CN113910232B - Self-adaptive attitude tracking method and device, storage medium and electronic equipment - Google Patents
Self-adaptive attitude tracking method and device, storage medium and electronic equipment Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J18/00—Arms
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/005—Manipulators for mechanical processing tasks
- B25J11/0065—Polishing or grinding
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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
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- 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
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- 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
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1661—Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
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- 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
- B25J9/1679—Programme controls characterised by the tasks executed
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Abstract
The invention provides a self-adaptive attitude tracking method, a self-adaptive attitude tracking device, a storage medium and electronic equipment. The method is applied to a robot, and comprises the following steps: fusing at least two preset controllers to generate a hybrid controller; determining a position interpolation quantity and an initial posture interpolation quantity of the robot according to the hybrid controller, and clearing the initial posture interpolation quantity; calculating the attitude interpolation amount of the robot which adaptively changes according to the current attitude; acquiring joint space interpolation quantity of the robot according to the position interpolation quantity and the posture interpolation quantity; and interpolating the current pose of the robot according to the joint space interpolation quantity, and controlling the robot to operate based on the interpolated pose. By adopting the scheme, the operation difficulty of the robot can be simplified, and the elevator robot can meet the response capability of complex working conditions.
Description
Technical Field
The invention belongs to the field of industrial robots, and particularly relates to a self-adaptive posture tracking method and device, a storage medium and electronic equipment.
Background
China is a large country in manufacturing industry, the traditional labor-intensive production mode is difficult to continue along with the decline of population dividends, machines are imperative to replace manpower, and enterprises are mainly developed towards the upgrading and reconstruction of automatic production. The industrial robot field includes traditional industrial robot and collaborative robot, and traditional industrial robot replaces manual operation in being applied to industrial environment, and neotype collaborative robot mainly used optimizes on having produced the line overall arrangement, and the people and the machine collaborative work of being convenient for, and collaborative robot's work scene makes it provide higher requirement to performance such as security, portability.
The robot is configured with different controllers to implement different control functions, such as position-based control or force-based control, but in the prior art, the control function of the controller is relatively single, the controllers are usually used independently, and the robot mainly faces a simple scene which can be implemented by a single controller, but cannot be implemented by a single controller directly when facing a complex working scene. In the prior art, the processing of complex working conditions is usually solved by adopting a manual teaching or software programming mode, but the precision of the manual teaching mode is relatively limited, the software programming mode is relatively complex to realize, the requirement on programming professional knowledge of a user is higher, and the flexible adjustment based on an application scene cannot be realized.
Disclosure of Invention
The application provides a self-adaptive attitude tracking method, a self-adaptive attitude tracking device, a storage medium and electronic equipment, wherein at least two controllers are fused, the integral fusion interpolation quantity is calculated, a hybrid controller is realized, and meanwhile, the functions of force tracking and attitude tracking are realized, so that the problem that the attitude tracking is realized in a manual programming or teaching mode in the prior art is solved.
In order to achieve the above object, the present invention can adopt the following technical solutions: an adaptive pose tracking method applied to a robot for connecting a tool to perform a predetermined operation on a work object, the method comprising: fusing at least two preset controllers to generate a hybrid controller; determining a position interpolation quantity and an initial posture interpolation quantity of the robot according to the hybrid controller, and clearing the initial posture interpolation quantity; calculating the attitude interpolation amount of the robot which adaptively changes according to the current attitude; acquiring joint space interpolation quantity of the robot according to the position interpolation quantity and the posture interpolation quantity; and interpolating the current pose of the robot according to the joint space interpolation quantity, and controlling the robot to operate based on the interpolated pose.
Further, the calculating a posture interpolation amount of the robot adaptively changing according to the current posture comprises: setting a target posture of the robot, wherein the target posture comprises a target operation angle of the tool on a working object; acquiring a current posture of the robot, wherein the current posture comprises a current operation angle of the tool on a working object; and calculating the posture interpolation quantity of the robot changing from the current posture to the target posture according to the target operation angle, the current operation angle and a pre-designed angle tracking controller.
Further, the acquiring the current posture of the robot comprises: and acquiring an included angle between the TCP attitude of the robot and the tangent vector of the TCP track.
Further, the angle tracking controller is a PID controller.
Further, before calculating the pose interpolation amount of the robot changing from the current pose to the target pose, the method further includes: and carrying out filtering processing on the current operation angle according to a predetermined filter.
Further, the at least two controllers include at least two of a position controller, a force controller, and an impedance controller.
Further, the fusing at least two controllers set in advance to generate a hybrid controller includes: obtaining the spatial interpolation quantities of at least two controllers; and determining a fusion interpolation amount according to the space interpolation amount of each controller to generate a hybrid controller.
The invention can also adopt the following technical scheme: an adaptive attitude tracking device applied to a robot comprises: the fusion unit is used for fusing at least two preset controllers to generate a hybrid controller; the determining unit is used for determining the position interpolation amount and the initial posture interpolation amount of the robot according to the hybrid controller and clearing the initial posture interpolation amount; the computing unit is used for computing the attitude interpolation amount of the robot which adaptively changes according to the current attitude; an acquisition unit, configured to acquire a joint space interpolation amount of the robot according to the position interpolation amount and the posture interpolation amount; and the control unit is used for interpolating the current pose of the robot according to the joint space interpolation amount and controlling the robot to operate based on the interpolated pose.
The invention can also adopt the following technical scheme: a computer readable storage medium storing a computer program which, when executed, implements an adaptive pose tracking method as described in any of the preceding.
The invention can also adopt the following technical scheme: an electronic device, comprising: a memory storing a computer program; a processor for executing the computer program in the memory to implement the adaptive tracking method of any of the preceding.
Compared with the prior art, the specific implementation mode of the invention at least brings the following beneficial effects:
according to the robot system, the generated hybrid controller is used for obtaining the position interpolation quantity of the robot based on the hybrid controller, the recalculated gesture interpolation quantity is combined, the robot joint space interpolation quantity is obtained, interpolation operation is carried out on the robot according to the position interpolation quantity, the robot can realize self-adaptation according to position change and force change according to the hybrid controller, meanwhile, gesture self-adaptation is carried out based on the recalculated gesture interpolation quantity which is adaptively changed according to the current gesture of the robot, the robot can realize force tracking and self-adaptation gesture tracking at the same time, a moving instruction does not need to be set manually, the robot can process complex scenes which need force tracking and gesture tracking when curved surfaces are polished and the like, programming work of a user for teaching the robot is simplified, and the capability of the robot for processing complex working conditions is improved.
Drawings
FIG. 1 is a schematic view of a robot according to one embodiment of the present invention;
FIG. 2 is a schematic diagram of an adaptive pose tracking method of one embodiment of the present invention;
FIG. 3 is a schematic diagram of an adaptive pose tracking method according to another embodiment of the invention;
FIG. 4 is a schematic diagram of an adaptive pose tracking method according to yet another embodiment of the invention;
FIG. 5 is a flow chart of an adaptive tracking method of one embodiment of the present invention;
FIG. 6 is a schematic diagram of an adaptive tracking device according to one embodiment of the present invention;
FIG. 7 is a schematic view of an electronic device of one embodiment of the invention.
Detailed Description
In order to make the technical scheme of the invention more clear, the embodiment of the invention will be described in the following with reference to the accompanying drawings. It should be understood that the detailed description of the embodiments is intended only to teach one skilled in the art how to practice the invention, and is not intended to be exhaustive of all possible ways of practicing the invention, nor is it intended to limit the scope of the practice of the invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.
The application provides an adaptive attitude tracking method, which is applied to a robot, and referring to fig. 1, a robot 100 comprises a base 30, a joint 20 and a connecting piece 40, the tail end of the robot is connected with a tool 300 to perform a predetermined operation on a working object, the joint 20 of the robot 100 is a power source and comprises a motor, a driver, a reducer and other elements, and sensors such as a force sensor and a visual sensor are optionally arranged at the tail end of the robot 100 to acquire necessary operation information of the robot. The robot includes a control system integrated with the robot or formed as a separate control component for processing operation information of the robot and issuing instructions for controlling the operation to the robot.
The present application provides an adaptive gesture tracking method, applied to a robot 100, which can be executed by the above control system, referring to fig. 2, the adaptive gesture tracking method includes the steps of:
s201, fusing at least two preset controllers to generate a hybrid controller;
s202, determining a position interpolation quantity and an initial posture interpolation quantity of the robot according to the hybrid controller, and clearing the initial posture interpolation quantity;
s203, calculating the posture interpolation amount of the robot which adaptively changes according to the current posture;
s204, acquiring joint space interpolation quantity of the robot according to the position interpolation quantity and the posture interpolation quantity;
and S205, interpolating the current pose of the robot according to the joint space interpolation amount, and controlling the robot to operate based on the interpolated pose.
In a specific embodiment, referring to fig. 3, step S201 includes steps S2011 to S2012.
S2011, spatial interpolation quantities of at least two controllers are obtained;
and S2012, determining fusion interpolation amount according to the space interpolation amount of each controller to generate a hybrid controller.
The robot comprises a plurality of joints, correspondingly, the robot has a plurality of degrees of freedom, for example, a common six-joint robot has six degrees of freedom, when a plurality of controllers of the robot are fused, the fusion of the plurality of degrees of freedom of the robot is completed through respective degrees of freedom of the robot, and then the fusion of the plurality of degrees of freedom of the robot is realized. Specifically, step S2011 includes obtaining spatial interpolation quantities of at least two controllers in the target degree of freedom; step S2012 includes determining an interpolation amount of the target degree of freedom from the spatial interpolation amount of each controller in the target degree of freedom, and fusing the interpolation amounts of the plurality of degrees of freedom of the robot to determine a fused interpolation amount to generate a hybrid controller. For example, there may be only a portion of the interpolation amount by the controller in a certain degree of freedom of the robot, or there may be a plurality of interpolation amounts by the controllers in a certain degree of freedom of the robot. By generating the hybrid controller, the position interpolation amount and the posture interpolation amount of the robot can be generated comprehensively based on the plurality of acquired variables. The spatial interpolation quantity is a Cartesian spatial interpolation quantity or a joint spatial interpolation quantity. In the cartesian space, the interpolation amount of the robot may be represented as coordinates of a cartesian coordinate system, and the interpolation amount in the cartesian space may be converted into the interpolation amount in the joint space after being fused for fusion; in the joint space, the interpolation amount can be expressed by the joint angle, and the controllers are merged.
For example, before the robot performs work, the user selects based on a scene of performing the work, the user may preset at least two controllers to be fused based on a teach pendant or other interactive devices, and the robot automatically implements function fusion of the at least two controllers. Or the user sets the type of work to be performed through a demonstrator or other modes, the robot determines which controllers need to be fused according to the work type, or the robot manufacturer recommends default controllers for common work scenes of the robot in the design and production stages, and the robot automatically sets at least two corresponding controllers after the user selects the work scenes and realizes the fusion of the controllers to support the subsequent work.
Wherein the at least two controllers comprise at least two of a position controller, a force controller, and an impedance controller. For example, taking a curved surface polishing operation as an example, a robot needs to be at least provided with a position controller to realize movement control of a robot position, the force controller is arranged to ensure that an acting force follows a target force in the robot position movement process, and in combination with attitude adaptation, the acting force can be controlled to follow the target acting force in the robot movement process, and the robot attitude can adaptively follow the target attitude.
Different controllers of the robot have different functions, for example, the position controller can realize the position following of the robot, the force control can enable the force to follow the target force in the moving process of the robot, the impedance controller can enable the robot to have flexibility, and the spatial interpolation quantity is calculated according to the controllers respectively so as to realize a hybrid controller. For example, the following is an exemplary description of how to convert the controller output into cartesian spatial interpolation for controller fusion:
(1) Force tracking controller
TCP has 6 degrees of freedom under the coordinate system { f }, including 3 degrees of freedom in position and 3 degrees of freedom in attitude. Assuming that the force/moment to be tracked in the target degree of freedom is f d Where the actual force is f, then the force tracking error is f e =f d -f, the interpolated acceleration in the target degree of freedom being:
(2) Impedance controller
Let x denote the value of the target degree of freedom of TCP under the coordinate system f, which may be, for example, position x, y or z, or an attitude variable. The cartesian space interpolation in the target degree of freedom is δ x.
If TCP is expected to behave in a mass-spring-damping model under the action of an external force, the external force on the target degree of freedom is f ext Then, the cartesian spatial interpolation amount in the target degree of freedom is:
wherein M, B and K are mass-spring-damping model parameters, and f is the operating process of the mechanical arm ext The interpolation quantity is obtained by a terminal force/moment sensor and then an Euler method is used for solving a differential equation (2) to obtain the interpolation quantity.
(3) Motion controller
In a possible implementation manner, the motion planning can be performed in a cartesian space to directly output cartesian space interpolation, or the motion planning can be performed in a joint space to obtain the cartesian space interpolation through a positive kinematics solution. The cartesian space coordinate system is the coordinate system to be fused { f }.
In one possible implementation, it is assumed that the interpolation quantities in this degree of freedom for the force tracking controller, the impedance controller, the motion controller and the other controllers are δ x tr ,δx im ,δx mov ,δx other Then the interpolation in this degree of freedom after the final fusion is:
δx=f 1 (δx tr )+f 2 (δx im )+f 3 (δx mov )+f 4 (δx other ) (3)
wherein f is 1 -f 4 Is a custom fusion function. For example, a common simple fusion function is that the value of f (x) is either 0 or x (x ≠ 0); if the value is 0, the value is,the corresponding controller does not function in that degree of freedom and if x then the corresponding controller functions in that degree of freedom.
Fusing different controllers will have different physical meanings, such as if f2 and f3 in (3) were fused then TCP behaves in this degree of freedom as: if the mechanical arm is not subjected to external force, the mechanical arm is purely controlled by motion, and if the mechanical arm is subjected to external force, the mechanical arm is controlled by motion and impedance, so that the tail end of the mechanical arm can be protected to show certain flexibility after meeting obstacles in the motion process. It can be seen that fusing different controllers in a single degree of freedom will eventually show completely different effects.
The controller of the robot can output interpolation amount according to the position or the moment, after the hybrid controller is generated, the output is adjusted according to the change of the position and the moment parameters, and the robot can perform force tracking and position tracking in a self-adaptive mode. In the conventional robot, if the robot needs to track the attitude, the robot cannot adaptively generate the attitude interpolation amount through the acquired position information, and when the position of the robot does not change, the attitude of the robot can also change, so that the robot is not feasible to realize the attitude adaptation based on position control or force control. The hybrid controller can obtain attitude information from input position information and force information, but the attitude information does not have the capability of changing adaptively.
In the prior art, a program instruction is edited by a user so as to accurately match the moving position, the moment, the posture information and the like of the robot, and the robot automatically outputs a force tracking signal according to a predetermined requirement by arranging a hybrid controller. Meanwhile, even if fusion of a plurality of controllers can be realized, the posture cannot be tracked adaptively through the hybrid controller, because the interpolation quantity output by the hybrid controller is calculated based on the position and/or the moment of the robot, when the posture of the robot changes, the hybrid controller cannot realize adaptive adjustment of the posture, the hybrid controller can calculate the posture interpolation quantity, but cannot deal with the problem of adaptive change of the posture interpolation quantity when the posture changes, and further cannot realize adaptive tracking of the posture. Therefore, the attitude information output by the hybrid controller is cleared, and the attitude interpolation amount of the robot which changes in a self-adaptive manner is calculated by a method different from that of the hybrid controller, so that the attitude tracking of the robot is realized; and acquiring joint space interpolation quantity of the robot according to the calculated posture interpolation quantity and the position interpolation quantity output by the hybrid controller so as to interpolate the current posture of the robot. Specifically, the gesture interpolation amount is adaptively changed according to the current position of the robot, and how to obtain the gesture interpolation amount adaptively changed according to the current position of the robot may have various forms.
For example, in a specific embodiment, referring to fig. 4, step S203 includes:
s2031, setting a target posture of the robot, wherein the target posture comprises a target operation angle of the tool on a working object;
s2032, acquiring the current posture of the robot, wherein the current posture comprises the current operation angle of the tool on a working object;
s2033, calculating a posture interpolation amount of the robot from the current posture to the target posture according to the target operation angle, the current operation angle and a pre-designed angle tracking controller.
Wherein the robot has a tool center point, TCP point, which is typically the tip point of the tool, and said obtaining the current pose of the robot comprises: and acquiring an included angle between the TCP attitude of the robot and a tangent vector of the TCP track. The target pose of the robot is preset by the user. Taking curved surface polishing as an example, the included angle between the robot tool and the work object is the included angle between the Z axis of the tool coordinate system and the tangent of the three-dimensional curve through which the TCP passes. Through the mode, the robot can operate along with the target posture in a self-adaptive manner in the current posture in the moving process of the robot, and the robot can perform self-adaptive tracking of the posture while tracking the force. Specifically, the control system can preset a target posture of the robot, determine a difference value between the current posture and the target posture based on the current posture detected in the running process of the robot, further determine a posture interpolation amount from the current posture to the target posture of the robot by combining the angle tracking controller, change the difference value between the current posture and the target posture when the current posture of the robot changes, and realize that the current posture of the robot always follows the target posture by calculating in real time through the robot. Specifically, the current posture of the robot may be obtained by a six-dimensional sensor at the end of the robot, or may be obtained by other possible means such as a visual sensor.
The calculating of the joint space interpolation amount according to the position interpolation amount and the posture interpolation amount comprises calculating the joint space interpolation amount through inverse kinematics solution according to the position interpolation amount and the posture interpolation amount. The inverse kinematics solution may use an analytical solution method or a numerical solution method, which is not described in detail herein.
Further, in a specific embodiment, the angle tracking controller is a PID controller, i.e. a proportional-integral-derivative controller, and the current operating angle is set to θ t The target operating angle is theta d Then angle error theta e =θ d -θ t The output of the PID controller is the attitude interpolation amount δ θ. The PID controller calculates the attitude interpolation amount according to the angle error Wherein K P 、K i 、K d Proportional, integral and derivative coefficients, respectively. Therefore, when the current operation angle of the PID controller changes, the angle error changes, and the attitude interpolation quantity output by the PID controller also changes, so that the self-adaptive tracking of the robot attitude can be realized.
Preferably, before calculating the attitude interpolation amount for the robot to change from the current attitude to the target attitude, the method further includes: and according to a predetermined filter, carrying out filtering processing on the current operation angle so as to process sudden change of the current operation angle caused by position change in the robot control process.
Referring to fig. 5, fig. 5 is a flowchart of an adaptive pose tracking method in an embodiment of the present application, where current state information of a robot is obtained through a force sensor at a robot end, a current pose of the robot, and a designated coordinate system, and a position interpolation amount is processed and output according to a hybrid controller; the method comprises the steps of obtaining a TCP track tangent vector and a TCP gesture according to the current pose of the robot, calculating the current operation angle of a robot tool and a working object according to the TCP track tangent vector and the TCP gesture, filtering the current operation angle to remove interference information, combining a preset target operation angle, obtaining a gesture interpolation quantity through an angle tracking controller, performing kinematic inverse solution on the gesture interpolation quantity and a position interpolation quantity output by a hybrid controller to obtain a joint space interpolation quantity, finally, interpolating the current pose of the robot according to the joint space interpolation quantity, controlling the servo drive of the robot, further controlling the motion angle of each joint of the robot, and finally achieving the effect of adjusting the pose of the robot.
The beneficial effects of the above preferred embodiment are: the method can avoid complex programming of the robot and enrich the scene that the robot processes complex working conditions, and the robot can track the target gesture in a self-adaptive manner, so that the use experience is improved.
The present application is also directed to providing an adaptive posture tracking apparatus, which is applied to a robot, and referring to fig. 6, the adaptive posture tracking apparatus includes:
a fusion unit 410 for fusing at least two controllers set in advance to generate a hybrid controller;
a determining unit 420, configured to determine a position interpolation amount and an initial posture interpolation amount of the robot according to the hybrid controller, and zero-clearing the initial posture interpolation amount;
a calculating unit 430, configured to calculate a posture interpolation amount that the robot adaptively changes according to the current posture;
an obtaining unit 440, configured to obtain a joint space interpolation amount of the robot according to the position interpolation amount and the posture interpolation amount;
and the control unit 450 is configured to interpolate the current pose of the robot according to the joint space interpolation amount, and control the robot to operate based on the interpolated pose.
The determining unit 420 calculates an initial posture interpolation amount and clears the initial posture interpolation amount, the robot posture interpolation amount is calculated according to the calculating unit 430, the calculating unit 430 determines the posture interpolation amount in a manner different from that of the determining unit, and the calculating unit 430 calculates the posture interpolation amount adaptively changed by the robot according to the current posture. Preferably, the calculating unit 430 includes adaptive processing on the current posture of the robot to determine a posture interpolation amount of the robot, and further determine a robot joint space interpolation amount, and after the robot posture is interpolated, the force tracking and the posture tracking can be realized.
Wherein, the preset at least two controllers comprise at least two of a position controller, a force controller and an impedance controller. The fusing at least two preset controllers to generate a hybrid controller includes: obtaining the spatial interpolation quantities of at least two controllers; and determining a fusion interpolation amount according to the space interpolation amount of each controller to generate a hybrid controller.
In a specific embodiment, the calculation unit 430 may calculate the pose interpolation amount of the robot adaptively changing according to the current pose, and may be implemented as: setting a target posture of the robot, wherein the target posture represents a target operation angle of the tool on a working object; acquiring a current posture of the robot, wherein the current posture comprises a current operation angle of the tool on the working object; and calculating the posture interpolation quantity of the robot changing from the current posture to the target posture according to the target operation angle, the current operation angle and a pre-designed angle tracking controller. Specifically, the target pose may be manually set, for example, a user may set the target pose through a teach pendant or other portable device to indicate an operation angle of a tool expected by the user to a working object, so as to ensure an operation effect of the robot, the current pose and the target pose are constantly compared in the operation process of the robot, a pose interpolation amount is calculated by combining with an angle tracking controller, and the pose of the robot after the final interpolation corresponds to the preset target pose, so as to ensure the operation effect of the robot.
Specifically, acquiring the current posture of the robot includes: and acquiring an included angle between the TCP attitude of the robot and the tangent vector of the TCP track. TCP, i.e. the tool center point of the robot, the tool center point in the initial state is the origin of the tool coordinate system, and when the robot is manually or programmatically moved close to a certain point in the space, it is essential to move the tool center point close to the point, so the trajectory motion of the robot can be represented by the tool center point. The TCP attitude, namely the tool center point attitude, and the TCP trajectory tangent vector, namely the tool center point trajectory tangent vector. Establishing a tool coordinate system of the robot, wherein a Z axis of the tool coordinate system represents the TCP posture of the robot; and taking curved surface polishing as an example, an included angle formed by the Z axis of the tool coordinate system and the tangential direction of a three-dimensional curve passed by the TCP is an operation angle of the robot tool on a working object, and the angle difference value required to be changed is obtained by detecting the angle and combining a preset target posture.
In one possible embodiment, the angle tracking controller is a PID controller. And before calculating the attitude interpolation quantity of the robot changing from the current attitude to the target attitude, the method further comprises the following steps: and carrying out filtering processing on the current operation angle according to a preset filter.
With regard to the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be described in detail here.
In an exemplary embodiment, the present application further provides a computer readable storage medium, such as a memory, having a computer program stored thereon, the computer program being executable by a processor to perform an adaptive pose tracking method. Alternatively, the storage medium may be a non-transitory computer readable storage medium, which may be, for example, a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
In an exemplary embodiment, the present application further provides an electronic device comprising a memory and a processor, the memory storing a computer program; the processor is configured to execute the computer program in the memory to implement the adaptive pose tracking method described above.
In a particular embodiment, referring to FIG. 7, electronic device 500 may include a processor 510, memory 520, input/output components 530, and communication ports 540. Processor 510 (e.g., a CPU) may execute program commands in the form of one or more processors. The memory 520 includes various forms of program storage and data storage such as a hard disk, read Only Memory (ROM), random Access Memory (RAM), etc. for storing various data files that are processed and/or transmitted by a computer. Input/output component 530 may be used to support input/output between a processing device and other components. The communication port 540 may be connected to a network for enabling data communication. An exemplary processing device may include program instructions stored in read memory (ROM), random Access Memory (RAM), and/or other types of non-transitory storage media that are executed by a processor. The methods and/or processes of the embodiments of the present specification may be implemented as program instructions.
Finally, it is to be noted that the above description is intended to be illustrative and not exhaustive, and that the invention is not limited to the disclosed embodiments, and that several modifications and variations may be resorted to by those skilled in the art without departing from the scope and spirit of the invention as set forth in the appended claims. Therefore, the protection scope of the present invention should be subject to the claims.
Claims (9)
1. An adaptive pose tracking method applied to a robot for connecting a tool to perform a predetermined operation on a work object, the method comprising:
fusing at least two preset controllers to obtain the spatial interpolation quantities of the at least two controllers, and determining the fusion interpolation quantity according to the spatial interpolation quantities of the controllers to generate a hybrid controller;
determining a position interpolation quantity and an initial posture interpolation quantity of the robot according to the hybrid controller, and clearing the initial posture interpolation quantity;
calculating the attitude interpolation amount of the robot which adaptively changes according to the current attitude;
acquiring joint space interpolation quantity of the robot according to the position interpolation quantity and the posture interpolation quantity;
and interpolating the current pose of the robot according to the joint space interpolation amount, and controlling the robot to operate based on the interpolated pose.
2. The adaptive pose tracking method of claim 1, wherein calculating a pose interpolation amount for the robot to adaptively change according to the current pose comprises:
setting a target posture of the robot, wherein the target posture comprises a target operation angle of the tool on a working object;
acquiring a current posture of the robot, wherein the current posture comprises a current operation angle of the tool on a working object;
and calculating the posture interpolation quantity of the robot changing from the current posture to the target posture according to the target operation angle, the current operation angle and a pre-designed angle tracking controller.
3. The adaptive pose tracking method of claim 2, wherein said obtaining a current pose of a robot comprises: and acquiring an included angle between the TCP attitude of the robot and the tangent vector of the TCP track.
4. The adaptive pose tracking method of claim 2, wherein the angle tracking controller is a PID controller.
5. The adaptive pose tracking method of claim 2, wherein the calculating of the pose interpolation amount for the robot to change from the current pose to the target pose further comprises:
and carrying out filtering processing on the current operation angle according to a predetermined filter.
6. The adaptive pose tracking method of claim 1, wherein said at least two controllers comprise at least two of a position controller, a force controller, an impedance controller.
7. An adaptive attitude tracking device applied to a robot is characterized by comprising:
the fusion unit is used for fusing at least two preset controllers, acquiring the spatial interpolation quantities of the at least two controllers, and determining the fusion interpolation quantities according to the spatial interpolation quantities of the controllers to generate a hybrid controller;
the determining unit is used for determining the position interpolation quantity and the initial posture interpolation quantity of the robot according to the hybrid controller and clearing the initial posture interpolation quantity;
the computing unit is used for computing the attitude interpolation amount of the robot which adaptively changes according to the current attitude;
an obtaining unit, configured to obtain a joint space interpolation amount of the robot according to the position interpolation amount and the posture interpolation amount;
and the control unit is used for interpolating the current pose of the robot according to the joint space interpolation quantity and controlling the robot to operate based on the interpolated pose.
8. A computer-readable storage medium storing a computer program, wherein the computer program when executed implements the adaptive pose tracking method of any of claims 1-6.
9. An electronic device, comprising:
a memory storing a computer program;
a processor for executing the computer program in the memory to implement the adaptive pose tracking method of any of claims 1-6.
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2010253668A (en) * | 2009-03-31 | 2010-11-11 | Daihen Corp | Control device of robot |
CN107838920A (en) * | 2017-12-20 | 2018-03-27 | 芜湖哈特机器人产业技术研究院有限公司 | A kind of robot polishing Force control system and method |
CN109015634A (en) * | 2018-07-24 | 2018-12-18 | 西北工业大学 | Multi-arm teleoperation robot power/Position Hybrid Control method based on performance function |
CN110315527A (en) * | 2019-02-26 | 2019-10-11 | 浙江树人学院(浙江树人大学) | A kind of flexible mechanical arm control method of adaptive Dynamic Programming |
CN110488745A (en) * | 2019-07-23 | 2019-11-22 | 上海交通大学 | A kind of human body automatic ultrasonic scanning machine people, controller and control method |
CN110948504A (en) * | 2020-02-20 | 2020-04-03 | 中科新松有限公司 | Normal constant force tracking method and device for robot machining operation |
CN111319036A (en) * | 2018-12-15 | 2020-06-23 | 天津大学青岛海洋技术研究院 | Self-adaptive algorithm-based mobile mechanical arm position/force active disturbance rejection control method |
CN111633668A (en) * | 2020-07-27 | 2020-09-08 | 山东大学 | Motion control method for robot to process three-dimensional free-form surface |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20140147267A (en) * | 2013-06-19 | 2014-12-30 | 광주과학기술원 | Control Method and Device for Position-Based Impedance Controlled Industrial Robot |
-
2021
- 2021-10-27 CN CN202111252255.3A patent/CN113910232B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2010253668A (en) * | 2009-03-31 | 2010-11-11 | Daihen Corp | Control device of robot |
CN107838920A (en) * | 2017-12-20 | 2018-03-27 | 芜湖哈特机器人产业技术研究院有限公司 | A kind of robot polishing Force control system and method |
CN109015634A (en) * | 2018-07-24 | 2018-12-18 | 西北工业大学 | Multi-arm teleoperation robot power/Position Hybrid Control method based on performance function |
CN111319036A (en) * | 2018-12-15 | 2020-06-23 | 天津大学青岛海洋技术研究院 | Self-adaptive algorithm-based mobile mechanical arm position/force active disturbance rejection control method |
CN110315527A (en) * | 2019-02-26 | 2019-10-11 | 浙江树人学院(浙江树人大学) | A kind of flexible mechanical arm control method of adaptive Dynamic Programming |
CN110488745A (en) * | 2019-07-23 | 2019-11-22 | 上海交通大学 | A kind of human body automatic ultrasonic scanning machine people, controller and control method |
CN110948504A (en) * | 2020-02-20 | 2020-04-03 | 中科新松有限公司 | Normal constant force tracking method and device for robot machining operation |
CN111633668A (en) * | 2020-07-27 | 2020-09-08 | 山东大学 | Motion control method for robot to process three-dimensional free-form surface |
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