPS positioning can be achieved via the communication between the inertial sensors and a mobile communication device, while allowing the result of the GPS positioning to be provided to an remote service center for monitoring and behavior analysis. Consequently, the remote service center can decide whether to provide an remote service operation accordingly, and the remote service operation includes a topography feedback process, a danger prompting process, a falling alert and distress call process, an exercise amount estimation process, a walking distance estimation process, a behavior monitoring process, an activity record process, and a rehabilitation feedback process.
With respect to the above description then, it is to be realized that the optimum dimensional relationships for the parts of the disclosure, to include variations in size, materials, shape, form, function and manner of operation, assembly and use, are deemed readily apparent and obvious to one skilled in the art, and all equivalent relationships to those illustrated in the drawings and described in the specification are intended to be encompassed by the present disclosure.
| Number | Date | Country | Kind |
|---|---|---|---|
| 104139717 | Nov 2015 | TW | national |