WO2018209861A1 - 角加速度确定方法、装置、机器人及存储介质 - Google Patents

角加速度确定方法、装置、机器人及存储介质 Download PDF

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Publication number
WO2018209861A1
WO2018209861A1 PCT/CN2017/103262 CN2017103262W WO2018209861A1 WO 2018209861 A1 WO2018209861 A1 WO 2018209861A1 CN 2017103262 W CN2017103262 W CN 2017103262W WO 2018209861 A1 WO2018209861 A1 WO 2018209861A1
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Prior art keywords
angular acceleration
target object
running
actual
determining
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PCT/CN2017/103262
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English (en)
French (fr)
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阳方平
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广州视源电子科技股份有限公司
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Publication of WO2018209861A1 publication Critical patent/WO2018209861A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J13/00—Controls for manipulators
    • B25J13/08—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
    • B25J13/088—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices with position, velocity or acceleration sensors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1602—Programme controls characterised by the control system, structure, architecture

Definitions

  • the present invention relates to the field of robot control technologies, and in particular, to an angular acceleration determining method, apparatus, robot, and storage medium.
  • a servo system also known as a follow-up system, is a feedback control system used to accurately follow or reproduce a process. It is capable of controlling the position, orientation, state, etc. of an object to follow the input target (or give Automatic control system with arbitrary changes of fixed value).
  • An engine that controls the operation of mechanical components in a servo system is called a servo motor, which is an auxiliary motor indirect shifting device.
  • the servo motor guarantees a very accurate control speed and positional accuracy, and can convert the voltage signal into torque and speed to drive the control object.
  • Servo motors can be widely used in robotics such as robotic arms and mobile trolleys.
  • the angular acceleration of the servo motor is a physical quantity that is often required to be used, and the joint torque of the mechanical arm can be estimated from the angular acceleration, and can also be used for model identification of the moving trolley.
  • the servo motor driver can directly acquire the physical quantity such as the angle, angular velocity, and current of the servo motor, and then determine the angular acceleration of the servo motor by the above physical quantity.
  • the existing method of determining the angular acceleration generally causes the proportion of random noise and error in the measurement result to be too large, resulting in a very inaccurate angular acceleration.
  • an embodiment of the present invention provides a method, a device, a robot, and a method for determining an angular acceleration.
  • the medium is stored to solve the technical problem that the angular acceleration result is inaccurate due to the excessive proportion of random noise and error in the measurement result.
  • an embodiment of the present invention provides a method for determining an angular acceleration, including:
  • an embodiment of the present invention further provides an angular acceleration determining apparatus, including:
  • a parameter obtaining module configured to acquire an operating parameter and an ideal angular acceleration of the current time during the running of the target object
  • An acceleration measuring module configured to determine an actual measured angular acceleration of the target object at a current time according to the operating parameter
  • an acceleration determining module configured to determine an actual angular acceleration of the target object at the current moment based on the actual measured angular acceleration and the ideal angular acceleration.
  • an embodiment of the present invention further provides a robot, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the program as the first The angular acceleration determining method described in the aspect.
  • an embodiment of the present invention further provides a storage medium including computer executable instructions for performing the angular acceleration determining method according to the first aspect when executed by a computer processor.
  • the method, device, robot and storage medium for determining the angular acceleration acquire the running parameter of the current moment and the ideal angular acceleration during the running of the target object, and determine the actual value of the target object at the current moment according to the obtained running parameter. Measure angular acceleration to measure based on actual measurements The angular acceleration and the ideal angular acceleration obtain the actual angular acceleration of the target object at the current moment. When determining the final result of the actual angular acceleration, it depends not only on the actual measured angular acceleration but also on the ideal angular acceleration at the current moment. The technical problem of inaccurate result due to excessive random noise and error in the actual measured angular acceleration is avoided, and the technical error of correcting the measurement error and making the actual angular acceleration finally obtained is more accurate.
  • FIG. 1a is a flowchart of a method for determining an angular acceleration according to Embodiment 1 of the present invention
  • FIG. 1b is a schematic diagram of a robot mounted with a target object according to Embodiment 1 of the present invention
  • FIG. 2 is a flowchart of a method for determining an angular acceleration according to Embodiment 2 of the present invention
  • FIG. 3 is a schematic structural diagram of an angular acceleration determining apparatus according to Embodiment 3 of the present invention.
  • FIG. 4 is a schematic structural diagram of a robot according to Embodiment 4 of the present invention.
  • FIG. 1a is a flowchart of a method for determining an angular acceleration according to Embodiment 1 of the present invention.
  • the angular acceleration determining method provided in this embodiment is applicable to determining the actual running of the target object when the target object is running.
  • the angular acceleration determining method provided by the embodiment may be performed by an angular acceleration determining device, which may be implemented by software and/or hardware, and integrated in a robot in which a target object is installed.
  • the target object is a device that has a rotating function and can be controlled by the host computer through the driver after the power is turned on.
  • the target object can be a motor.
  • the robot is a machine that can perform work automatically. It can accept human command, run pre-programmed procedures, or act on principles that are based on artificial intelligence techniques. For example, mobile forklifts and equipment with robotic arms are all robots.
  • the method for determining an angular acceleration provided in this embodiment may specifically include:
  • the running parameter is a physical quantity of the target object during the running process, which includes the measured physical quantity of the current moment (also referred to as the current running parameter) and the measured physical quantity of the recorded historical moment (also referred to as Historical running parameters).
  • the physical quantity may include: a target object rotation angle, a rotation angular velocity, a sampling period, and/or a running time.
  • the ideal angular acceleration is the angular acceleration that the target object expects to produce at the current moment.
  • the current moment may also be referred to as a current sampling moment.
  • the operating parameters and the ideal angular acceleration are obtained, the operating parameters and the ideal angular acceleration are obtained according to the set sampling period interval.
  • FIG. 1b is a schematic diagram of a robot mounted with a target object
  • the robot specifically includes: a target object 11, an encoder 12, a driver 13, and a host computer 14.
  • the encoder 12 is disposed on the target object 11 for detecting the physical quantity of the current time of the target object 11 and generating encoded data when the target object 11 is running.
  • the driver 13 is electrically connected to the target object 11 for driving the target object 11 according to the torque command of the host computer 14, and is also used for reading the encoded data of the encoder 12 and converting the encoded data into the current time recognizable by the host computer 14. After the physical quantity (current running parameter), the physical quantity of the current time is sent to the upper computer 14.
  • the host computer 14 is connected to the bus of the driver 13 for rooting
  • the angular acceleration determination method is performed based on the physical quantity (current operation parameter) of the current time and the physical quantity (historical operation parameter) of the recorded historical time, and is also used to generate a torque command, and the target object 11 is controlled to be operated by the driver 13.
  • the host computer 14 is installed with a Linux operating system. It should be noted that the above-mentioned robot is only used to explain how to obtain the current operating parameters, and is not limited to the robot in which the target object is installed in the embodiment.
  • the physical quantity (current running parameter) of the current time may be determined by the encoded data read by the encoder 12, and the physical quantity (historical running parameter) measured by the historical time of the current record may be acquired.
  • the physical quantity (historical running parameter) of the historical moment includes: a physical quantity obtained at a previous sampling moment and/or a physical quantity obtained by the first two sampling moments.
  • the motion planning of the target object may be performed during the initial operation of the target object, and the ideal angular acceleration of the current moment is determined according to the motion planning result.
  • the ideal angle of the target object at the current time is determined, and the ideal angle is calculated by the second integral to obtain the ideal angular acceleration.
  • the ideal angular velocity of the target object at the current time is determined according to the result of the motion planning, and an integral calculation is performed on the ideal angular velocity to obtain an ideal angular acceleration.
  • the ideal angular acceleration of the target object at the current time is directly determined according to the result of the motion planning.
  • the specific method of the motion planning is not limited in this embodiment.
  • the actual measured angular acceleration is an angular acceleration of the current time of the target object calculated according to the operating parameter, which depends on the measured physical quantity in the operating parameter, and can also be understood as the measured angular acceleration as the measured angular acceleration. Since the error in the operating parameters is amplified when calculating the actual measured angular acceleration, the error between the actual measured angular acceleration and the actual angular acceleration of the target object during actual operation is large. In view of this, after the actual measured angular acceleration is obtained, the actual measured angular acceleration is not directly taken as the actual angular acceleration, but is processed through subsequent processing to ensure the final The result of the actual angular acceleration obtained is more accurate.
  • the specific calculation rule of the actual measured angular acceleration is not limited in this embodiment.
  • the running parameter may be the running angular velocity of the current time of the target object, the running angular velocity of the last sampling instant, the current time, and the sampling period, and performing a differential calculation according to the above operating parameters to obtain the current time of the target object.
  • the actual measured angular acceleration; the operating parameter may also be the running angle of the current time of the target object, the running angle of the previous sampling time, the running angle of the first two sampling moments, the current time, and the sampling period, and the second differential calculation is performed according to the above operating parameters.
  • the actual measured angular acceleration of the target object at the current time.
  • the sampling low-pass filter filters the measured angular acceleration, and uses the signal output by the low-pass filter as the actual measured angular acceleration.
  • the filter parameters of the low-pass filter can be set according to the actual situation.
  • the measured data is usually differentially amplified, which causes the measurement errors existing in the measured data to be differentially amplified together.
  • the measurement error is corrected using a low-pass filter, there is still a high measurement error in the actual measured angular acceleration after filtering.
  • the actual angular acceleration is corrected by using the ideal angular acceleration to obtain the actual angular acceleration, and the actual angular acceleration is closest to the target object. The angular acceleration of the actual operation.
  • the current filter may be used to Actual measurement of angular acceleration and ideal angular acceleration as filter
  • the input of the filter uses the output of the filter as the actual angular acceleration of the current time of the target object.
  • the filter may be selected from a Bayesian filter, a Kalman filter, or the like.
  • the target object After determining the actual angular acceleration of the current time of the target object, it is confirmed whether the target object is still running. If the target object continues to run, the next sampling time is taken as the current time of the target object according to the sampling period, and then determined according to the above method. The actual angular acceleration of the target object at the current moment until the target object finishes running.
  • the technical solution provided by the embodiment obtains the running parameter of the current time and the ideal angular acceleration during the running of the target object, and determines the actual measured angular acceleration of the target object at the current time according to the acquired running parameter, so as to measure the angular acceleration according to the actual measurement.
  • the ideal angular acceleration to obtain the actual angular acceleration of the target object at the current moment the realization of the final result of the actual angular acceleration, not only depends on the actual measured angular acceleration, but also depends on the ideal angular acceleration at the current moment, avoiding Due to the technical problem of the randomness of the random noise and the error in the actual measurement of the angular acceleration, the result is inaccurate, and the technical error of correcting the measurement error is obtained, so that the actual angular acceleration finally obtained is more accurate.
  • FIG. 2 is a flowchart of a method for determining an angular acceleration according to Embodiment 2 of the present invention.
  • the angular acceleration determining method provided in this embodiment is embodied on the basis of the above embodiment. Specifically, the determining, according to the operating parameter, the actual measured angular acceleration of the target object at the current time is: calculating a measured angular acceleration of the target object at the current time according to the operating parameter; using a low pass filter The measured angular acceleration is filtered to obtain an actual measured angular acceleration.
  • the method further includes: acquiring an initial parameter of the initial running time of the target object; using the initial parameter The number constructs a motion planning formula according to a preset rule to determine an ideal angular acceleration of the target object at the current moment according to the motion planning formula.
  • determining the actual angular acceleration of the target object at the current moment based on the actual measured angular acceleration and the ideal angular acceleration is specifically: using the actual measured angular acceleration and the ideal angular acceleration as the input of the Bayesian filter, and filtering the Bayesian
  • the output of the device is the actual angular acceleration of the target object at the current time.
  • the method for determining an angular acceleration specifically includes:
  • the initial parameters include initial target operating parameters and initial actual operating parameters of the target object initial running time.
  • the initial target running parameter is a target running parameter that is expected to be achieved when the target object is initially operated, and specifically includes: an initial target angle, an initial target angular velocity, and/or an initial target angular acceleration, and the initial actual operating parameter is actually achieved when the target object is initially operated.
  • the operating parameters include: initial time angle, initial time angular velocity, actual measured angular acceleration at the initial time, and/or sampling period, and the sampling period is the same as the sampling period in the operating parameter.
  • the initial target running parameter may be set when the target object is initialized, and the setting rule and the specific value may be determined according to the application scenario of the target object.
  • the initial actual operating parameters can be measured at the initial operation of the target object, and the specific measurement method is the same as the measurement method of the aforementioned current operating parameters.
  • the motion planning is to plan each running time of the target object to determine a target operating parameter that the target object expects to reach at each running time.
  • the target operating parameter includes at least one of an ideal angle of the current moment, an ideal angular velocity, and an ideal angular acceleration.
  • the motion planning formula is a mathematical expression of the reaction motion planning, which can be determined by calculation. According to the motion planning formula, the target pair can be determined. Like the ideal angular acceleration at the current moment.
  • the fifth-order polynomial method is exemplarily selected for motion planning.
  • the following is a detailed description of the motion planning formula based on the fifth-order polynomial method:
  • the five-time polynomial method of motion planning can be expressed as:
  • a 0 , a 1 , a 2 , a 3 , a 4 and a 5 are the planning coefficients
  • t is the current running time of the moving object (the target object in this embodiment)
  • S(t) is the time t.
  • initial target angle ⁇ 0 initial target angular velocity Initial target angular acceleration Initial time angle ⁇ (0), initial moment angular velocity Actual measurement of angular acceleration at initial time
  • T sampling period
  • ⁇ 1 (t) a 0 +a 1 t+a 2 t 2 +a 3 t 3 +a 4 t 4 +a 5 t 5 (3)
  • Equations (3), (4), and (5) are motion planning formulas of the constructed target object. According to the above motion planning formula, the target operating parameters of the target object that are expected to run at any running time can be obtained. It should be noted that, in the actual process, at least one motion planning formula may be selectively constructed in the equations (3), (4), and (5) according to actual conditions. In the present embodiment, the structural formula (5) is preferred.
  • the ideal angular acceleration at the current time can be determined by using equation (5).
  • the ideal angle or the ideal angular velocity of the current moment may be determined by using formula (3) or formula (4) after the current moment is known, and the ideal angular acceleration of the current moment is further calculated.
  • the running parameters include current running parameters and historical running parameters.
  • the current running parameter may include: a current time, a sampling period, a running angle of the target object, and/or an operating angular velocity of the target object.
  • the historical running parameter may include: an operating angular velocity of the target object at a historical time and/or a running angular velocity of the target object at a historical time, and the historical moment may be at least one historical sampling moment.
  • Scheme 1 Perform a second differential calculation on the current operating parameters and historical operating parameters to obtain the measured angular acceleration.
  • the current running parameter may include: a current time, a sampling period, and a running angle of the target object
  • the historical running parameter may optionally include: a running angle of the target object in the first preset historical time.
  • the first preset historical time preferably includes: a historical time corresponding to a previous sampling period of the current time, and a historical time corresponding to the first two sampling periods of the current time.
  • the running angle of the target object is the measured running angle.
  • the quadratic differential formula in the solution is specifically:
  • T is the sampling period, which is set when the target object is initially running
  • ⁇ (t) is the running angle of the target object
  • t is the current time
  • ⁇ (tT) is the historical time corresponding to the previous sampling period based on the current time.
  • the running angle of the target object, ⁇ (t-2T) is the running angle of the target object based on the historical time corresponding to the first two sampling periods of the current time.
  • the angular acceleration is measured for the current moment calculated.
  • Scheme 2 Perform a differential calculation on the current operating parameters and historical operating parameters to obtain the measured angular acceleration.
  • the current running parameter may include: a current time, a sampling period, and an operating angular velocity of the target object
  • the historical running parameter may optionally include: a running angular velocity of the target object in the second preset historical time.
  • the second preset historical time preferably includes: a historical time corresponding to a previous sampling period of the current time.
  • the running angular velocity of the target object is the measured running angular velocity.
  • the first differential formula in the solution is specifically:
  • T is the sampling period, which is set when the target object is initially running.
  • t is the current time
  • the running angular velocity of the target object based on the historical time corresponding to the previous sampling period of the current time, The angular acceleration is measured for the current moment calculated.
  • S250 Filter the measured angular acceleration by using a low-pass filter to obtain an actual measured angular acceleration.
  • the measured angular acceleration is filtered by a low-pass filter to achieve high-frequency noise suppression to some extent and amplification of the error in differential calculation.
  • the low-pass filter can be a first-order low-pass filter, and the specific filter parameters can be set according to actual conditions.
  • the filtering formula of the first-order low-pass filter is:
  • ⁇ is the cutoff frequency
  • s is the independent variable
  • F(s) is the Laplace transform
  • T is the sampling period
  • the specific value may be the same as the sampling period in the operating parameter, or may be different from the sampling period in the operating parameter
  • X(t) is the input signal of the current moment of the first-order low-pass filter.
  • X(t) is the measured angular acceleration
  • t is the current time
  • Y(tT) is the first-order low-pass filtering based on the output signal corresponding to the previous sampling period of the current time.
  • Y(tT) is The actual measured angular acceleration outputted at the previous sampling time
  • a ⁇ 2 ⁇ T
  • ⁇ is the cutoff frequency
  • Y(t) is the output signal of the current time.
  • Y(t) is the actual measured angular acceleration output at the current time. .
  • the actual measured angular acceleration and the ideal angular acceleration are used as input of the Bayesian filter, and the output of the Bayesian filter is taken as the actual angular acceleration of the target object at the current time.
  • the filter coefficient of the Bayesian filter can be set according to actual conditions.
  • the actual measured angular acceleration and the ideal angular acceleration both satisfy the Gaussian distribution, and the first variance value corresponding to the actual measured angular acceleration is greater than the second variance value corresponding to the ideal angular acceleration.
  • the actual measured angular acceleration output through the low pass filter can be approximated as satisfying a Gaussian distribution, which can be written as among them, Actual measured angular acceleration at time t,
  • R t is the first variance value corresponding to the actual measured angular acceleration, which can be determined by analyzing the actual measured angular acceleration of the history.
  • the ideal angular acceleration can also be approximated as satisfying a Gaussian distribution, which can be written as among them.
  • Q t is the second variance value corresponding to the ideal angular acceleration, which can be set by the control effect achieved when the target object is running.
  • R t is greater than Q t to indicate that the confidence of the ideal angular acceleration is higher than the confidence of the actual measured angular acceleration.
  • setting R t greater than Q t ensures that the actual angular acceleration ultimately obtained is more accurate.
  • the actual measured angular acceleration and the ideal angular acceleration are combined by a Bayesian filter to obtain the actual angular acceleration at the current time.
  • the actual angular acceleration can also be considered to satisfy the Gaussian distribution.
  • the actual angular acceleration Gaussian distribution can be expressed as:
  • ⁇ is a proportional coefficient, which may also be referred to as a distribution average, which can be obtained by calculation.
  • ⁇ is a proportional coefficient, which may also be referred to as a distribution average, which can be obtained by calculation.
  • Gaussian distribution for the actual angular acceleration Gaussian distribution, Gaussian distribution for ideal angular acceleration, For the actual measurement of the angular acceleration Gaussian distribution.
  • R t is the first variance value corresponding to the actual measured angular acceleration
  • Q t is the second variance value corresponding to the ideal angular acceleration
  • t is the current time.
  • the initial parameters of the initial running time are read, which specifically include: an initial time angle, which is recorded as ⁇ (0); an initial time angular velocity, which is recorded as And set the initial measured actual angular acceleration and the actual angular acceleration are zero, recorded as Initial target angle ⁇ 0 ; initial target angular velocity Initial target angular acceleration
  • the sampling period is T.
  • the actual angular acceleration at the end of the servo motor last operation may be used as the actual angular acceleration of the initial running time.
  • the operation can be continuously determined according to the above method.
  • the technical solution provided by the embodiment obtains an initial parameter of the target object when the target object is initially run, and constructs a motion planning formula according to the initial parameter, and acquires an operation parameter of the current time in the running process of the target object, and according to the operation plan.
  • the formula determines the ideal angular acceleration at the current moment, obtains the measured angular acceleration according to the operating parameters and low-pass filters the measured angular acceleration to obtain the actual measured angular acceleration, and uses the actual measured angular acceleration and the ideal angular acceleration as the input of the Bayesian filter.
  • the final result of determining the actual angular acceleration is achieved not only by the actual measured angular acceleration but also by the ideal angular acceleration at the current moment, the ideal angular acceleration and
  • the actual measurement of the angular acceleration as the input of the Bayesian filter can avoid the technical problem of inaccurate result due to the excessive proportion of random noise and error in the actual measured angular acceleration, and the corrected measurement error is obtained, so that the actual angle obtained is finally obtained. accelerate More precise technical effect.
  • FIG. 3 is a schematic structural diagram of an angular acceleration determining apparatus according to Embodiment 3 of the present invention.
  • the angular acceleration determining apparatus provided in this embodiment includes a parameter acquiring module 301, an acceleration measuring module 302, and an acceleration determining module 303.
  • the parameter obtaining module 301 is configured to acquire an operating parameter and an ideal angular acceleration of the current time during the running of the target object, and the acceleration measuring module 302 is configured to determine an actual measured angular acceleration of the target object at the current time according to the operating parameter; the acceleration determining module 303. Determine an actual angular acceleration of the target object at the current moment based on the actual measured angular acceleration and the ideal angular acceleration.
  • the technical solution provided in this embodiment obtains the current time by running during the running of the target object.
  • the line parameter and the ideal angular acceleration, and the actual measured angular acceleration of the target object at the current time is determined according to the obtained running parameter, so as to obtain the actual angular acceleration of the target object according to the actual measured angular acceleration and the ideal angular acceleration,
  • the final result of the actual angular acceleration it depends not only on the actual measured angular acceleration, but also on the ideal angular acceleration at the current moment, avoiding the inaccurate result due to the excessive proportion of random noise and error in the actual measured angular acceleration.
  • the technical problem has reached the technical effect of correcting the measurement error and making the actual angular acceleration finally obtained more accurate.
  • the acceleration measurement module 302 includes: a measurement unit 3021, configured to calculate a measured angular acceleration of the target object at the current time according to the operation parameter; and a filtering unit 3022, configured to measure the angular acceleration by using the low-pass filter Filtering is performed to obtain the actual measured angular acceleration.
  • the operating parameters include current operating parameters and historical operating parameters.
  • the measuring unit 3021 is specifically configured to: perform second differential calculation on the current operating parameter and the historical running parameter to obtain the measured angular acceleration, and the current operating parameters include: the current time, the sampling period, and the running angle of the target object, and the historical running parameter.
  • the method includes: a running angle of the target object in a first preset historical time; or performing a differential calculation on the current running parameter and the historical running parameter to obtain a measured angular acceleration, where the current operating parameters include: a current time, a sampling period, and a target object
  • the running angular velocity, the historical running parameter includes: a running angular velocity of the target object at the second preset historical moment.
  • the method further includes: an initialization module 304, configured to acquire an initial parameter of an initial running time of the target object before acquiring an operating parameter and an ideal angular acceleration of the current time during the running of the target object; and the motion planning module 305 uses The motion planning formula is constructed according to a preset rule by using the initial parameters to determine the ideal angular acceleration of the target object at the current moment according to the motion planning formula.
  • the acceleration determining module 303 is specifically configured to: use the actual measured angular acceleration and the ideal angular acceleration as the input of the Bayesian filter, and use the output of the Bayesian filter as the mesh. The actual angular acceleration of the target object at the current moment.
  • the actual measured angular acceleration and the ideal angular acceleration both satisfy the Gaussian distribution, and the first variance value corresponding to the actual measured angular acceleration is greater than the second variance value corresponding to the ideal angular acceleration.
  • the angular acceleration determining apparatus provided in this embodiment may perform the angular acceleration determining method provided by any of the above embodiments, and has corresponding functions and beneficial effects.
  • the robot includes a processor 40, a memory 41, an input device 42, and an output device 43.
  • the number of processors 40 in the robot may be One or more, one processor 40 is taken as an example in FIG. 4; the processor 40, the memory 41, the input device 42 and the output device 43 in the robot can be connected by a bus or other means, and the bus connection is taken as an example in FIG. .
  • the processor 40 executes the program, the angular acceleration determining method in the embodiment of the present invention is implemented.
  • the memory 41 is used as a computer readable storage medium, and can be used to store a software program, a computer executable program, and a module, such as a program instruction/module corresponding to the angular acceleration determining method in the embodiment of the present invention (for example, in an angular acceleration determining device)
  • the processor 40 executes various functional applications of the robot and data processing by executing software programs, instructions, and modules stored in the memory 41, that is, implementing the above-described angular acceleration determining method.
  • the memory 41 may mainly include a storage program area and an storage data area, wherein the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created according to usage of the robot, and the like. Furthermore, the memory 41 may comprise a high speed random access memory, and may also comprise a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile Solid state storage devices. In some examples, memory 41 may further include memory remotely located relative to processor 40, which may be connected to the robot via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
  • Input device 42 can be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the robot.
  • the output device 43 may include a display device such as a display screen.
  • Embodiment 5 of the present invention further provides a storage medium including computer executable instructions for performing an angular acceleration determining method when executed by a computer processor, the angular acceleration determining method comprising:
  • the computer executable instructions are not limited to the angular acceleration determining method operation as described above, and may also perform the angular acceleration provided by any embodiment of the present invention. Determine the relevant actions in the method.
  • the present invention can be implemented by software and necessary general hardware, and can also be implemented by hardware, but in many cases, the former is a better implementation. .
  • the technical solution of the present invention which is essential or contributes to the prior art, may be embodied in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk of a computer.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • FLASH Flash memory
  • hard disk or optical disk includes instructions for causing a computer device (which may be a robot, a personal computer, a server, or a network device, etc.) to perform the angular acceleration determination method described in various embodiments of the present invention.
  • a computer device which may be a robot, a personal computer, a server, or a network device, etc.
  • each unit and module included is divided according to functional logic, but is not limited to the above-mentioned division, as long as the corresponding function can be implemented;
  • the specific names of the respective functional units are also for convenience of distinguishing from each other and are not intended to limit the scope of protection of the present invention.
  • portions of the invention may be implemented in hardware, software, firmware or a combination thereof.
  • multiple steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques well known in the art: having logic gates for implementing logic functions on data signals. Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

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  • Engineering & Computer Science (AREA)
  • Robotics (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Feedback Control In General (AREA)
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Abstract

一种角加速度确定方法、装置、机器人及存储介质。其中，该角加速度确定方法包括：获取目标对象运行过程中当前时刻的运行参数和理想角加速度；根据运行参数确定目标对象在当前时刻的实际测量角加速度；基于实际测量角加速度和理想角加速度确定目标对象在当前时刻的实际角加速度。根据上述角加速度确定方法可以解决由于测量结果中随机噪声和误差的比重过大导致角加速度结果不准确的技术问题。

Description

角加速度确定方法、装置、机器人及存储介质 技术领域
本发明涉及机器人控制技术领域，尤其涉及一种角加速度确定方法、装置、机器人及存储介质。
背景技术
伺服系统，又称为随动系统，是用来精确地跟随或复现某个过程的反馈控制系统，其是可以使物体的位置、方位、状态等输出被控量能够跟随输入目标(或给定值)的任意变化的自动控制系统。在伺服系统中控制机械元件运转的发动机称为伺服电机，其是一种补助马达间接变速装置。
伺服电机可保证控制速度以及位置精度非常准确，可以将电压信号转化为转矩和转速以驱动控制对象。伺服电机可以被广泛的应用于机械臂以及移动小车等机器人领域。一般而言，在上述领域中，伺服电机的角加速度是经常需要使用的物理量，根据角加速度可以估计出机械臂的关节力矩，也可以用于移动小车的模型辨识。通常，伺服电机的驱动器可以直接获取伺服电机的角度、角速度以及电流等物理量，进而通过上述物理量确定伺服电机的角加速度。然而，现有的角加速度确定方法通常会造成测量结果中随机噪声和误差的比重过大，导致测量得到的角加速度十分不精确。
发明内容
有鉴于此，本发明实施例提供一种角加速度确定方法、装置、机器人及存 储介质，以解决由于测量结果中随机噪声和误差的比重过大导致角加速度结果不准确的技术问题。
第一方面，本发明实施例提供了一种角加速度确定方法，包括：
获取目标对象运行过程中当前时刻的运行参数和理想角加速度；
根据所述运行参数确定所述目标对象在当前时刻的实际测量角加速度；
基于所述实际测量角加速度和所述理想角加速度确定所述目标对象在所述当前时刻的实际角加速度。
第二方面，本发明实施例还提供了一种角加速度确定装置，包括：
参数获取模块，用于获取目标对象运行过程中当前时刻的运行参数和理想角加速度；
加速度测量模块，用于根据所述运行参数确定所述目标对象在当前时刻的实际测量角加速度；
加速度确定模块，用于基于所述实际测量角加速度和所述理想角加速度确定所述目标对象在所述当前时刻的实际角加速度。
第三方面，本发明实施例还提供了一种机器人，包括：存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现如第一方面所述的角加速度确定方法。
第四方面，本发明实施例还提供了一种包含计算机可执行指令的存储介质，所述计算机可执行指令在由计算机处理器执行时用于执行如第一方面所述的角加速度确定方法。
本发明实施例提供的角加速度确定方法、装置、机器人及存储介质，通过在目标对象运行过程中获取当前时刻的运行参数以及理想角加速度，并根据获取的运行参数确定目标对象在当前时刻的实际测量角加速度，以根据实际测量 角加速度和理想角加速度得到目标对象在当前时刻的实际角加速度的技术方案，实现了在确定实际角加速度的最终结果时，不仅取决于实际测量角加速度，还取决于当前时刻的理想角加速度，避免了由于实际测量角加速度中随机噪声和误差的比重过大导致结果不准确的技术问题，达到了修正测量误差，使得最终得到的实际角加速度更加精确的技术效果。
附图说明
通过阅读参照以下附图所作的对非限制性实施例所作的详细描述，本发明的其它特征、目的和优点将会变得更明显：
图1a为本发明实施例一提供的一种角加速度确定方法的流程图；
图1b为本发明实施例一提供的一种安装有目标对象的机器人示意图；
图2为本发明实施例二提供的一种角加速度确定方法的流程图；
图3为本发明实施例三提供的一种角加速度确定装置的结构示意图；
图4为本发明实施例四提供的一种机器人的结构示意图。
具体实施方式
下面结合附图和实施例对本发明作进一步的详细说明。可以理解的是，此处所描述的具体实施例仅仅用于解释本发明，而非对本发明的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与本发明相关的部分而非全部内容。
实施例一
图1a为本发明实施例一提供的一种角加速度确定方法的流程图。本实施例提供的角加速度确定方法适用于在目标对象运行时，确定目标对象实际运行的 角加速度的情况。其中，本实施例提供的角加速度确定方法可以由角加速度确定装置执行，该角加速度确定装置可以通过软件和/或硬件的方式实现，并集成在安装有目标对象的机器人中。在本实施例中，目标对象为具有转动功能且在接通电源后可以由上位机通过驱动器控制其转动的设备。例如，目标对象可以为电机。机器人为可以自动执行工作的机器装置。它既可以接受人类指挥，又可以运行预先编排的程序，也可以根据以人工智能技术制定的原则纲领行动。例如，移动叉举车以及带有机械臂的设备等均属于机器人。
参考图1a，本实施例提供的角加速度确定方法具体可以包括：
S110、获取目标对象运行过程中当前时刻的运行参数和理想角加速度。
在本实施例中，运行参数为目标对象在运行过程中的物理量，其包括测量得到的当前时刻的物理量(也可称为当前运行参数)和记录的历史时刻测量得到的物理量(也可称为历史运行参数)。可选的，物理量可以包括：目标对象转动角度、转动角速度、采样周期和/或运行时间等。理想角加速度是在当前时刻目标对象期望产生的角加速度。
进一步的，当前时刻也可以称为当前采样时刻。在获取运行参数和理想角加速度时，根据设定的采样周期间隔获取运行参数和理想角加速度。
示例性的，参考图1b，其为安装有目标对象的机器人示意图，该机器人具体包括：目标对象11、编码器12、驱动器13以及上位机14。其中，编码器12设置在目标对象11上，用于在目标对象11运行时检测目标对象11当前时刻的物理量并生成编码数据。驱动器13与目标对象11电气连接，用于根据上位机14的力矩指令驱动目标对象11运行，还用于读取编码器12的编码数据，并将编码数据转换成上位机14可识别的当前时刻的物理量(当前运行参数)后，将当前时刻的物理量发送至上位机14。上位机14与驱动器13总线连接，用于根 据当前时刻的物理量(当前运行参数)以及记录的历史时刻的物理量(历史运行参数)执行角加速度确定方法，还用于生成力矩指令，并通过驱动器13控制目标对象11运行。可选的，上位机14安装有Linux操作系统。需要说明的是，上述机器人仅用于解释说明如何获取当前运行参数，而并非对本实施例中安装有目标对象的机器人的限定。
进一步的，获取运行参数时，可以是通过编码器12读取的编码数据确定当前时刻的物理量(当前运行参数)，并获取当前记录的历史时刻测量得到的物理量(历史运行参数)。可选的，历史时刻的物理量(历史运行参数)包括：前一个采样时刻得到的物理量和/或前两个采样时刻得到的物理量。
典型的，获取当前时刻的理想角加速度时，可以是在目标对象初始运行时，对目标对象的运行过程进行运动规划，并根据运动规划结果确定当前时刻的理想角加速度。例如，根据运动规划结果确定出当前时刻的目标对象的理想角度，对理想角度进行二次积分计算，以得到理想角加速度。再如，根据运动规划结果确定出当前时刻的目标对象的理想角速度，对理想角速度进行一次积分计算，以得到理想角加速度。又如，根据运动规划结果直接确定出当前时刻的目标对象的理想角加速度。其中，运动规划的具体方法本实施例不作限定。
S120、根据运行参数确定目标对象在当前时刻的实际测量角加速度。
具体的，实际测量角加速度为根据运行参数计算得到的目标对象当前时刻的角加速度，其依赖于运行参数中测量得到的物理量，也可以理解为实际测量角加速度为测量得到的角加速度。由于在计算实际测量角加速度时会对运行参数中的误差进行放大，因此会导致实际测量角加速度与目标对象实际运行时的实际角加速度之间的误差较大。有鉴于此，在得到实际测量角加速度后，并不直接将实际测量角加速度作为实际角加速度，而是通过后续处理，以保证最终 得到的实际角加速度的结果更为准确。
进一步的，实际测量角加速度的具体计算规则本实施例不作限定。例如，在计算实际测量角加速度时，运行参数可以是目标对象当前时刻的运行角速度、上一采样时刻的运行角速度、当前时刻以及采样周期，根据上述运行参数进行一次微分计算得到目标对象当前时刻的实际测量角加速度；运行参数还可以是目标对象当前时刻的运行角度、前一采样时刻的运行角度、前二采样时刻的运行角度、当前时刻以及采样周期，根据上述运行参数进行二次微分计算得到目标对象当前时刻的实际测量角加速度。
一般而言，根据运行参数得到的测量角加速度中存在高频噪声以及被放大的测量误差。为了减小上述误差对后续计算结果的影响，采样低通滤波器对测量角加速度进行滤波，并将低通滤波器输出的信号作为实际测量角加速度。其中，低通滤波器的滤波参数可以根据实际情况进行设定。
S130、基于实际测量角加速度和理想角加速度确定目标对象在当前时刻的实际角加速度。
在计算实际测量角加速度时，通常会对测量得到的数据进行差分放大，这样会使得测量得到的数据中存在的测量误差也一同被差分放大。虽然使用低通滤波器修正了测量误差，但是滤波后的实际测量角加速度中仍然存在较高的测量误差。为了保证最终得到的实际角加速度更加贴近目标对象实际运行时的角加速度，在本实施例中利用理想角加速度对实际测量角加速度进行修正，以得到实际角加速度，且实际角加速度最接近目标对象实际运行的角加速度。
具体的，计算得到的实际测量角加速度和理想角加速度均近似满足高斯分布，因此在利用理想角加速度对实际测量角加速度进行修正时，可以是利用现有的滤波器，将目标对象当前时刻的实际测量角加速度和理想角加速度作为滤 波器的输入，将滤波器的输出作为目标对象当前时刻的实际角加速度。其中，滤波器可选为贝叶斯滤波器、卡尔曼滤波器等。
进一步的，确定目标对象当前时刻的实际角加速度后，确认目标对象是否还在继续运行，如果目标对象继续运行，则根据采样周期将下一采样时刻作为目标对象的当前时刻，继续根据上述方法确定目标对象当前时刻的实际角加速度，直到目标对象运行结束为止。
本实施例提供的技术方案，通过在目标对象运行过程中获取当前时刻的运行参数以及理想角加速度，并根据获取的运行参数确定目标对象在当前时刻的实际测量角加速度，以根据实际测量角加速度和理想角加速度得到目标对象在当前时刻的实际角加速度的技术方案，实现了在确定实际角加速度的最终结果时，不仅取决于实际测量角加速度，还取决于当前时刻的理想角加速度，避免了由于实际测量角加速度中随机噪声和误差的比重过大导致结果不准确的技术问题，达到了修正测量误差，使得最终得到的实际角加速度更加精确的技术效果。
实施例二
图2为本发明实施例二提供的一种角加速度确定方法的流程图。本实施例提供的角加速度确定方法是在上述实施例的基础上进行具体化。具体的，所述根据所述运行参数确定所述目标对象在当前时刻的实际测量角加速度具体为：根据所述运行参数计算得到所述目标对象在当前时刻的测量角加速度；利用低通滤波器对所述测量角加速度进行滤波，以得到实际测量角加速度。
进一步的，所述获取目标对象运行过程中当前时刻的运行参数和理想角加速度之前，还具体包括：获取目标对象初始运行时刻的初始参数；利用初始参 数按照预设规则构造运动规划公式，以根据运动规划公式确定目标对象在当前时刻的理想角加速度。
进一步的，所述基于实际测量角加速度和理想角加速度确定目标对象在当前时刻的实际角加速度具体为：将实际测量角加速度和理想角加速度作为贝叶斯滤波器的输入，将贝叶斯滤波器的输出作为目标对象在当前时刻的实际角加速度。
参考图2，本实施例提供的角加速度确定方法具体包括：
S210、获取目标对象初始运行时刻的初始参数。
在本实施例中，初始参数包括目标对象初始运行时刻的初始目标运行参数和初始实际运行参数。其中，初始目标运行参数为目标对象初始运行时期望达到的目标运行参数，其具体包括：初始目标角度、初始目标角速度和/或初始目标角加速度，初始实际运行参数为目标对象初始运行时实际达到的运行参数，其包括：初始时刻角度、初始时刻角速度、初始时刻实际测量角加速度和/或采样周期，且采样周期与运行参数中采样周期相同。
具体的，初始目标运行参数可以在目标对象初始化时设定，且设定规则以及具体数值可以根据目标对象的应用场景决定。初始实际运行参数可以在目标对象初始运行时测量得到，其具体的测量方法与前述当前运行参数的测量方法相同。
S220、利用初始参数按照预设规则构造运动规划公式。
具体的，运动规划是对目标对象各运行时刻进行规划，以确定各运行时刻目标对象期望达到的目标运行参数。其中，目标运行参数包括当前时刻的理想角度、理想角速度以及理想角加速度中的至少一个。运动规划公式为反应运动规划的数学表达式，其可以通过计算确定。根据运动规划公式可以确定目标对 象在当前时刻的理想角加速度。
进一步的，对目标对象进行运动规划时，可以采用现有的多种运动规划方法。在本实施例中，示例性的选择了五次多项式法进行运动规划。下面对基于五次多项式法构造运动规划公式进行详细描述：
五次多项式法的运功规划过程可以表示为：
S(t)＝a0+a1t+a2t2+a3t3+a4t4+a5t5       (1)
其中，a0、a1、a2、a3、a4以及a5，为规划系数，t为运动对象(本实施例中为目标对象)当前的运行时刻，S(t)为t时刻的运功规划结果。
从上述公式可知，如果想要确定目标对象的运功规划结果，需要明确规划系数的具体值，且规划系数的具体值可以根据初始参数确定。
进一步的，初始参数确定规划系数的具体过程为：
设定初始参数包括：初始目标角度θ0、初始目标角速度
Figure PCTCN2017103262-appb-000001
初始目标角加速度
Figure PCTCN2017103262-appb-000002
初始时刻角度θ(0)、初始时刻角速度
Figure PCTCN2017103262-appb-000003
初始时刻实际测量角加速度
Figure PCTCN2017103262-appb-000004
和采样周期T，那么可以得到：
a0＝θ(0)             (2-1)
Figure PCTCN2017103262-appb-000005
Figure PCTCN2017103262-appb-000006
Figure PCTCN2017103262-appb-000007
Figure PCTCN2017103262-appb-000008
Figure PCTCN2017103262-appb-000009
进一步的，确定规划系数后，式(1)可以表示为：
θ1(t)＝a0+a1t+a2t2+a3t3+a4t4+a5t5       (3)
其中，θ1(t)表示为t时刻目标对象期望运行的理想角度。对式(3)进行微 分计算，可得：
Figure PCTCN2017103262-appb-000010
其中，
Figure PCTCN2017103262-appb-000011
表示为t时刻目标对象期望运行的理想角速度。对式(4)进行微分计算，可得：
Figure PCTCN2017103262-appb-000012
其中，
Figure PCTCN2017103262-appb-000013
表示为t时刻目标对象期望运行的理想角加速度。
进一步的，式(3)、式(4)以及式(5)为构造的目标对象的运动规划公式。根据上述运动规划公式便可以得到目标对象任意运行时刻期望运行的目标运行参数。需要说明的是，在实际应该过程中，可以根据实际情况在式(3)、式(4)以及式(5)中选择性的构造至少一个运动规划公式。在本实施例中，优选构造式(5)。
S230、获取目标对象运行过程中当前时刻的运行参数和理想角加速度。
示例性的，在获取理想角加速度时，已知当前时刻t后，便可以利用公式(5)确定出当前时刻的理想角加速度。作为另外的可选方案，也可以在已知当前时刻后，利用公式(3)或者公式(4)确定出当前时刻的理想角度或者理想角速度，并进一步计算得到当前时刻的理想角加速度。
S240、根据运行参数计算得到目标对象在当前时刻的测量角加速度。
具体的，运行参数包括当前运行参数和历史运行参数。其中，当前运行参数可选包括：当前时刻、采样周期、目标对象的运行角度和/或目标对象的运行角速度等。历史运行参数可选包括：历史时刻目标对象的运行角速和/或历史时刻目标对象的运行角速度等，上述历史时刻可以是至少一个历史采样时刻。
进一步的，根据运行参数计算目标对象当前时刻的测量角加速度时，可以包括下述任一种方案：
方案一、对当前运行参数和历史运行参数进行二次微分计算，以得到测量角加速度。
在本方案中，当前运行参数可选包括：当前时刻、采样周期和目标对象的运行角度，历史运行参数可选包括：第一预设历史时刻目标对象的运行角度。其中，第一预设历史时刻优选包括：基于当前时刻的前一个采样周期对应的历史时刻，基于当前时刻的前二个采样周期对应的历史时刻。目标对象的运行角度为测量得到的运行角度。
可选的，本方案中二次微分公式具体为：
Figure PCTCN2017103262-appb-000014
其中，T为采样周期，其在目标对象初始运行时设定，θ(t)为目标对象的运行角度，t是当前时刻，θ(t-T)为基于当前时刻的前一个采样周期对应的历史时刻目标对象的运行角度，θ(t-2T)为基于当前时刻的前二个采样周期对应的历史时刻目标对象的运行角度，
Figure PCTCN2017103262-appb-000015
为计算得到的当前时刻测量角加速度。
方案二、对当前运行参数和历史运行参数进行一次微分计算，以得到测量角加速度。
在本方案中，当前运行参数可选包括：当前时刻、采样周期和目标对象的运行角速度，历史运行参数可选包括：第二预设历史时刻目标对象的运行角速度。第二预设历史时刻优选包括：基于当前时刻的前一个采样周期对应的历史时刻。目标对象的运行角速度为测量得到的运行角速度。
可选的，本方案中一次微分公式具体为：
Figure PCTCN2017103262-appb-000016
其中，T为采样周期，其在目标对象初始运行时设定，
Figure PCTCN2017103262-appb-000017
为目标对象的运 行角速度，t是当前时刻，
Figure PCTCN2017103262-appb-000018
为基于当前时刻的前一个采样周期对应的历史时刻目标对象的运行角速度，
Figure PCTCN2017103262-appb-000019
为计算得到的当前时刻测量角加速度。
S250、利用低通滤波器对测量角加速度进行滤波，以得到实际测量角加速度。
具体的，利用低通滤波器对测量角加速度进行滤波，以实现在一定程度上抑制高频噪声以及在微分计算时对误差的放大。其中，低通滤波器可以为一阶低通滤波器，其具体的滤波参数可以根据实际情况设定。
下面以一阶低通滤波器为例进行描述：
具体的，一阶低通滤波器的滤波公式为：
Figure PCTCN2017103262-appb-000020
在式(8)中，λ为截止频率，s为自变量，F(s)为拉普拉斯变换量。在实际应用中，为了简化计算机实现过程，在一阶低通滤波器滤波时，优选采用微分差分方程，其具体为：
Y(t)＝aX(t)+(1-a)Y(t-T)         (9)
其中，T为采样周期，其具体值可以与运行参数中的采样周期相同，也可以与运行参数中的采样周期不同，X(t)为一阶低通滤波器当前时刻的输入信号，在本实施例中X(t)为测量角加速度，t为当前时刻，Y(t-T)为一阶低通滤波基于当前时刻的前一个采样周期对应的输出信号，在本实施例中Y(t-T)为前一采样时刻输出的实际测量角加速度，a＝λ·2πT，λ为截止频率，Y(t)为当前时刻的输出信号，本实施例中Y(t)为当前时刻输出的实际测量角加速度。
S260、将实际测量角加速度和理想角加速度作为贝叶斯滤波器的输入，将贝叶斯滤波器的输出作为目标对象在当前时刻的实际角加速度。
具体的，贝叶斯滤波器的滤波系数可以根据实际情况进行设定。
其中，实际测量角加速度和理想角加速度均满足高斯分布，实际测量角加速度对应的第一方差值大于理想角加速度对应的第二方差值。
示例性的，经过低通滤波器输出的实际测量角加速度可以近似认为满足高斯分布，其可以记为
Figure PCTCN2017103262-appb-000021
其中，
Figure PCTCN2017103262-appb-000022
为t时刻的实际测量角加速度，
Figure PCTCN2017103262-appb-000023
为实际测量角加速度数学期望，Rt为实际测量角加速度对应的第一方差值，其可以通过对历史记录的实际测量角加速度的分析结果确定。同样，理想角加速度也可以近似认为满足高斯分布，其可以记为
Figure PCTCN2017103262-appb-000024
其中，
Figure PCTCN2017103262-appb-000025
为理想角加速度数学期望，Qt为理想角加速度对应的第二方差值，其可以通过对目标对象运行时达到的控制效果进行设定。一般而言，Qt越小，那么在目标对象运行时，对目标对象的控制越精确。通常情况下，Rt大于Qt可以说明理想角加速度的置信度高于实际测量角加速度的置信度。换言之，设置Rt大于Qt，可以保证最终得到的实际角加速度更加准确。
进一步的，经过贝叶斯滤波器将实际测量角加速度和理想角加速度进行融合以得到当前时刻的实际角加速度。一般而言，实际角加速度同样可以认为满足高斯分布，那么，实际角加速度高斯分布可以表示为：
Figure PCTCN2017103262-appb-000026
其中，η为比例系数，也可以称为分布平均数，其可以通过计算得到。
Figure PCTCN2017103262-appb-000027
为实际角加速度，
Figure PCTCN2017103262-appb-000028
为实际角加速度高斯分布，
Figure PCTCN2017103262-appb-000029
为理想角加速度高斯分布，
Figure PCTCN2017103262-appb-000030
为实际测量角加速度高斯分布。
在实际计算过程中，为了简化计算过程，利用贝叶斯滤波器对实际测量角加速度和理想角加速度进行融合时，可以采用下述计算公式：
Figure PCTCN2017103262-appb-000031
其中，
Figure PCTCN2017103262-appb-000032
Rt为实际测量角加速度对应的第一方差值，Qt为理想角加速度对应的第二方差值，t为当前时刻，
Figure PCTCN2017103262-appb-000033
为当前时刻的实际测量角加速度，
Figure PCTCN2017103262-appb-000034
为当前时刻的理想角加速度，
Figure PCTCN2017103262-appb-000035
为计算得到的当前时刻实际角加速度。
下面对本实施例提供的角加速度确定方法进行示例性说明：
假设目标对象为伺服电机，伺服电机初始运行时刻记为0。读取初始运行时刻的初始参数，其具体包括：初始时刻角度，记为θ(0)；初始时刻角速度，记为
Figure PCTCN2017103262-appb-000036
并设定初始时刻实际测量角加速度和实际角加速度均为零，记为
Figure PCTCN2017103262-appb-000037
初始目标角度θ0；初始目标角速度
Figure PCTCN2017103262-appb-000038
初始目标角加速度
Figure PCTCN2017103262-appb-000039
采样周期为T。另一种可选方案，在确定初始运行时刻伺服电机的实际角加速度时，可以将伺服电机上次运行结束时刻的实际角加速度作为本次初始运行时刻的实际角加速度。
进一步的，获取上述初始参数后，根据公式(2-1)至公式(2-6)确定五次多项式法中规划系数a0、a1、a2、a3、a4以及a5的具体值，并根据规划系数构造运动规划方程，即为公式(5)。
将低通滤波器的初始输入设定为
Figure PCTCN2017103262-appb-000040
伺服电机运行后，记录伺服电机的运行时间t，并获取t时刻的运行参数，以根据公式(6)或者公式(7)确定伺服电机在t时刻的测量加速度，并利用低通滤波器根据公式(9)对测量加速度进行滤波，以得到实际测量角加速度。
根据公式(5)确定t时刻伺服电机的理想角加速度。将理想角加速度和实际测量角加速度作为贝叶斯滤波器的输入，利用公式(11)得到伺服电机t时刻的实际角加速度。
进一步的，如果伺服电机继续运行，那么可以根据上述方法持续确定运行 过程中各采样周期对应的采样时刻的实际角加速度，直到伺服电机停止运行为止。
本实施例提供的技术方案，通过在目标对象初始运行时，获取目标对象的初始参数，并根据初始参数构造运动规划公式，并在目标对象运行过程中获取当前时刻的运行参数，以及根据运行规划公式确定当前时刻的理想角加速度，根据运行参数得到测量角加速度并将测量角加速度进行低通滤波以得到实际测量角加速度，并将实际测量角加速度和理想角加速度作为贝叶斯滤波器的输入，以得到目标对象当前时刻的实际角加速度的技术方案，实现了在确定实际角加速度的最终结果时，不仅取决于实际测量角加速度，还取决于当前时刻的理想角加速度，将理想角加速度和实际测量角加速度作为贝叶斯滤波器的输入，可以避免由于实际测量角加速度中随机噪声和误差的比重过大导致结果不准确的技术问题，达到了修正了测量误差，使得最终得到的实际角加速度更加精确的技术效果。
实施例三
图3为本发明实施例三提供的一种角加速度确定装置的结构示意图。参考图3，本实施例提供的角加速度确定装置包括：参数获取模块301、加速度测量模块302以及加速度确定模块303。
其中，参数获取模块301，用于获取目标对象运行过程中当前时刻的运行参数和理想角加速度；加速度测量模块302，用于根据运行参数确定目标对象在当前时刻的实际测量角加速度；加速度确定模块303，用于基于实际测量角加速度和理想角加速度确定目标对象在当前时刻的实际角加速度。
本实施例提供的技术方案，通过在目标对象运行过程中获取当前时刻的运 行参数以及理想角加速度，并根据获取的运行参数确定目标对象在当前时刻的实际测量角加速度，以根据实际测量角加速度和理想角加速度得到目标对象在当前时刻的实际角加速度的技术方案，实现了在确定实际角加速度的最终结果时，不仅取决于实际测量角加速度，还取决于当前时刻的理想角加速度，避免了由于实际测量角加速度中随机噪声和误差的比重过大导致结果不准确的技术问题，达到了修正测量误差，使得最终得到的实际角加速度更加精确的技术效果。
在上述实施例的基础上，加速度测量模块302包括：测量单元3021，用于根据运行参数计算得到目标对象在当前时刻的测量角加速度；滤波单元3022，用于利用低通滤波器对测量角加速度进行滤波，以得到实际测量角加速度。
在上述实施例的基础上，运行参数包括当前运行参数和历史运行参数。
相应的，测量单元3021具体用于：对当前运行参数和历史运行参数进行二次微分计算，以得到测量角加速度，当前运行参数包括：当前时刻、采样周期和目标对象的运行角度，历史运行参数包括：第一预设历史时刻所述目标对象的运行角度；或，对当前运行参数和历史运行参数进行一次微分计算，以得到测量角加速度，当前运行参数包括：当前时刻、采样周期和目标对象的运行角速度，历史运行参数包括：第二预设历史时刻所述目标对象的运行角速度。
在上述实施例的基础上，还包括：初始化模块304，用于获取目标对象运行过程中当前时刻的运行参数和理想角加速度之前，获取目标对象初始运行时刻的初始参数；运动规划模块305，用于利用初始参数按照预设规则构造运动规划公式，以根据运动规划公式确定目标对象在当前时刻的理想角加速度。
在上述实施例的基础上，加速度确定模块303具体用于：将实际测量角加速度和理想角加速度作为贝叶斯滤波器的输入，将贝叶斯滤波器的输出作为目 标对象在当前时刻的实际角加速度。
在上述实施例的基础上，实际测量角加速度和理想角加速度均满足高斯分布，实际测量角加速度对应的第一方差值大于理想角加速度对应的第二方差值。
本实施例提供的角加速度确定装置可以执行上述任意实施例提供的角加速度确定方法，具备相应的功能和有益效果。
实施例四
图4为本发明实施例四提供的一种机器人的结构示意图，如图4所示，该机器人包括处理器40、存储器41、输入装置42和输出装置43；机器人中处理器40的数量可以是一个或多个，图4中以一个处理器40为例；机器人中的处理器40、存储器41、输入装置42和输出装置43可以通过总线或其他方式连接，图4中以通过总线连接为例。其中，处理器40执行所述程序时实现如本发明实施例中的角加速度确定方法。
存储器41作为一种计算机可读存储介质，可用于存储软件程序、计算机可执行程序以及模块，如本发明实施例中的角加速度确定方法对应的程序指令/模块(例如，角加速度确定装置中的参数获取模块301、加速度测量模块302和加速度确定模块303)。处理器40通过运行存储在存储器41中的软件程序、指令以及模块，从而执行机器人的各种功能应用以及数据处理，即实现上述的角加速度确定方法。
存储器41可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序；存储数据区可存储根据机器人的使用所创建的数据等。此外，存储器41可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他非易失性 固态存储器件。在一些实例中，存储器41可进一步包括相对于处理器40远程设置的存储器，这些远程存储器可以通过网络连接至机器人。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
输入装置42可用于接收输入的数字或字符信息，以及产生与机器人的用户设置以及功能控制有关的键信号输入。输出装置43可包括显示屏等显示设备。
实施例五
本发明实施例五还提供一种包含计算机可执行指令的存储介质，所述计算机可执行指令在由计算机处理器执行时用于执行一种角加速度确定方法，该角加速度确定方法包括：
获取目标对象运行过程中当前时刻的运行参数和理想角加速度；
根据所述运行参数确定所述目标对象在当前时刻的实际测量角加速度；
基于所述实际测量角加速度和所述理想角加速度确定所述目标对象在所述当前时刻的实际角加速度。
当然，本发明实施例所提供的一种包含计算机可执行指令的存储介质，其计算机可执行指令不限于如上所述的角加速度确定方法操作，还可以执行本发明任意实施例所提供的角加速度确定方法中的相关操作。
通过以上关于实施方式的描述，所属领域的技术人员可以清楚地了解到，本发明可借助软件及必需的通用硬件来实现，当然也可以通过硬件实现，但很多情况下前者是更佳的实施方式。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如计算机的软盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、 闪存(FLASH)、硬盘或光盘等，包括若干指令用以使得一台计算机设备(可以是机器人，个人计算机，服务器，或者网络设备等)执行本发明各个实施例所述的角加速度确定方法。
值得注意的是，上述角加速度确定装置的实施例中，所包括的各个单元和模块只是按照功能逻辑进行划分的，但并不局限于上述的划分，只要能够实现相应的功能即可；另外，各功能单元的具体名称也只是为了便于相互区分，并不用于限制本发明的保护范围。
应当理解，本发明的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。例如，如果用硬件来实现，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施例或示例中以合适的方式结合。
注意，上述仅为本发明的较佳实施例及所运用技术原理。本领域技术人员会理解，本发明不限于这里所述的特定实施例，对本领域技术人员来说能够进行各种明显的变化、重新调整和替代而不会脱离本发明的保护范围。因此，虽 然通过以上实施例对本发明进行了较为详细的说明，但是本发明不仅仅限于以上实施例，在不脱离本发明构思的情况下，还可以包括更多其他等效实施例，而本发明的范围由所附的权利要求范围决定。

Claims (10)

  1. 一种角加速度确定方法，其特征在于，包括：
    获取目标对象运行过程中当前时刻的运行参数和理想角加速度；
    根据所述运行参数确定所述目标对象在当前时刻的实际测量角加速度；
    基于所述实际测量角加速度和所述理想角加速度确定所述目标对象在所述当前时刻的实际角加速度。
  2. 根据权利要求1所述的角加速度确定方法，其特征在于，所述根据所述运行参数确定所述目标对象在当前时刻的实际测量角加速度包括：
    根据所述运行参数计算得到所述目标对象在当前时刻的测量角加速度；
    利用低通滤波器对所述测量角加速度进行滤波，以得到实际测量角加速度。
  3. 根据权利要求2所述的角加速度确定方法，其特征在于，所述运行参数包括当前运行参数和历史运行参数；
    所述根据所述运行参数计算得到所述目标对象在当前时刻的测量角加速度包括：
    对所述当前运行参数和所述历史运行参数进行二次微分计算，以得到测量角加速度，所述当前运行参数包括：当前时刻、采样周期和目标对象的运行角度，所述历史运行参数包括：第一预设历史时刻所述目标对象的运行角度；或
    对所述当前运行参数和所述历史运行参数进行一次微分计算，以得到测量角加速度，所述当前运行参数包括：当前时刻、采样周期和目标对象的运行角速度，所述历史运行参数包括：第二预设历史时刻所述目标对象的运行角速度。
  4. 根据权利要求1所述的角加速度确定方法，其特征在于，所述获取目标对象运行过程中当前时刻的运行参数和理想角加速度之前，还包括：
    获取目标对象初始运行时刻的初始参数；
    利用所述初始参数按照预设规则构造运动规划公式，以根据所述运动规划 公式确定所述目标对象在当前时刻的理想角加速度。
  5. 根据权利要求1所述的角加速度确定方法，其特征在于，所述基于所述实际测量角加速度和所述理想角加速度确定所述目标对象在所述当前时刻的实际角加速度包括：
    将所述实际测量角加速度和所述理想角加速度作为贝叶斯滤波器的输入，将所述贝叶斯滤波器的输出作为所述目标对象在所述当前时刻的实际角加速度。
  6. 根据权利要求5所述的角加速度确定方法，其特征在于，所述实际测量角加速度和所述理想角加速度均满足高斯分布，所述实际测量角加速度对应的第一方差值大于所述理想角加速度对应的第二方差值。
  7. 一种角加速度确定装置，其特征在于，包括：
    参数获取模块，用于获取目标对象运行过程中当前时刻的运行参数和理想角加速度；
    加速度测量模块，用于根据所述运行参数确定所述目标对象在当前时刻的实际测量角加速度；
    加速度确定模块，用于基于所述实际测量角加速度和所述理想角加速度确定所述目标对象在所述当前时刻的实际角加速度。
  8. 根据权利要求7所述的角加速度确定装置，其特征在于，所述加速度测量模块包括：
    测量单元，用于根据所述运行参数计算得到所述目标对象在当前时刻的测量角加速度；
    滤波单元，用于利用低通滤波器对所述测量角加速度进行滤波，以得到实际测量角加速度。
  9. 一种机器人，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现如权利要求1-6中任一所述的角加速度确定方法。
  10. 一种包含计算机可执行指令的存储介质，其特征在于，所述计算机可执行指令在由计算机处理器执行时用于执行如权利要求1-6中任一所述的角加速度确定方法。
PCT/CN2017/103262 2017-05-18 2017-09-25 角加速度确定方法、装置、机器人及存储介质 WO2018209861A1 (zh)

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