JP2013113661A - External force detection device, robot control system and external force detection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an external force detection device, a robot control system and an external force detection method, etc. for performing external force detection with high accuracy when external force is modulated by a machine mechanism provided at the tip of a force sensor.SOLUTION: An external force detection device 30 includes: an acquisition part 32 which acquires sensor information output from a force sensor 10; and a correction part 34 which performs correction processing to the acquired sensor information, in which the force sensor 10 is provided with a machine mechanism (such as a hand 110) which converts external force f to be transmitted to the force sensor 10 as force F, and the correction part 34 performs inverse transformation of conversion by the machine mechanism as correction processing.

Description

  The present invention relates to an external force detection device, a robot control system, an external force detection method, and the like.

  Conventionally, a force sensor that acquires force acting on a sensing unit as sensor information and various systems using the force sensor are known.

  For example, in the field of robot control, a system that performs force control represented by impedance control is conceivable. Impedance control is a control method for operating a robot manipulator as if it had a value suitable for work regardless of its actual mass, viscosity, and elasticity. Specifically, a solution of the equation of motion is obtained based on force information obtained from a force sensor provided in the manipulator, and the manipulator is operated according to the solution.

  Impedance control allows you to control force in addition to position control, such as tracing the surface of an object, fitting one object to another object, grasping a soft object without breaking it, etc. It becomes possible to correspond to the scene.

  Patent Document 1 discloses a technique for performing impedance control with high accuracy even in a very complicated system.

JP-A-6-320451

  In the force control using the force sensor disclosed in Patent Document 1 or the like, it is assumed that the sensor information of the force sensor accurately represents the magnitude of the external force. However, when there is some structure, such as a robot hand, before the force sensor, it is necessary to accurately acquire the external force that the hand receives in force control, whereas the external force depends on the structure of the hand. Due to the modulation, the force sensor detects the external force after the modulation.

  If the hand is mechanically highly rigid, the degree of this modulation is small, but if the hand is low in rigidity, the degree of modulation becomes large, and the impedance control based on the modulated external force does not become a desired operation.

  According to some aspects of the present invention, when an external force is modulated by a mechanical mechanism provided at the tip of a force sensor, an external force detection device that performs highly accurate external force detection, a robot control system, an external force detection method, and the like Can be provided.

  One aspect of the present invention includes an acquisition unit that acquires sensor information output from a force sensor, and a correction unit that performs a correction process on the acquired sensor information. The force sensor includes an external force A mechanical mechanism that converts f and transmits the force F to the force sensor is provided, and the correction unit relates to an external force detection device that performs reverse conversion of the conversion by the mechanical mechanism as the correction processing.

  In one embodiment of the present invention, the force sensor is provided with a mechanical mechanism, and the mechanical mechanism converts the external force f and transmits the force F to the force sensor. In that case, it is possible to accurately obtain the external force f actually applied to the mechanical mechanism by performing a correction process corresponding to the reverse conversion of the conversion by the mechanical mechanism on the acquired sensor information.

  In the aspect of the invention, the correction unit may perform the correction process using an inverse conversion formula of the conversion formula when the conversion in the mechanical mechanism is modeled by a predetermined conversion formula. Also good.

  As a result, the conversion can be modeled by a predetermined conversion equation, and correction processing can be easily performed by using the inverse conversion equation of the conversion equation.

  In one aspect of the present invention, the correction unit uses the inverse transformation equation of the ordinary differential equation when the transformation in the mechanical mechanism is modeled using an ordinary differential equation as the transformation equation. The correction process may be performed.

  This makes it possible to use an ordinary differential equation as the conversion equation.

  In the aspect of the invention, the correction unit may model the conversion in the mechanical mechanism using an equation of motion having a mass term, a viscosity term, and an elastic term as coefficient parameters as the conversion formula. In addition, the correction processing may be performed using the inverse transformation formula of the equation of motion.

  This makes it possible to use an equation of motion as the conversion equation.

  In the aspect of the invention, the correction unit may perform the correction process by digital filter processing.

  As a result, the correction process can be converted into a digital filter, and hardware can be facilitated.

In one aspect of the present invention, the correction unit sets the sensor information value at the nth (n is an integer of 3 or more) timing as F _n , and the intermediate parameter at the ( _{n−1) th} timing as x _n−1. And when the coefficient parameters of the digital filter processing are α and β, the intermediate parameter x _n at the n-th timing is obtained by x _n = αF _n + βx _n−1 and the obtained intermediate parameter x _n , the intermediate parameter x _n−1 obtained at the _n−1 th timing, the intermediate parameter x _n−2 obtained at the n−2 th timing, and the coefficient parameter C of the digital filter processing _0, from _{C 1, C 2, f n} = - by _{{x n (C 1 x n} -1 + C 2 x n-2)} / C 0, the first n It may be obtained the sensor information f _n after the correction processing in the timing.

  This makes it possible to execute the correction process specifically using the above-described equation.

  In one aspect of the present invention, the acquisition unit acquires information corresponding to the force F as the sensor information, and the correction unit performs the correction process on the sensor information, whereby the external force is acquired. Information corresponding to f may be acquired.

  Thereby, it is possible to acquire the external force f by performing the correction process on the force F.

  In the aspect of the invention, the mechanical mechanism may be a robot end effector.

  As a result, even when a robot end effector is used as a mechanical mechanism, it is possible to perform the above correction processing.

  According to another aspect of the present invention, the external force detection device according to any one of the above, and a control unit that performs a robot control process based on the sensor information on which the correction process has been performed in the external force detection device, Related to the robot control system including.

  Thereby, it becomes possible to control the robot using the processing result of the external force detection device.

  In one aspect of the present invention, the control unit outputs a correction value of a target value of the robot based on the sensor information on which the correction process has been performed in the external force detection device; And a robot control unit that performs feedback control of the robot based on the target value corrected by the correction value.

  This makes it possible to perform force control as robot control.

  Another aspect of the present invention is an external force detection method for performing correction processing on sensor information output from a force sensor provided with a mechanical mechanism that converts an external force f and transmits it as a force F. The present invention relates to an external force detection method that acquires the sensor information from the force sensor and performs reverse conversion of conversion by the mechanical mechanism as the correction process on the acquired sensor information.

A configuration example of a force sensor. A specific example in which a mechanical mechanism is provided at the tip of a force sensor. 1 is a configuration example of an external force detection device, a robot control system, and a robot system including them according to the present embodiment. An example of a robot system. An example of mechanical mechanism modeling. The figure explaining the modulation | alteration in a mechanical mechanism. An example of a digital filter used for correction processing. Another example of a digital filter used for correction processing. Another example of a digital filter used for correction processing. FIG. 10A to FIG. 10C are explanatory diagrams of force control. FIG. 11A and FIG. 11B are explanatory diagrams regarding compliance control. 12A and 12B are explanatory diagrams of impedance control. The figure explaining the relationship between the characteristic of a mechanical mechanism, and the characteristic implement | achieved by force control. The flowchart for demonstrating the process in an external force detection apparatus.

  Hereinafter, this embodiment will be described. In addition, this embodiment demonstrated below does not unduly limit the content of this invention described in the claim. In addition, all the configurations described in the present embodiment are not necessarily essential configuration requirements of the present invention.

1. First, the method of this embodiment will be described. A configuration example of a force sensor used in this embodiment is shown in FIG. Although various configurations can be considered for the force sensor, basically, the external force is detected by measuring a minute deformation of the sensing unit due to the external force by some method. As a deformation measuring method, a method using a strain gauge, a method using an electrostatic sensor, a method using an optical sensor, a method using a piezoelectric element such as a crystal element, and the like can be considered.

As shown in FIG. 1, the force sensor can be modeled by modeling the mechanical structure of the force sensor. When the equivalent mass term of the force sensor is m ₀ , the equivalent viscosity term is μ ₀ , and the equivalent elastic term is k ₀ , the characteristic can be expressed as the following equation (1).

Here, x represents the deformation (displacement) of the sensing unit measured by the deformation measurement method (specific example is as described above), and F represents the external force received by the force sensor. That is, since the equivalent mass term m ₀ , equivalent viscosity term μ ₀ , and equivalent elastic term k ₀ of the force sensor can be known by design, the external force F is obtained from the above equation (1) by measuring the displacement x. can do. The force sensor outputs F as sensor information.

However, in practice, since the elastic term k ₀ is made relatively large, the time differential term becomes relatively small, and it is generally unnecessary to explicitly consider the equation of motion. If the elastic term is not relatively large (that is, if the force sensor is not made very hard), the deformation of the sensing unit will be large, and accordingly the space of the structure provided at the tip of the force sensor This is because the target position fluctuates. For example, in the case of a robot system, it is assumed that a hand is provided at the tip of the force sensor, but if the force sensor is not hard, the spatial position of the hand, that is, the hand position of the robot will fluctuate. The accuracy of position control will deteriorate.

  From the above, although a model of the force sensor is shown in FIG. 1, it is not necessary to consider such a model in this embodiment, and it is handled that there is no deformation of the sensing unit of the force sensor. May be.

  The problem in this embodiment is that a mechanical mechanism (a robot hand in the example of FIG. 2) is provided at the tip of the force sensor as shown in FIG. 2, and the rigidity of the mechanical mechanism is larger than that of the force sensor. This is the case. In such a case, the external force f applied to the mechanical mechanism undergoes conversion (modulation) by the mechanical mechanism and is transmitted to the force sensor as a force F. As an example, if the mechanical mechanism is a flexible structure, a part of the energy generated by f is used for deformation of the flexible structure, so that the force F transmitted to the force sensor is smaller than the external force f. Can be considered.

  As described above, F, which is the output value of the force sensor, does not need to take into account deformation of the force sensor itself. That is, it may be considered that the force transmitted from the mechanical mechanism to the force sensor is accurately reflected in the sensor information. However, what the system actually wants to acquire is not the force F but the external force f before conversion. In the case of a robot control system as shown in FIG. 2, force control should be performed based on the force applied to the workpiece to be processed by the hand, and the force is equal to the force transmitted from the workpiece to the hand as a reaction force. This is nothing but the external force f in FIG. That is, if the sensor information of the force sensor is used as it is, desired force control cannot be performed, which is not preferable. Even in a system other than the robot control system, external force exchange should be performed in a mechanical mechanism provided before the force sensor, and conversion of external force by the mechanical mechanism cannot be ignored.

  If the rigidity of the mechanical mechanism is high, the influence of the conversion on the external force f by the mechanical mechanism is reduced. However, there are cases where other advantages are produced by using a mechanical mechanism with low rigidity, so the rigidity of the mechanical mechanism is not necessarily high. I can't make it. Hereinafter, a specific example will be described using a robot control system.

  The robot to be controlled by the robot control system is generally highly rigid in order to improve the accuracy of the spatial position of the hand (the position of the hand of the robot). In addition, when soft characteristics are required (for example, when gripping a flexible object without destroying it), force control such as impedance control is performed to control the robot softly. For example, control for reducing the apparent elasticity term or the like may be performed.

  However, in such control, soft characteristics are only realized by force control, and if the control unit that performs force control stops operation for some reason, the robot's original machine Characteristic will appear and the rigidity will be high. That is, when an operator contacts the robot while the control unit is stopped, it is very difficult to push back the highly rigid robot. There is also a problem of collision with other robots and devices.

  Therefore, it is conceivable to soften the original mechanical characteristics of the robot, such as configuring the robot hand with a flexible structure. In this way, even if the control unit stops for some reason, the original mechanical characteristics of the robot appearing at that time will be soft, so it is possible to cope with contact with workers etc. Easy. If the accuracy of the hand position is required, it is sufficient to realize a visually stiff characteristic by force control such as impedance control.

  From the above, a mechanical mechanism with low rigidity may be provided at the tip of the force sensor, and in that case, conversion to an external force by the mechanical mechanism becomes a problem. Therefore, the present applicant proposes a method of performing correction processing corresponding to the inverse conversion of the conversion by the mechanical mechanism on the sensor information from the force sensor. By using this method, it becomes possible to accurately detect external force from the sensor information of the force sensor, and in various systems that perform processing based on the external force, processing in the system can be performed appropriately. .

  Hereinafter, after describing an example of the system configuration of the external force detection device, etc., modeling of the mechanical mechanism and inverse conversion of the conversion by the mechanical mechanism will be described. Further, after describing a method for converting the inverse transformation process into a digital filter, a specific example of impedance control in the robot control system will be described, and finally, details of the process will be described using a flowchart.

  In the following description, a robot control system is used as a specific example, but the external force detection device of the present embodiment is not prevented from being used in a system other than the robot control system.

2. System Configuration Example FIG. 3 shows a configuration example of a robot system including the external force detection device 30 of the present embodiment. The present embodiment can also be applied to a robot control system including a force control unit 20, a target value output unit 60, and a robot control unit 80 in addition to the external force detection device 30. Note that the external force detection device and the robot control system of the present embodiment are not limited to the configuration shown in FIG. 3, and various modifications such as omitting some of the components or adding other components are possible. is there.

  The external force detection device 30 of the present embodiment performs a correction process on the sensor information from the force sensor 10 to detect an accurate external force. The external force detection device 30 includes an acquisition unit 32 and a correction unit 34.

  The acquisition unit 32 acquires sensor information from the force sensor 10. The acquisition unit 32 may be realized as an interface with the force sensor 10, for example, and may directly acquire sensor information. In the case of the configuration shown in FIG. 2, it is conceivable that the force sensor 10 detects a force other than an external force due to its own weight, posture, etc., such as the mechanical mechanism (hand 110) or the arm 120. Therefore, the acquisition unit 32 may acquire information obtained by performing preprocessing such as self-weight posture correction on the sensor information. Alternatively, although not shown in FIG. 3, the external force detection device 30 includes a preprocessing unit, and the preprocessing unit performs its own weight posture correction on the information acquired by the acquisition unit 32, and information after the preprocessing is performed. However, the correction process may be performed by the correction unit 34.

  The correction unit 34 performs correction processing on the sensor information acquired by the acquisition unit (including information that has been preprocessed after acquisition). In the correction unit 34, assuming that the external force f received by the mechanical mechanism is converted into the force F by the mechanical mechanism and transmitted to the force sensor 10, a correction process corresponding to the inverse conversion of the conversion by the mechanical mechanism is performed. To obtain the external force f. The mechanical mechanism itself and the conversion in the mechanical mechanism are modeled, and the inverse conversion is obtained based on the modeling. Details will be described later.

  The robot control system of the present embodiment includes a force control unit 20, an external force detection device 30, a target value output unit 60, and a robot control unit 80.

  The force control unit 20 performs force control (force control) based on the sensor information from the force sensor 10 and outputs a correction value for the target value. More specifically, the force control unit 20 performs impedance control (or compliance control) based on sensor information (force information, moment information) from the force sensor 10.

  The force control unit 20 can include an impedance processing unit 22 and a control parameter storage unit 24. The impedance processing unit 22 performs impedance control as force control. A specific method of impedance control will be described later. The control parameter storage unit 24 stores control parameters used in force control (impedance control).

  The target value output unit 60 outputs a target value for feedback control of the robot (manipulator in a narrow sense). Based on this target value, feedback control of the robot 100 is realized. Taking an articulated robot or the like as an example, this target value is information on the joint angle of the robot. The joint angle information of the robot is information representing the angle of each joint (angle formed by the joint axis) in the link mechanism of the robot arm, for example.

The target value output unit 60 can include a trajectory generation unit 62 and an inverse kinematics processing unit 64. The trajectory generator 62 outputs the trajectory information of the robot. The trajectory information can include position information (x, y, z) of the end effector section (end point) of the robot and rotation angle information (u, v, w) about each coordinate axis. The inverse kinematics processing unit 64 performs inverse kinematics processing based on the trajectory information from the trajectory generation unit 62, and outputs, for example, robot joint angle information as a target value. The inverse kinematics process is a process for calculating the motion of a robot having a joint, and is a process for calculating joint angle information and the like by inverse kinematics from the position and orientation of the end effector unit of the robot.

  The robot control unit 80 performs feedback control of the robot based on the target value from the target value output unit 60. Specifically, the feedback control of the robot is performed based on the target value output as a result of the correction process based on the correction value from the force control unit 20. For example, feedback control of the robot 100 is performed based on the target value and a feedback signal from the robot 100.

  The robot system according to this embodiment includes the robot control system described above and the robot 100 (force sensor 10). The force sensor 10 is as described above.

  The robot 100 includes a hand 110 (mechanical mechanism) and an arm 120. Specifically, as shown in FIG. 2, it is assumed that the force sensor 10 is provided on the arm 120 and the hand 110 is provided at the tip of the force sensor 10. The robot 100 may have a motor control unit (not shown in FIG. 3), and the motor control unit sets a joint angle of the arm 120, for example. The robot control unit 80 controls the hand 110, the arm 120, and the like of the robot 100, but actually acquires the value of the joint angle information as a target value and controls the motor control unit based on the target value. It will be.

  FIG. 4 shows an example of a robot system including the robot control system of this embodiment. This robot system includes a control device 300 (information processing device) and a robot 310 (robot 100 in FIG. 3). The control device 300 performs control processing for the robot 310. Specifically, control for operating the robot 310 is performed based on the operation sequence information (scenario information). The robot 310 includes an arm 320 and a hand (gripping unit) 330. Then, it operates according to an operation instruction from the control device 300. For example, operations such as gripping or moving a workpiece placed on a pallet (not shown) are performed. Further, information such as the posture of the robot and the position of the workpiece is detected based on captured image information acquired by an imaging device (not shown), and the detected information is sent to the control device 300.

  The robot control system according to the present embodiment is provided in, for example, the control device 300 in FIG. 4. For example, the robot control system is realized by hardware or a program of the control device 300. According to the robot control system of this embodiment, it is possible to reduce performance requirements for control hardware such as the control device 300 and to operate the robot 310 with high responsiveness. Although FIG. 4 shows an example of a single arm type, a multi-arm type robot such as a double arm type may be used.

3. Modeling and Inverse Transformation A technique for describing the modulation (transformation) in the mechanical mechanism by modeling the characteristics of the mechanical mechanism, and obtaining the inverse transformation, which is correction processing performed by the correction unit 34 based on the modulation (conversion) will be described.

  Although various mechanical mechanism modeling methods are conceivable, in this embodiment, as shown in FIG. 5, an object having a mass m is connected to the force sensor 10 by a damper having a viscosity coefficient μ and a spring having an elastic coefficient k. Approximate with the structure. By modeling in this way, as shown in FIG. 6, the conversion in the mechanical mechanism is expressed by the following expression (2).

  Here, x represents the displacement of the mechanical mechanism, and the above equation (2) is nothing but an equation of motion. About this, as shown in FIG. 5, it can be considered that the mechanical mechanism is regarded as a structure including a mass object, a damper, and a spring. Alternatively, the characteristics of the mechanical mechanism can be expressed by a linear combination of the 1st to Nth derivative terms of x and x as in the following equation (3), but the second derivative term in the following equation (3) is used. It can also be regarded as an approximate expression.

  Next, the relationship with the converted force F transmitted to the force sensor 10 will be considered. Assuming that the force sensor 10 is fixed, the force F is equal to the external force f minus the inertia term, and is expressed by the following equation (4).

  The following expression (5) is derived from the above expressions (2) and (4).

  In other words, the above equation (5) represents the balance of forces on the surface indicated by C1 in FIG. When the external force f acts on the object indicated by C2 in FIG. 5, if the behavior of the mechanical mechanism is taken into consideration, the influence of the inertia due to the object of C2 cannot be ignored, so the inertia term is included as in the above equation (2). The obtained relational expression is acquired. However, when considering the balance of forces on the surface indicated by C1 (that is, when considering the force transmitted to the force sensor 10), the object of C2 is not physically connected directly to the surface of C1. The inertia due to the object does not need to be taken into consideration, and the above expression (4) represents it. Alternatively, the force received by the surface of C1 may be considered to be limited to that received from a physically connected damper and spring, and the above equation (5) can be directly derived from such a view.

  In any case, the relationship between f and F is determined from the above equations (2) and (5). The conversion by the mechanical mechanism can be regarded as a system that takes f as an input and outputs F based on the above equations (2) and (5). Therefore, the inverse transformation may be regarded as a system that takes F as an input and obtains f based on the above equations (5) and (2). Specifically, F is acquired as sensor information, and x is obtained by solving the differential equation of the above equation (5). Then, the obtained x may be substituted into the above equation (2) to obtain f.

4). Digital Filtering As described above, in order to obtain the external force f from F, the linear ordinary differential equations of the above equations (2) and (5) are solved. Conventionally, a Newton method, a Runge-Kutta method, or the like has been used to obtain a solution of a linear ordinary differential equation. However, these methods are not suitable for hardware and it is difficult to determine stability. Therefore, the present applicant uses a digital filter as a method for solving a linear ordinary differential equation.

  Here, the step of obtaining the solution of the ordinary differential equation is regarded as a filter that outputs a solution (displacement x in the above equation (5)) with respect to the input of the input value (sensor information of the force sensor). Then, from the form of the above equation (5), it can be considered as a one-pole analog filter.

  That is, since the solution of the ordinary differential equation can be obtained as the output of the analog filter, the ordinary differential equation can be solved by the digital filter by converting the analog filter into a digital filter.

  Various methods for converting an analog filter into a digital filter are known. For example, an impulse invariance method may be used. This is a technique for considering a digital filter that gives the same impulse response as the value obtained by sampling the impulse response of an analog filter at a discrete time T. Since the Impulse Invariance method is a known method, detailed description thereof is omitted.

  As a result, the solution of the ordinary differential equation can be obtained as the output of the digital filter. If it is the above formula (5), it becomes a 1-pole digital filter as shown in FIG. In FIG. 7, d is a delay for one sample, and α and β are filter coefficients. The filter of FIG. 7 is represented by the following formula (6).

x _n = αF _n + βx _n−1 (6)
Similarly, the equation of motion of the above equation (2) can be digitally filtered, and the equation of motion is a two-pole digital filter as shown in FIG. In FIG. 8, C0, C1, and C2 are filter coefficients, which are expressed in the following equation (7).

_{x n = C 0 f n +} C 1 x n-1 + C 2 x n-2 ····· (7)
If it is a process using a digital filter, it is easy to implement hardware and it is easy to determine stability. This is because the stability of the digital filter can be easily determined by whether or not the pole of the digital filter is inside the unit circle.

  The filter coefficients α, β, C0, C1, and C2 are determined by the characteristics of the mechanical mechanism. In this case, the mass term m, the viscosity term μ, and the elastic term k (in some cases, in addition to the above) The driving frequency T of the digital filter may be used. Since the characteristics of the mechanical mechanism (hand 110) are known by design, the filter coefficient can be obtained in advance. Further, even when considering replacing a plurality of hands 110, if filter coefficients corresponding to the respective hand characteristics are obtained, it is possible to easily cope with them by switching the filter coefficients. Therefore, the Runge-Kutta It is superior to conventional methods such as law.

  The above equations (6) and (7) can be transformed into the following equation (8).

_{C 0 f n = αF n +} βx n-1 - (C 1 x n-1 + C 2 x n-2) ····· (8)
FIG. 9 illustrates the above equation (8). By using the digital filter of FIG. 9, it is possible to realize a correction process (inverse conversion) in which the force F detected by the force sensor 10 is input and the external force f received by the mechanical mechanism is output.

5. Specific Example of Impedance Control According to the method described above, a mechanical mechanism with low rigidity is provided at the tip of the force sensor 10, and the external force f and the force F received by the force sensor 10 differ depending on the modulation by the mechanical mechanism. Even in such a case, it is possible to accurately detect the external force f by performing inverse transformation on F.

  Here, a robot control system that performs force control (impedance control) will be described as an example of a system that performs control using the external force f obtained by the correction processing. Here, description of feedback control based on the target value (corresponding to processing in the target value output unit 60 and the robot control unit 80) is omitted, and the impedance performed by the force control unit 20 (impedance processing unit 22 in a narrow sense). Control will be described.

  FIG. 10A shows a state in which the object OB is moved between the left arm AL and the right arm AR of the robot. For example, with position control alone, there is a risk of dropping or destroying an object. With force control, a flexible object or a fragile object is sandwiched with appropriate force from both sides as shown in FIG. It can be moved.

  Further, according to the force control, as shown in FIG. 10B, it is possible to trace the surface SF of an uncertain object with the arm AM or the like. Such control is impossible or very difficult by position control alone. Further, according to the force control, as shown in FIG. 10C, after rough positioning, it is possible to probe and align the object OB into the hole HL.

  However, there is a problem that the application is limited in force control using actual mechanical parts such as a spring. In addition, in such force control using mechanical parts, it is difficult to dynamically switch characteristics.

  On the other hand, torque control for controlling the torque of the motor is simple, but there is a problem that the positional accuracy is deteriorated. In addition, a problem such as a collision occurs when an abnormality occurs. For example, in FIG. 10A, when an abnormal situation occurs and the object OB is dropped, there is no reaction force to be balanced in the torque control, so the left and right arms AL and AR collide. Problems arise.

  On the other hand, impedance control (compliance control) has the advantage of high versatility and safety.

  FIG. 11A and FIG. 11B are diagrams for explaining compliance control, which is one type of impedance control. Compliance means the reciprocal of the spring constant, and the spring constant represents hardness, whereas compliance means softness. Control that provides compliance, which is mechanical flexibility, when interaction between the robot and the environment works is called compliance control.

  For example, in FIG. 11A, a force sensor SE is attached to an arm AM of the robot, and the arm AM has joint portions J1 and J2. The robot arm AM is programmed so that its posture changes according to sensor information (force / torque information) obtained by the force sensor SE. Specifically, the virtual spring indicated by A1 in FIG. 11A controls the robot as if it is attached to the tip of the arm AM.

  For example, it is assumed that the spring constant of the spring indicated by A1 is 100 kg / m. If this is pressed with a force of 5 kg as shown at A2 in FIG. 11B, the spring contracts by 5 cm as shown at A3. In other words, if it shrinks by 5 cm, it can be said that it is pushed with a force of 5 kg. That is, force information and position information are associated with each other.

  In the compliance control, control is performed as if the virtual spring indicated by A1 is attached to the tip of the arm AM. Specifically, the robot operates in response to the input of the force sensor SE, and is controlled to move back by 5 cm as shown in A3 with respect to the 5 kg weight shown in A2, corresponding to the force information. The position information is controlled to change.

  Such simple compliance control does not include a time term, but the control including the time term and considering the second order term is impedance control. Specifically, the second-order term is a mass term, the first-order term is a viscosity term, and the impedance control model can be expressed by an equation of motion as shown in the following equation (9).

In the above equation (9), m _I is mass, μ _I is a viscosity coefficient, k _I is an elastic coefficient, f is a force (an external force acquired by the correction process in the correction unit 34), u is a displacement from the target position. is there. The first and second derivatives of u correspond to speed and acceleration, respectively. In the impedance control, a control system for providing the characteristic of the above equation (9) to the end effector section that is the tip of the arm is configured. That is, control is performed as if the tip of the arm has the virtual mass, virtual viscosity coefficient, and virtual elastic coefficient represented by the above equation (9).

  As described above, impedance control is control that makes a contact with an object with a viscosity coefficient and an elastic coefficient set as an object in a model in which a viscous element and an elastic element are connected to the mass of the tip of the arm in each direction. .

  For example, as shown in FIG. 12A, let us consider a control in which an object OB is grasped by robot arms AL and AR and moved along a trajectory TR. In this case, the trajectory TRL is a trajectory through which the point PL set inside the left side of the object OB passes, and is a virtual left-hand trajectory determined on the assumption of impedance control. The trajectory TRR is a trajectory through which the point PR set inside the right side of the object OB passes, and is a virtual right-hand trajectory determined on the assumption of impedance control. In this case, the arm AL is controlled so that a force corresponding to the distance difference between the tip of the arm AL and the point PL is generated. The arm AR is controlled so that a force corresponding to the distance difference between the tip of the arm AR and the point PR is generated. In this way, it is possible to realize impedance control that moves the object OB while grasping it softly. In the impedance control, even if the situation where the object OB falls as shown by B1 in FIG. 12A occurs, the arms AL and AR have their tips at points PL and PR as shown by B2 and B3. It is controlled to stop at the position. That is, if the virtual trajectory is not a collision trajectory, it is possible to prevent the arms AL and AR from colliding.

  In addition, as shown in FIG. 12B, when the control is performed so that the surface SF of the object is traced, the impedance control is performed according to the distance difference DF between the virtual trajectory TRVA and the tip with respect to the tip of the arm AM. It is controlled so that the applied force works. Therefore, the arm AM can be controlled to trace the surface SF while applying a force.

By performing the impedance control as described above, as shown in FIG. 13, it can be controlled as if it had mass m _I , viscosity μ _I , and elasticity k _I. For this reason, the robot 100 as a whole exhibits characteristics that are obtained by synthesizing the characteristics (m _I , μ _I , k _I ) that are apparently obtained by the control and the actual characteristics (m, μ, k) of the mechanical mechanism. .

In normal impedance control, the mechanical mechanism (hand 110) is highly rigid, and it is not necessary to consider the characteristics (m, μ, k) of the mechanical mechanism, and therefore target characteristics (m _I , μ _{I in the} control). , K _I ) is a desired characteristic. On the other hand, when the influence of the characteristics of the mechanical mechanism cannot be ignored as in the present embodiment, the target characteristics in the control and the characteristics of the entire robot 100 that actually appear are different. It should be noted that must be determined.

  Also, the above equation (9) can be converted to a digital filter in the same manner as the correction process in the correction unit 34.

6). Details of Processing Processing performed by the external force detection device 30 will be described with reference to the flowchart of FIG. When this process is started, first, acquisition of sensor information from the force sensor 10 is waited (S101). The waiting time is determined according to the sensor information output rate of the force sensor 10. Here, it is assumed that the acquisition process and the correction process in the external force detection device 30 are performed for each output of the sensor information of the force sensor 10. However, when reducing power consumption or the like, the processing may be performed for each of a plurality of outputs.

After waiting for input, sensor information is acquired (S102). As described above, the sensor information corresponds to the force F (external force modulated by the mechanical mechanism). Then, correction processing is performed based on the acquired force F (S103). Here, x is an intermediate parameter and physically corresponds to the deformation (displacement) of the mechanical mechanism. Specifically, the past values of x (x _n−1 and x _n−2 ) are updated, and the current value of x (x _n ) is obtained from the updated x _n−1 and F _n . Then, the _{x n} obtained, thereby obtaining the _{f n} from the updated _{x n-1, x n-2} Prefecture.

Then, outputs _{f n} obtained as corrected external force (S104), and determines whether the process ends (S105). If No in S105, the process returns to S101 and continues. If Yes in S105, the process ends.

  The output external force f is used for control in an arbitrary system. For example, in the robot control system described above, force control (impedance control) is performed based on f. However, since impedance control is a known technique, description using a flowchart is omitted.

  In the above embodiment, as shown in FIG. 3, the external force detection device 30 has an acquisition unit 32 that acquires sensor information from the force sensor 10 and a correction unit 34 that performs a correction process on the acquired sensor information. Including. As shown in FIG. 2, the force sensor 10 is provided with a mechanical mechanism that converts the external force f and transmits the force F to the force sensor 10. And the correction | amendment part 34 performs reverse conversion of conversion by a mechanical mechanism as a correction process.

  Here, the external force f represents the force received by the mechanical mechanism, and the force F represents the force received by the force sensor 10 as a result of the modulation of the external force f by the mechanical mechanism. However, the force sensor 10 receives a force such as gravity due to its own weight or posture such as a mechanical mechanism. Therefore, the sensor information output from the force sensor 10 may include not only the force F resulting from the modulation of the external force f but also other forces. In such a case, it is necessary to obtain the force F by removing other forces by performing a self-weight posture correction process or the like on the sensor information.

  Thereby, even when the external force f is modulated (converted) into the force F by the mechanical mechanism, the external force f can be accurately obtained. Since it is assumed that what is necessary for the control in the system is a force that is actually exchanged with the outside, information useful in the control can be acquired by performing the processing of this embodiment.

  Moreover, the correction | amendment part 34 may perform a correction | amendment process using the inverse conversion type | formula of a conversion type, when conversion in a mechanical mechanism is modeled by a predetermined conversion type | formula. Here, the predetermined conversion equation may be an ordinary differential equation. Specifically, as shown in FIG. 6, an equation of motion having a mass term, a viscosity term, and an elastic term as coefficient parameters may be used.

  Here, the process of modeling the conversion in the mechanical mechanism with a conversion formula is, for example, the process of modeling the physical characteristics of the mechanical mechanism and formulating the conversion based on the model of the obtained characteristics. Good. In the modeling, it is not necessary to obtain a model that completely reproduces the transformation (or the characteristics of the mechanical mechanism), and it is sufficient to obtain an approximate model. When the characteristics of the mechanical mechanism are modeled with m, μ, and k, the model is the actual mechanical mechanism except when the mechanical mechanism itself is formed of an object having mass, a damper, and a spring. However, there is no problem as long as accuracy can be secured in the subsequent control. Specifically, the mechanical mechanism may not be modeled by a mathematical expression (or mathematical expression such as an infinite series) using up to a high-order differential term, and may be approximated up to a secondary differential term. In that case, the conversion formula corresponds to the equation of motion.

  As a result, modeling can be performed to facilitate processing. If the transformation can be expressed in some form, the inverse transformation corresponding to the correction processing in the present embodiment can be derived therefrom. In particular, when the deformation equation is an ordinary differential equation (linear ordinary differential equation in a narrow sense), a method for obtaining a solution on the system is widely known and can be easily processed. If the equation of motion is one of linear ordinary differential equations, the coefficient can be obtained in association with the mass, viscosity, elasticity, etc. of the mechanical mechanism.

  Further, as shown in FIG. 9, the correction unit 34 may perform correction processing by digital filter processing.

  This makes it possible to convert the correction process into a digital filter. By using a digital filter, hardware and stability can be easily determined.

Further, as shown in the above equation (6), the correction unit 34 sets the sensor information value at the nth (n is an integer of 3 or more) timing to F _n , and the intermediate parameter at the n−1th timing to x _{When n−1} and the coefficient parameters of the digital filter processing are α and β, the intermediate parameter x _n at the nth timing may be obtained by x _n = αF _n + βx _n−1 . Then, as shown in the above equation (7), the obtained x _n , the intermediate parameter x _n−1 obtained at the ( _n−1) th timing, and the intermediate parameter x _n obtained at the (n−2) th timing. _-2, the coefficient of the digital filter parameters _{C 0, C 1, C 2} , f n = - by _{{x n (C 1 x n} -1 + C 2 x n-2)} / C 0, of the n Sensor information (external force) f _n after correction processing at timing is obtained.

  Thereby, the external force f can be obtained from F based on the above equations (6) and (7). FIG. 9 is a digital filter of this process.

  The acquisition unit 32 may acquire information corresponding to the force F as sensor information. And the correction | amendment part 34 acquires the information corresponding to the external force f by performing a correction process with respect to sensor information.

  As a result, it is possible to obtain the external force f received by the mechanical mechanism from F which is sensor information (however, if the weight correction is taken into account, it corresponds to information after correction). As described above, since it is assumed that it is the external force f that is desired to be used in the system, it is important to accurately obtain the external force f.

  The mechanical mechanism may be an end effector of the robot 100.

  Here, the end effector refers to, for example, a mechanical mechanism that is provided at the tip of the arm 120 and performs an operation on an object (workpiece or the like). However, in view of the fact that this embodiment proposes a technique for performing correction processing for conversion to external force by a mechanical mechanism provided before the force sensor 10, the machine of this embodiment The mechanism is not limited to the end effector. For example, assuming that the robot has a shoulder joint, an elbow joint, and a wrist joint, such as a person, if the force sensor 10 is provided at the elbow joint part, in addition to the end effector, the front of the elbow It is possible to think of the mechanical mechanism of the present embodiment including a portion (that is, a part of the arm 120).

  Further, as the end effector, for example, a hand 110 having a structure like a human finger and performing operations such as grasping, grasping, and pinching is conceivable, but is not limited thereto. It may be a suction hand that does not have a finger-like structure, or may be a suction tweezer suitable for a finer movement. The work content of the end effector is not limited to gripping or moving. Therefore, the end effector may be a welding gun that performs a welding operation or the like, or may be a spray gun that performs a painting operation or the like, and various other forms are conceivable.

  As a result, even when the mechanical mechanism is an end effector of the robot 100 (for example, the hand 110 of the robot 100), the correction processing in the external force detection device 30 of the present embodiment can be applied.

  Further, as shown in FIG. 3, the present embodiment described above performs the robot control processing based on the external force detection device 30 described above and the sensor information (external force f) corrected in the external force detection device 30. The present invention can be applied to a robot control system including a control unit for performing. Specifically, the control unit outputs the correction value of the target value of the robot 100 based on the sensor information corrected by the external force detection device 30, and the target value corrected by the correction value. The robot control unit 80 that performs feedback control of the robot 100 is included.

  This makes it possible to realize a robot control system that controls the robot 100 using the external force f that is the output of the external force detection device 30. In the robot system, the hand 110 needs to be highly rigid in order to increase the accuracy of the hand position of the robot 100 (the position of the hand 110), but if that happens, there is a problem when it collides with an operator or the like. Even if an apparently soft (low rigidity) characteristic is realized by force control, the same problem remains if the force control unit 20 that performs force control stops operating for some reason. That is, in the robot system, there is a certain advantage in making the hand 110 low in rigidity such as a flexible structure. Therefore, the force sensor 10 is more rigid than the force sensor 10 as in the present embodiment. A situation in which a low mechanical mechanism is provided can be considered. In this case, as described above, since the modulation by the mechanical mechanism cannot be ignored, the correction process corresponding to the inverse transformation is applied to the sensor information in order to suppress the influence on the subsequent control (for example, impedance control in this case). Need to do.

  Although the present embodiment has been described in detail as described above, it will be easily understood by those skilled in the art that many modifications can be made without departing from the novel matters and effects of the present invention. Accordingly, all such modifications are intended to be included in the scope of the present invention. For example, a term described at least once together with a different term having a broader meaning or the same meaning in the specification or the drawings can be replaced with the different term in any part of the specification or the drawings. Further, the configurations and operations of the external force detection device and the robot control system are not limited to those described in this embodiment, and various modifications can be made.

10 force sensor, 20 force control unit, 22 impedance processing unit,
24 control parameter storage unit, 30 external force detection device, 32 acquisition unit, 34 correction unit,
60 target value output unit, 62 trajectory generation unit, 64 inverse kinematics processing unit,
80 robot controller, 100 robot, 110 hand, 120 arm,
300 control device, 310 robot, 320 arm

Claims (11)

An acquisition unit for acquiring sensor information output from the force sensor;
A correction unit that performs correction processing on the acquired sensor information;
Including
The force sensor is provided with a mechanical mechanism that converts an external force f and transmits the force F to the force sensor as a force F.
The correction unit is
An external force detection device that performs reverse conversion of conversion by the mechanical mechanism as the correction processing. In claim 1,
The correction unit is
An external force detection device that performs the correction process using an inverse conversion formula of the conversion formula when the conversion in the mechanical mechanism is modeled by a predetermined conversion formula. In claim 2,
The correction unit is
An external force detection device that performs the correction process using the inverse transformation equation of the ordinary differential equation when the transformation in the mechanical mechanism is modeled using an ordinary differential equation as the transformation equation. . In claim 2 or 3,
The correction unit is
When the transformation in the mechanical mechanism is modeled using the equation of motion having the mass term, the viscosity term, and the elastic term as coefficient parameters as the transformation equation, the inverse transformation equation of the equation of motion is used as the transformation equation. An external force detection device that performs correction processing. In any one of Claims 1 thru | or 4,
The correction unit is
An external force detection device that performs the correction processing by digital filter processing. In claim 5,
The correction unit is
The value of the sensor information at the nth (n is an integer of 3 or more) timing is _Fn , the intermediate parameter at the ( _{n-1) th} timing is _xn-1, and the coefficient parameters of the digital filter processing are α and β. If
x _n = αF _n + βx _n−1 to obtain the intermediate parameter x _n at the n-th timing,
The obtained intermediate parameter x _n, and the intermediate parameter x _n-2 obtained in the first n-1 of said intermediate parameter x _n-1 and the n-2 timing determined by the timing, the digital filter From the coefficient parameters C ₀ , C ₁ , C ₂ of the process,
f _n = - by _{{x n (C 1 x n} -1 + C 2 x n-2)} / C 0, and obtains the sensor information _{f n} after the correction in the timing of the first n External force detection device. In any one of Claims 1 thru | or 6.
The acquisition unit
Obtaining information corresponding to the force F as the sensor information;
The correction unit is
An external force detection device that acquires information corresponding to the external force f by performing the correction process on the sensor information. In any one of Claims 1 thru | or 7,
The external force detection device, wherein the mechanical mechanism is an end effector of a robot. The external force detection device according to any one of claims 1 to 8,
A control unit that performs control processing of the robot based on the sensor information on which the correction processing has been performed in the external force detection device;
A robot control system comprising: In claim 9,
The controller is
A force control unit that outputs a correction value of the target value of the robot based on the sensor information on which the correction processing has been performed in the external force detection device;
A robot control unit that performs feedback control of the robot based on the target value corrected by the correction value;
A robot control system comprising: An external force detection method for performing correction processing on sensor information output from a force sensor provided with a mechanical mechanism that converts an external force f and transmits the force F as a force F,
Obtaining the sensor information from the force sensor;
An external force detection method comprising performing reverse conversion of conversion by the mechanical mechanism as the correction process on the acquired sensor information.

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