Patent Application
20210354285
Embodiments of the present disclosure generally relate to calibration of three-dimensional position information between two fixed-base robotic arms. In particular, the present disclosure describes a mechanical coupling that allows the arms of two fixed-base robotic arms to be calibrated and methods for calibrating two fixed base robotic arms after coupling the two arms together.
According to embodiments of the present disclosure, systems for, methods for, and computer program products for calibration of two fixed-base robotic arms are provided. In various embodiments, a system includes a first robotic arm having a proximal end and a distal end. The proximal end of the first robotic arm is fixed to a first base. The system further includes a second robotic arm having a proximal end and a distal end. The proximal end of the second robotic arm is fixed to a second base. A first coupling is disposed at the distal end of the first robotic arm. The first coupling has a first flange and a protrusion extending from the flange. A second coupling is disposed at the distal end of the second robotic arm, the second coupling having a second flange and a recess in the second flange having a shape corresponding to a shape of the protrusion. A locking mechanism releasably couples the first flange and the second flange together such that the distal end of the first robotic arm and the distal end of the second robotic arm move together. The first robotic arm and second robotic are configured to be calibrated to one another when the first coupling is coupled to the second coupling by collecting positional data in at least a first and a second coupled position and determining therefrom a calibration value.
In various embodiments, the locking mechanism includes a collar. In various embodiments, the locking mechanism includes a fastener. In various embodiments, the protrusion has rotational symmetry about an axis normal to the first flange. In various embodiments, a shape of the protrusion is selected from the group consisting of: square, rectangle, triangle, and circle. In various embodiments, the protrusion has rotational asymmetry about an axis normal to the first flange. In various embodiments, the recess has rotational symmetry about an axis normal to the second flange. In various embodiments, a shape of the recess is selected from the group consisting of: square, rectangle, triangle, and circle. In various embodiments, the recess has rotational asymmetry about an axis normal to the second flange. In various embodiments, the second flange includes two or more recesses. In various embodiments, the first flange includes two or more protrusions.
In various embodiments, a method for calibrating two robotic arms includes providing a first robotic arm having a proximal end and a distal end and a second robotic arm having a proximal end and a distal end. The proximal end of the first robotic arm is fixed to a first base and the proximal end of the second robotic arm is fixed to a second base. The distal end of the first robotic arm is releasably coupled to the distal end of the second robotic arm via a coupling at a first coupled position. First positional data for the distal end of the first robotic arm is collected at the first coupled position. Second positional data for the distal end of the second robotic arm is collected at the first coupled position. A calibration value based at least on the first positional data and the second positional data is determined. In various embodiments, the calibration value may be a calibration matrix determined by a least mean squares method.
In various embodiments, after collecting the first positional data and the second positional data, the first and second robotic arms are moved to a second coupled position, third positional data is collected for the distal end of the first robotic arm while in the second coupled position, fourth positional data is collected for the distal end of the second robotic arm while in the second coupled position, and the calibration value is determined using the third and fourth positional data.
In various embodiments, after collecting the first positional data and the second positional data, the distal ends of the first and second robotic arms are moved to a second coupled position, third positional data is collected for the distal end of the first robotic arm while in the second coupled position, fourth positional data is collected for the distal end of the second robotic arm while in the second coupled position, and the calibration value is applied to each of the third and fourth positional data.
In various embodiments, the calibration value includes a calibration matrix. In various embodiments, the calibration matrix is determined by a least mean squares method. In various embodiments, the calibration matrix is determined by a least squares method. In various embodiments, the calibration matrix is determined by a Kalman filter. In various embodiments, the first robotic arm and the second robotic arm are configured to perform a medical procedure. In various embodiments, the medical procedure is a gastric bypass surgery. In various embodiments, the first positional data and the second positional data each includes three-dimensional data. In various embodiments, collecting first positional data and collecting second positional data each includes continuous recording of data.
In various embodiments, a computer program product is provided for calibrating two fixed-base robotic arms. The computer program product includes a computer readable storage medium having program instructions embodied therewith and the program instructions are executable by a processor to cause the processor to perform a method including collecting first positional data from a distal end of a first robotic arm releasably coupled to a distal end of a second robotic arm at a first coupled position. Second positional data is collected from the distal end of the second robotic arm at the first coupled position. A calibration value based at least on the first positional value and the second positional value is determined. In various embodiments, the calibration value may be a calibration matrix determined by a least mean squares method.
In various embodiments, after collecting the first positional data and the second positional data, the first and second robotic arms are moved to a second coupled position, third positional data is collected for the distal end of the first robotic arm while in the second coupled position, fourth positional data is collected for the distal end of the second robotic arm while in the second coupled position, and the calibration value is determined using the third and fourth positional data.
In various embodiments, after collecting the first positional data and the second positional data, the distal ends of the first and second robotic arms are moved to a second coupled position, third positional data is collected for the distal end of the first robotic arm while in the second coupled position, fourth positional data is collected for the distal end of the second robotic arm while in the second coupled position, and the calibration value is applied to each of the third and fourth positional data.
In various embodiments, the calibration value includes a calibration matrix. In various embodiments, the calibration matrix is determined by a least mean squares method. In various embodiments, the calibration matrix is determined by a least squares method. In various embodiments, the calibration matrix is determined by a Kalman filter. In various embodiments, the first robotic arm and the second robotic arm are configured to perform a medical procedure. In various embodiments, the medical procedure is a gastric bypass surgery. In various embodiments, the first positional data and the second positional data each includes three-dimensional data. In various embodiments, collecting first positional data and collecting second positional data each includes continuous recording of data.
Many surgical maneuvers (e.g., suturing, cutting, and/or folding) require highly dexterous and highly accurate motion of surgical tools to achieve a satisfactory surgical outcome. These surgical maneuvers may require more than one robotic arm to adequately perform the particular maneuver, for example, where one robotic arm holds a tissue while the other robotic arm sutures or cuts the tissue. In fully automated robotic surgical procedures using two or more robots that are cooperating to perform a surgical maneuver, each of the robots may operate within the same three-dimensional coordinate system to provide accurate collaborative motions (e.g., hand-offs) and collision prevention/detection between the robots. A calibration map may be provided to enable the robots to operate within the same coordinate system, thereby enabling the robots to work together.
In various embodiments, one option for calibrating two or more robots in a robotic system involves placing each of the robots in predetermined locations having known coordinates in a 3-dimensional coordinate system. In various embodiments, program code for each robot is adjusted prior to using the robotic system to account for any movement within the operative field. However, this method is not completely accurate as knowledge of robot position may not be absolute. For example, any error in the placement of the robots may result in a suboptimal calibration, which may cause imprecise motion of the robots and/or collision between robots. In fields where room for error is very small, such as in robotic-assisted surgery, each collaborative robot must be accurately and precisely calibrated to minimize the risk of adverse events.
Accordingly, a need exists for a system and method to calibrate two or more fixed-based robotic arms thereby enabling accurate surgical maneuvers and cooperation between the two or more robotic arms to improve robotic-assisted surgery.
Embodiments of the present disclosure generally relate to calibration of three-dimensional position information between two fixed-base robotic arms. In particular, the present disclosure describes a mechanical coupling that allows the arms of two fixed-base robotic arms to be calibrated and methods for calibrating two fixed base robotic arms after coupling the two arms together. While the present disclosure generally focuses on calibrating the three-dimensional position with respect to two or more automated surgical robots, the systems, methods, and computer program products are suitable for use in other fields that employ collaborative robots, such as manufacturing, consumer robotics, or other autonomous robots.
The two or more robotic arms may perform a surgical maneuver or other collaborative maneuver. In various embodiments, the collaborative maneuver may be a hand-off In various embodiments, a hand-off may involve transferring an object being held by a first robotic arm to a second robotic arm, thus freeing up the first robotic arm to perform other functions. In various embodiments, the collaborative maneuver may involve any suitable biological tissue. For example, the biological tissue may be an internal bodily tissue, such as esophageal tissue, stomach tissue, small/large intestinal tissue, and/or muscular tissue. In other embodiments, the object may be external tissue, such as dermal tissue on the abdomen, back, arm, leg, or any other external body part. Moreover, the biological tissue may be a bone, internal organ, or other internal bodily structure. The systems and methods of the present disclosure would similarly work for animals in veterinary applications.
A system for calibrating two fixed-base robotic arms may include a first robotic arm having a proximal end and a distal end and a second robotic arm having a proximal end and a distal end. The proximal end of the first robotic arm is fixed to a first base and the proximal end of the second robotic arm is fixed to a second base. A first coupling may be disposed at the distal end of the first robotic arm and a second coupling may be disposed at the distal end of the second robotic arm. The first coupling may have a first flange and one or more protrusion and the second coupling may have a second flange and a recess in the second flange having a shape corresponding to a shape of the protrusion of the first coupling. A locking mechanism may releasably couple the first flange and the second flange. In various embodiments, the locking mechanism may be a collar or clamp. In various embodiments, the locking mechanism may include a wingnut screw.
In various embodiments, the protrusion may include any suitable shape for engaging with the recess as is known in the art. For example, the protrusion may include a taper where the protrusion tapers from a wider diameter to a narrower diameter. In this example, the recess may include a corresponding taper such that the tapered protrusion may matingly engage the recess. In various embodiments, more than one protrusion may be provided on the first coupling. In various embodiments, more than one recess may be provided on the second coupling. In various embodiments, the protrusion(s) and recess(es) may be arranged such that relative motion between the distal ends of the robotic arms is prevented when the protrusion(s) matingly engages the corresponding recess(es).
In various embodiments, a method for calibrating two robotic arms includes providing a first robotic arm and a second robotic arm. Each robotic arm is fixed to a base (which may be the same base or different bases) at their respective proximal-most end. A first coupling is affixed to a distal-most end of the first robotic arm and a second coupling is affixed to a distal-most end of the second robotic arm. In various embodiments, the first coupling and the second coupling may be similar to the couplings described in more detail above and below.
In various embodiments, first position data may be collected for the distal end of the first robotic arm. In various embodiments, second positional data may be collected for the distal end of the second robotic arm. In various embodiments, the first and second positional data may be collected continuously. In various embodiments, the first and second positional data may be collected by manually moving the first and second robotic arms while they are coupled together. Positional data/information, as used herein, may generally be defined as (X, Y, Z) in a three-dimensional coordinate system. In various embodiments, collecting more positional data will provide more accurate calibration map for the two or more robotic arms.
When the first and second robotic arms are coupled together via the first and second couplings, the distal ends of each robotic are may be a predetermined, fixed distance away from one another. The positional information of the distal ends of each robotic arm and the fixed distance between the two distal ends may be used to generate a calibration value so that the two robotic arms may work together on a task, for example, suturing or cutting tissue. In various embodiments, once the calibration value is determined, the calibration value may be applied to all future positional information that is collected from the first and second robotic arms.
In various embodiments, the calibration value may be a calibration matrix. In various embodiments, the calibration matrix may be determined via a least mean squares (LMS) algorithm. LMS is a method in the family of stochastic gradient methods where statistics are estimated continuously. Since statistics are estimated continuously, the LMS algorithm can adapt to changes in the signal statistics and thus is an adaptive filter. In general, LMS minimizes E{|e(n)|2} similar to steepest descent, but based on unknown statistics. In various embodiments, the LMS algorithm uses estimates of the autocorrelation matrix R and the cross-correlation vector p. If instantaneous estimates are chosen, then the resulting method is the LMS algorithm shown in Equations 1a, 1b:
{circumflex over (R)}(n)=u(n)uH(n) (Eqn. 1a)
{circumflex over (p)}(n)=u(n)d*(n) (Eqn. 1b)
In various embodiments, the calibration matrix may be determined via a least squares algorithm. In this method, a least squares solution to A=
is an actual solution to A
=
∥. The least squares algorithm minimizes |
−A
|2=Σ(
−A
)i2. Equation 2a-2c shows the equation to solve for the least square solution:
A
=
∥=−
(Eqn. 2a)
A
T
A
=A
T
−A
T
(Eqn. 2b)
A
T
A
=A
T
(Eqn. 2c)
For example, a matrix A of positional data for the first robotic arm may be related to a matrix B of positional data for the second robotic arm by the following equation:
[A][H]=[B] (Eqn. 3a)
In Equations 3a-3c, A represents a matrix of three-dimensional positional data of the first robotic arm, H represents the calibration matrix, and B represents a matrix of three-dimensional positional data of the second robotic arm. The first row of matrix A may correspond to a first three-dimensional positional data point for the first robotic arm and the first row of matrix B may correspond to a first three-dimensional data point for the second robotic arm at the same sampling time. Each additional row in each matrix A, B may be an additional three-dimensional positional data point at another sampling time. To find the calibration matrix H,
[A]T[A][H]=[A]T[B] (Eqn. 3b)
[H]=([A]T[A])−1([A]T[B]) (Eqn. 3c)
In various embodiments, a Kalman filter may be used to determine the calibration matrix.
Various embodiments may be adapted for use in gastrointestinal (GI) catheters, such as an endoscope. In particular, the endoscope may include an atomized sprayer, an IR source, a camera system and optics, a robotic arm, and an image processor.
In various embodiments, after the first coupling 102 is locked to the second coupling 104, three-dimensional coordinate information may be recorded for each robotic arm while the robotic arms are stationary. In various embodiments, after the first coupling 102 is locked to the second coupling 104, the two couplings 102, 104 may be moved (e.g., manually by a user) together through three-dimensional space and three-dimensional coordinate information may be recorded for each robotic arm during the motion.
In various embodiments, a fastener as described above may be any suitable device or mechanism that is configured to hold the locking mechanism against the two couplings during calibration. In various embodiments, the fastener may include, for example, a screw, clamp, magnet, clasp, clip, pin, tie, wire, etc.
In various embodiments, once the distal ends of each of the first and second robotic arms 301a, 301b are coupled together at a first coupled position, positional data may be recorded for the distal end of each robotic arm 301a, 301b (e.g., first positional data corresponding to the distal end of the first robotic arm and second positional data corresponding to the distal end of the second robotic arm). In various embodiments, a calibration value (e.g., calibration matrix) may be computed from this positional data. In various embodiments, the coupled robotic arms 301a, 301b may be moved in three-dimensional space to a second coupled position (e.g., a coupled position different from the first coupled position). In various embodiments, additional positional data may be recorded for each of the distal ends of the robotic arms 301a, 301b once the robotic arms 301a, 301b are in the second coupled position (e.g., third positional data corresponding to the distal end of the first robotic arm and fourth positional data corresponding to the distal end of the second robotic arm). In various embodiments, a calibration value (e.g., calibration matrix) may be computed from the recorded positional data at the second and/or first coupled position. In various embodiments, the coupled robotic arms 301a, 301b may be moved in three-dimensional space to a third coupled position. In various embodiments, additional positional data may be recorded once the robotic arms 301a, 301b are in the third coupled position (e.g., fifth positional data corresponding to the distal end of the first robotic arm and sixth positional data corresponding to the distal end of the second robotic arm). In various embodiments, a calibration value (e.g., calibration matrix) may be computed from the recorded positional data at the third, second and/or first coupled position. This process of moving the coupled distal ends to additional coupled positions and collecting positional data for each distal end may be repeated any suitable number of times to generate an accurate calibration value for each of the robotic arms 301a, 301b. In various embodiments, any combination (e.g., all or only a portion) of the recorded positional data may be used to compute the calibration value.
In various embodiments, the coupled distal ends of the robotic arms may be moved to a second coupled position. In various embodiments, third positional data for the distal end of the first robotic arm and fourth positional data for the distal end of the second robotic arm are collected at the first coupled position. In various embodiments, the calibration value is determined using the first, second, third, and fourth positional data. In various embodiments, the calibration value determined from the first and second positional data is applied to the third and fourth positional data.
Referring now to
In computing node 10 there is a computer system/server 12, which is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with computer system/server 12 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like.
Computer system/server 12 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system/server 12 may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.
As shown in
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Computer system/server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 12, and it includes both volatile and non-volatile media, removable and non-removable media.
System memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and/or cache memory 32. Computer system/server 12 may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system 34 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM or other optical media can be provided. In such instances, each can be connected to bus 18 by one or more data media interfaces. As will be further depicted and described below, memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the disclosure.
Program/utility 40, having a set (at least one) of program modules 42, may be stored in memory 28 by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Program modules 42 generally carry out the functions and/or methodologies of embodiments described herein.
Computer system/server 12 may also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24, etc.; one or more devices that enable a user to interact with computer system/server 12; and/or any devices (e.g., network card, modem, etc.) that enable computer system/server 12 to communicate with one or more other computing devices. Such communication can occur via Input/Output (I/O) interfaces 22. Still yet, computer system/server 12 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter 20. As depicted, network adapter 20 communicates with the other components of computer system/server 12 via bus 18. It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer system/server 12. Examples, include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.
In other embodiments, the computer system/server may be connected to one or more cameras (e.g., digital cameras, light-field cameras) or other imaging/sensing devices (e.g., infrared cameras or sensors).
The present disclosure includes a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.
The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In various embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.
Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In various alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
The descriptions of the various embodiments of the present disclosure have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
This application is a continuation application of International Application No. PCT/US2019/065056, filed on Dec. 6, 2019, which application claims the benefit of U.S. Provisional Application No. 62/776,842, filed Dec. 7, 2018, which applications are incorporated herein by reference in their entirety for all purposes.
| Number | Date | Country | |
|---|---|---|---|
| 62776842 | Dec 2018 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/US2019/065056 | Dec 2019 | US |
| Child | 17338030 | US |
