Method, apparatus and medium for controlling dual-arm robot to perform chemical gel characterization experiment

Abstract

The application discloses a method, equipment and medium for controlling a double-arm robot to perform a chemical gel characterization experiment, and belongs to the field of double-arm robot collaborative operation. The method comprises the following steps: step 1, modeling a gel operation platform as a scene model; step 2, setting double-arm motion constraint conditions of the double-arm robot according to a gel characterization experiment task, and planning a double-arm joint trajectory conforming to the double-arm motion constraint conditions in the scene model by using a trajectory planning algorithm; step 3, monitoring and processing abnormal information in a double-arm operation process by using a double-arm robot double-arm end torque sensor; step 4, under the monitoring of step 3, the double-arm robot performs a gel demolding and carrying task and a gel stretching characterization task according to the double-arm joint trajectory, and collects gel performance data when the gel is stretched; and step 5, after the double-arm robot completes the operation in step 4, a reset operation is performed, and the current task process is ended. The method can adapt to diversified gel experiment demands, and improves the efficiency and precision of gel performance data collection.

Description

Technical Field

[0001] The present invention relates to the technical field of collaborative operation of dual-arm robots, and in particular to a method for controlling a dual-arm robot to perform a high-throughput chemical gel characterization experiment. Background Art

[0002] In chemical gel characterization experiments, it is necessary to efficiently and accurately obtain a large amount of performance data during the gel deformation process. However, traditional manual operation methods usually have problems such as low experimental efficiency, poor data reliability, and potential safety hazards caused by long-term contact with gel materials. In order to improve the reliability of data, some experiments have begun to introduce stretching equipment, such as stretching machines, to replace manual gel deformation operations, but this method still requires a lot of manual intervention to operate the equipment and transport gel materials, and the equipment has a single function and is difficult to adapt to diverse experimental needs; in industry, automated equipment such as conveyor belts are usually used to transfer workpieces, but the variability of gel characterization experimental scenarios makes the conveying system design complex and costly, and lacks sufficient scalability and adaptability.

[0003] In recent years, the field of intelligent chemistry has gradually introduced mobile manipulators to complete some experimental operations and improve experimental efficiency. However, existing systems are mostly based on single-arm robots. Although they can complete gel handling tasks, they perform poorly when it comes to high-precision, multi-step stretching characterization tasks. In particular, it is difficult to achieve closed-loop automation of gel stretching and performance data collection. Currently, the application of dual-arm robots in chemical experiments is still underexplored. Compared with single-arm robots, dual-arm robots have stronger collaborative operation capabilities and can demonstrate greater flexibility and precision in complex experimental tasks. However, the introduction of dual-arm manipulators into chemical gel characterization experiments requires consideration of the dual-arm robot's collaborative operation during gel handling and stretching characterization, as well as the handling of gel deformation anomalies. This situation indicates that in current chemical gel data characterization experiments, there is no systematic method that enables dual-arm robots to complete the integrated operations of gel handling, controllable stretching, and data collection in characterization experiments.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a method, equipment and medium for controlling a dual-arm robot to perform chemical gel characterization experiments, so that the dual-arm robot can complete the non-destructive transportation and controllable stretching tasks of chemical gels in a variety of experimental scenarios, achieve the high-throughput goal of chemical gel characterization experiments, and thus solve the above-mentioned technical problems existing in the prior art.

[0006] The purpose of the present invention is achieved through the following technical solutions:

[0007] A method for controlling a dual-arm robot to perform chemical gel characterization experiments, modeling the gel operation platform as a scene model, including:

[0008] Step 1: Set the dual-arm motion constraints of the dual-arm robot according to the gel characterization experiment task, and use the trajectory planning algorithm in the scene model to plan the dual-arm joint trajectory that meets the dual-arm motion constraints;

[0009] Step 2: Use the torque sensors at the ends of the dual-arm robot's arms to monitor and process abnormal information during the operation of the dual-arm robot in real time;

[0010] Step 3: Under the monitoring of step 2, the dual-arm robot completes the gel demoulding and handling tasks and the gel stretching characterization tasks according to the dual-arm joint trajectory planned in step 1, and collects gel performance data during the gel stretching characterization tasks;

[0011] Step 4: After the dual-arm robot completes the operation in step 3, it performs a reset operation to end the current gel characterization experiment task.

[0012] A processing device comprising:

[0013] at least one memory for storing one or more programs;

[0014] At least one processor is capable of executing one or more programs stored in the memory. When the one or more programs are executed by the processor, the processor is enabled to implement the method described in the present invention.

[0015] A readable storage medium stores a computer program, which can implement the method of the present invention when the computer program is executed by a processor.

[0016] Compared with the prior art, the method, device and medium for controlling a dual-arm robot to perform chemical gel characterization experiments provided by the present invention have the following beneficial effects:

[0017] By modeling the gel manipulation platform as a scenario model and setting dual-arm motion constraints for the dual-arm robot based on the gel characterization experimental task, a dual-arm joint trajectory that meets the dual-arm motion constraints is planned in the scenario model. Under the monitoring of the torque sensor, the dual-arm robot completes the gel demolding and gel stretching characterization tasks according to the planned dual-arm joint trajectory, and collects gel performance data during gel stretching characterization. This realizes trajectory planning under constraint conditions for the dual-arm robot, effectively reducing gel deformation loss during gel handling, improving the controllability of the stretching operation and the consistency of experimental data. Combined with the dual-arm end torque sensor, it can detect and handle abnormal situations in real time. This method covers the entire process of chemical gel characterization experiments, can adapt to diverse experimental scenarios and task requirements, and improves the efficiency and accuracy of gel performance data collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0019] Figure 1 The method flow chart for controlling the double-arm robot to perform the chemical gel characterization experiment is provided for the embodiments of the present application.

[0020] Figure 2 The application state flow chart of the method for controlling the double-arm robot to perform the chemical gel characterization experiment is provided for the embodiments of the present application.

[0021] Figure 3 The schematic diagram for representing the mapping relationship between the posture deviation in the Atlas RRT planning algorithm is provided for the embodiments of the present application.

[0022] Figure 4 The main coordinate system schematic diagram when the double-arm robot performs the gel operation is provided for the embodiments of the present application.

[0023] Figure 5 The overall flow chart of the chemical gel characterization experiment performed on the gel stretching platform in the method is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the specific contents of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application, which does not constitute a limitation to the present application. Based on the embodiments of the present application, all the other embodiments obtained by those skilled in the art without any creative effort are within the protection scope of the present application.

[0025] Firstly, the terms possibly used in the present text are explained as follows:

[0026] The term "and / or" means either of the two or both of them can be realized, for example, X and / or Y means three cases including "X" or "Y", or "X and Y".

[0027] The terms "comprise", "comprising", "include", "including", "contain", "containing", "have", "having", or any other similar semantic descriptions, are to be construed as open-ended rather than limiting. For example, the inclusion of an element, such as a raw material, component, ingredient, carrier, dosage form, material, dimension, part, component, mechanism, device, step, process, method, reaction condition, processing condition, parameter, algorithm, signal, data, product, or article, is to be interpreted as including not only the explicitly recited element, but also any element known to one of ordinary skill in the art to be associated with or useful in conjunction with the explicitly recited element.

[0028] The term "consisting of" means excluding any element not specifically recited. If the term is used in the context of a claim, the term shall make the claim closed, meaning that the claim does not include any element not specifically recited. If the term is used in the context of a clause in a claim, the term shall limit the clause to only the elements specifically recited in that clause, but other clauses in the claim are not excluded from the overall claim.

[0029] Unless specifically stated otherwise, the terms "mount", "connected", "connected", "fixed", and the like, are to be construed broadly, for example, as either a fixed connection, or as a detachable connection, or as an integral connection; as either a mechanical connection, or as an electrical connection; as either a direct connection, or as an indirect connection via an intermediate medium; as a communication between the internal elements of two components. The specific meaning of the above terms in the context of the present disclosure can be understood by one of ordinary skill in the art according to the specific circumstances.

[0030] When a concentration, temperature, pressure, size, or other parameter is expressed as a numerical range, the numerical range should be understood to specifically disclose all ranges formed from any pair of an upper limit value, a lower limit value, a preferred value within the numerical range, whether or not the range is explicitly recited; for example, if a numerical range "2 to 8" is recited, the numerical range should be interpreted to include "2 to 7", "2 to 6", "5 to 7", "3 to 4 and 6 to 7", "3 to 5 and 7", "2 and 5 to 7", and the like. Unless otherwise specified, numerical ranges recited herein include all integers and fractions within the range.

[0031] The terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings and are only for the convenience and simplification of description, and do not explicitly or implicitly indicate that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore should not be understood as a limitation to this document.

[0032] The scheme provided by the present invention is described in detail below. The contents not described in detail in the examples of the present invention belong to the prior art known to professionals in this field. If specific conditions are not specified in the examples of the present invention, they are carried out according to conventional conditions in the field or conditions recommended by the manufacturer. If the manufacturer of the reagents or instruments used in the examples of the present invention is not specified, they are all conventional products that can be purchased commercially.

[0033] like Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a method for controlling a dual-arm robot to perform a chemical gel characterization experiment, wherein a gel operation platform is modeled as a scene model, including:

[0034] Step 1: Set the dual-arm motion constraints of the dual-arm robot according to the gel characterization experiment task, and use the trajectory planning algorithm in the scene model to plan the dual-arm joint trajectory that meets the dual-arm motion constraints;

[0035] Step 2: Use the torque sensors at the ends of the dual-arm robot's arms to monitor and process abnormal information during the operation of the dual-arm robot in real time;

[0036] Step 3: Under the monitoring of step 2, the dual-arm robot completes the gel demoulding and handling tasks and the gel stretching characterization tasks according to the dual-arm joint trajectory planned in step 1, and collects gel performance data during the gel stretching characterization tasks;

[0037] Step 4: After the dual-arm robot completes the operation in step 3, it performs a reset operation to end the current gel characterization experiment task.

[0038] Furthermore, if there is a subsequent gel characterization experiment task, an instruction is sent to the gel operation platform to indicate whether to continue the gel characterization experiment task. If so, steps 1 to 4 are repeated until all gel characterization experiment tasks are completed.

[0039] The dual arms of the dual-arm robot in the above method are divided into a left arm and a right arm, that is, a left robotic arm and a right robotic arm.

[0040] Preferably, in the above method, the modeling method of the gel operation platform as a scene model adopts the MVSNet method or the SLAM method.

[0041] Preferably, in step 1 of the above method, the dual-arm motion constraint condition of the dual-arm robot is set according to the gel characterization experimental task in the following manner, including:

[0042] Step 11, according to the scheduling instruction of the dual-arm robot performing the gel characterization experimental task, set the dual-arm motion constraint condition of the dual-arm robot in the following manner;

[0043] If the scheduling instruction of the dual-arm robot performing the gel demolding and carrying task, the dual-arm motion constraint equation is:

[0044] ;

[0045] If the scheduling instruction of the dual-arm robot performing the gel tensile characterization task, the one-way deformation of the characterization process gel, the dual-arm motion constraint equation is:

[0046] ;

[0047] In the above two equations, the meanings of the parameters are as follows: And The dual-arm position constraint and the dual-arm attitude constraint of the dual-arm robot, which constitute the dual-arm motion constraint F ( q ) = [ f p ( q ) f o ( q ) ] T , , The entire configuration space of the dual-arm motion of the dual-arm robot, Indicates a set of real numbers, and n is the dimension of the constraint; Is the transpose matrix of the rotation matrix of the end coordinate system {E1} of the left arm of the dual-arm robot to the world coordinate system {W}; Is the relative position of the end of the dual-arm robot in the world coordinate system; Is the expected relative position of the end of the dual-arm robot; Is the row selection function of extracting the i-th row of the matrix, i is 2, 3, or 4; Is the inverse of the expected relative attitude of the end of the left arm of the dual-arm robot The left matrix of the quaternion ξ = [ w , x , y , z ] T Is the end attitude of the dual-arm robot in the world coordinate system; Is the inverse of the attitude of the end of the left arm of the dual-arm robot The left matrix of the quaternion Is the attitude of the end of the right arm of the dual-arm robot; the superscript T in each term indicates the transpose of the matrix.

[0048] Preferably, in step 1 of the above method, the trajectory planning algorithm used to plan the dual-arm joint trajectory that meets the dual-arm motion constraint conditions in the scene model is the AtlasRRT algorithm.

[0049] Preferably, in step 1 of the above method, a trajectory planning algorithm is used to plan the dual-arm joint trajectory that meets the dual-arm motion constraint conditions in the scene model in the following manner, including:

[0050] Step 12: Under the dual-arm motion constraints set in step 11, In step 1, remove the obstacle area caused by the scene model , we get the configuration space of the collision-free constraint manifold of the dual-arm robot , and then plan a path in the entire configuration space , connection starting position With target location The collision-free path is represented by the function ,in , , and for each τ ∈ [ 0 , 1 ] , whether there is a collision path ;

[0051] Step 13, in the entire configuration space In the example, we use the AtlasRRT algorithm from the starting position Perform random uniform sampling to obtain the initial configuration , the initial configuration is converted to Configuration space projected onto the collision-free constraint manifold , and obtain a collision-free path Internal configuration ;

[0052] Step 14: Define the valid atlas , for the configuration obtained in step 13 With valid atlas Each configuration in Compare and include the constrained configurations that satisfy the following constraints into the valid atlas :

[0053] ;

[0054] Among them, such as Figure 3 As shown, Position In-position The projection into tangent space at , Position In-position The transposed matrix of the orthogonal basis matrix in the tangent space; Position Relative to configuration The minimum distance in the tangent space; Position Relative to configuration The orthogonal basis matrix of the tangent space at ; Position and configuration The cosine of the angle in tangent space; Valid atlas The maximum radius of the bounded coverage area; Through configuration The logarithmic mapping of the tangent space at is obtained, satisfy:

[0055] [ J ( q ) Φ T ] ， Φ T = [ 0 I ] ;

[0056] In the above formula, For motion constraints In-position The Jacobian matrix at , Position In-position The transpose matrix of a set of orthogonal basis matrices of the tangent space at , I is The identity matrix, is the dimension of the identity matrix I, Position In-position The projection into tangent space at is:

[0057] ;

[0058] In the above formula, is the mapping from parameter space to tangent space; is an exponential mapping from parameter space to the configuration space of collision-free constraint manifolds; Position In-position The orthogonal basis matrix of the tangent space at ;

[0059] According to the above constraints, the Newton-Raphson method is used to align the shape Increment per iteration Perform iterative updates as follows:

[0060] [ J(q j ) Φ i T ] Δ q j =− [ F(q j ) Φ i T ( q j − q j i ) ] ;

[0061] In the above formula, For motion constraints In-position The Jacobian matrix at ; Is in position Motion constraints at

[0062] Repeat the iterative update until the configuration Satisfy the constraints and change the configuration Included in the valid atlas as a constrained configuration If the maximum number of iterations is exceeded, skip step 14 and return to step 13 for resampling;

[0063] Step 15: Repeat steps 13 and 14, and use the RRTConnect algorithm to calculate the Sampling is performed to obtain constrained configurations until a connection initial position is obtained from each constrained configuration plan With target location Collision-free path As the planned double-arm joint trajectory that meets the double-arm motion constraints;

[0064] During the planning process, if the current planning time exceeds the preset maximum planning time , then the planning is terminated and the incomplete dual-arm joint trajectory is output as the planned dual-arm joint trajectory that meets the dual-arm motion constraints.

[0065] Preferably, in step 2 of the above method, the torque sensors at the ends of the dual arms of the dual-arm robot are used to monitor and process abnormal information of the dual arms during operation in real time in the following manner, including:

[0066] Step 21: Use the torque sensor at the end of the dual-arm robot to obtain measurement data, and use the gravity compensation algorithm to eliminate the gravity of the dual-arm end gripper. Influence, get the actual contact torque of the double-arm end gripper , The expression is as follows:

[0067] E M a = [ E F a E T a ] = [ E F m E T m ] − [ E F G E T G ] ;

[0068] like Figure 4 As shown, and are the actual force and torque at the end of the dual-arm robot’s manipulator arm; and are the force and torque of the torque sensor of the dual-arm robot; and are the gravity and gravity torque of the end-of-arm gripper in the end-of-arm tool coordinate system {E}, respectively; is the gravity of the end-of-arm gripper in the world coordinate system {W}, and its center of gravity coordinates are expressed in the end-of-arm tool coordinate system {E} [ l x , l y , l z ] T 、 are the positions of the center of gravity coordinates on the x, y, and z axes of the double-arm end tool coordinate system {E}, respectively. The superscript T indicates the transpose of the matrix; is the rotation matrix from the dual-arm end tool coordinate system {E} to the world coordinate system {W}, then and Satisfy the following formula:

[0069] ;

[0070] Step 22, after processing by the gravity compensation algorithm in step 21, obtain the left arm end contact force of the left arm end tool coordinate system {E1} The right end of the arm contact force with the right end of the arm tool coordinate system {E2} And the contact force at the end of the left arm in the world coordinate system {W} is obtained by coordinate transformation. Contact force with the end of the right arm , according to the different stages of the gel operation, determine whether there are any abnormalities in the operation process:

[0071] If the gel is currently being demoulded and transported, the contact force at the end of the left arm should be Contact force with the end of the right arm Satisfy the following formula:

[0072] ;

[0073] in, The modulus represents the orientation quantity; is the contact force at the end of the left arm exerted on the gel during the gel demoulding and transportation process in the world coordinate system {W}; is the contact force at the end of the right arm exerted on the gel during the gel demoulding and transportation process in the world coordinate system {W}; is the torque at the end of the right arm applied to the gel during the gel demoulding and handling process in the world coordinate system {W}; is the torque at the end of the left arm applied to the gel during the gel demoulding and handling process in the world coordinate system {W}; and are the maximum contact force and torque that the gel is subjected to during the gel demoulding and handling process;

[0074] If the current stage is gel stretch characterization, due to the unidirectional stretching characteristics of the gel during the characterization process and the tensile force generated by the gel deformation, the contact force at the end of the left arm Contact force with the end of the right arm Satisfy the following formula:

[0075] ;

[0076] in, and are the minimum contact force and torque that the gel is subjected to during the set gel stretching process;

[0077] Step 23, in step 22, if the contact force and torque at the ends of the dual arms of the dual-arm robot do not satisfy the corresponding formula conditions during the handling or characterization stage, it is determined that an abnormality has occurred and the gel is discarded.

[0078] Preferably, in step 3 of the above method, under the monitoring of step 2, the dual-arm robot completes the gel demoulding and handling task and the gel stretching characterization task according to the dual-arm joint trajectory planned in step 1, and collects the gel performance data during the gel stretching characterization task in the following manner, including:

[0079] Step 31: Set the dual-arm robot's dual-arm collaboration speed and acceleration, and configure the kinematic parameters of the dual-arm joint trajectory;

[0080] Step 32, as Figure 5 As shown in the figure, during the gel stretching characterization task, the dual-arm robot collects the gel deformation distance and deformation torque in real time, receives the gel characterization data, and sends it to the public computer used to collect data for subsequent analysis and evaluation by experimental personnel.

[0081] Preferably, in the above method, the received gel characterization data includes polarizer angle and light intensity.

[0082] An embodiment of the present invention further provides a processing device, comprising:

[0083] at least one memory for storing one or more programs;

[0084] At least one processor can execute one or more programs stored in the memory, and when the one or more programs are executed by the processor, the processor can implement the above method.

[0085] The embodiments of the present invention further provide a readable storage medium storing a computer program, which can implement the above method when executed by a processor.

[0086] In summary, the method provided by the embodiment of the present application realizes trajectory planning of the dual-arm robot under the constraint condition through the Atlas RRT algorithm, effectively reduces the deformation loss of the gel in the gel carrying process, improves the controllability of the gel stretching operation and the consistency of experimental data, and in combination with the dual-arm end torque sensor, can discover and handle abnormal conditions in real time. The method covers the whole process of the chemical gel characterization experiment, can adapt to diversified experimental scenes and task requirements, and improves the efficiency and precision of gel performance data acquisition.

[0087] In order to more clearly show the technical solutions provided by the present application and the technical effects generated, the scheme provided by the embodiment of the present application is described in detail below with specific examples.

[0088] Embodiment 1

[0089] As shown in the formula (1), the embodiment of the present application provides a method for controlling a dual-arm robot to perform a chemical gel characterization experiment, which is a method for controlling a dual-arm robot to perform a high-throughput chemical gel characterization experiment, modeling a gel operation platform to obtain a scene model, and the modeling can select to use MVSNet or a SLAM method, comprising: Figure 1 Step 1, setting dual-arm motion constraint conditions of the dual-arm robot according to a gel characterization experiment task target, in the scene model of step 1, using an Atlas RRT algorithm to plan a dual-arm joint trajectory that meets the dual-arm motion constraint conditions, comprising the following steps:

[0090] Step 11, setting dual-arm motion constraint conditions of the dual-arm robot end according to a scheduling instruction of the dual-arm robot performing a gel characterization experiment task;

[0091] If the scheduling instruction of the dual-arm robot performing a gel demolding and carrying task, the dual-arm motion constraint equation is:

[0092]

[0093] ;

[0094] If the scheduling instruction of the dual-arm robot performing a gel stretching characterization task, since the gel is deformed in one direction in the characterization process, the dual-arm motion constraint equation is:

[0095] ;

[0096] In the above two equations, the meanings of the parameters are as follows: and are a dual-arm position constraint and a dual-arm attitude constraint of the dual-arm robot, which constitute a dual-arm motion constraint F ( q ) = [ f p ( q ) f o ( q ) ] T , , is a whole configuration space of the dual-arm motion of the dual-arm robot,​ represents a set of real numbers, and n is the dimension of the constraint; is the transposed matrix of the rotation matrix from the left arm end coordinate system {E1} of the dual-arm robot to the world coordinate system {W}; is the relative position of the ends of the two arms of the dual-arm robot in the world coordinate system; is the desired relative position of the ends of the two arms of the dual-arm robot; To extract the row selection function of the i-th row of the matrix, i takes values ​​of 2, 3, and 4; is the inverse of the desired relative posture of the left arm end of the dual-arm robot The left matrix, quaternion ξ = [ w , x , y , z ] T is the end posture of the dual-arm robot in the world coordinate system; The inverse of the posture of the left arm end of the dual-arm robot The left matrix of is the posture of the right arm end of the dual-arm robot; the superscript T in each term represents the transpose of the matrix.

[0097] Step 12: Set the configuration space of the collision-free constraint manifold of the dual-arm robot , and find a path in the configuration space , connection starting position and target location The collision-free path is: Specifically, under the dual-arm motion constraints set in step 11, in the entire configuration space In step 1, remove the obstacle area caused by the scene model , we get the configuration space of the collision-free constraint manifold of the dual-arm robot , and then plan a path in the entire configuration space , connection starting position With target location The collision-free path is represented by the function ,in , , and for each τ ∈ [ 0 , 1 ] , whether there is a collision path ;

[0098] Step 13, in the entire configuration space In the AtlasRRT algorithm, the starting position Perform random uniform sampling to obtain the initial configuration , by using the Newton-Raphson method to convert the initial configuration Projection onto the configuration space of the collision-free constraint manifold , and obtain a collision-free path Internal configuration ;

[0099] Step 14: Define the valid atlas , for the configuration obtained in step 13 With valid atlas Each configuration in For comparison, such as Figure 3 As shown, the constrained configurations that satisfy the following constraints are included in the valid atlas :

[0100] ;

[0101] in, Position In-position The projection into tangent space at , Position In-position The transposed matrix of the orthogonal basis matrix in the tangent space; Position Relative to configuration The minimum distance in the tangent space; Position Relative to configuration The orthogonal basis matrix of the tangent space at ; Position and configuration The cosine of the angle in tangent space at ; Valid atlas The maximum radius of the bounded coverage area; Through configuration The logarithmic mapping of the tangent space at is obtained, satisfy:

[0102] [ J ( q ) Φ T ] ， Φ T = [ 0 I ] ;

[0103] in, For motion constraints In-position The Jacobian matrix at , Position In-position The transpose matrix of a set of orthogonal basis matrices of the tangent space at , I is The identity matrix, is the dimension of the identity matrix I, Position In-position The projection into tangent space at is:

[0104] ;

[0105] in, is the mapping from parameter space to tangent space; is an exponential mapping from parameter space to the configuration space of collision-free constraint manifolds; Position In-position The orthogonal basis matrix of the tangent space at ; According to the above constraints, the Newton-Raphson method is used to align the shape Increment per iteration Perform iterative updates as follows:

[0106] [ J(q j ) Φ i T ] Δ q j =− [ F(q j ) Φ i T ( q j − q j i ) ] ;

[0107] in, For motion constraints In-position The Jacobian matrix at ; Is in position Motion constraints at

[0108] Repeat the iterative update until the configuration Satisfy the constraints and change the configuration Included in the valid atlas as a constrained configuration If the maximum number of iterations is exceeded, skip step 14 and return to step 13 for resampling;

[0109] Step 15, repeat steps 13 and 14, using RRTConnect in the configuration space Sampling is performed to obtain constrained configurations until a connection initial position is obtained from each constrained configuration plan With target location Collision-free path As the planned double-arm joint trajectory that meets the double-arm motion constraints;

[0110] During the planning process, if the current planning time exceeds the preset maximum planning time , then the planning is terminated and the incomplete dual-arm joint trajectory is output as the planned dual-arm joint trajectory that meets the dual-arm motion constraints.

[0111] Step 2: Use the torque sensors at the ends of the dual-arm robot's arms to monitor and process abnormal information during operation in real time, including the following steps:

[0112] Step 21: perform gravity identification and compensation on the torque data at the end of the dual arms: Specifically, use the torque sensor at the end of the dual arms of the dual-arm robot to obtain measurement data, and use the gravity compensation algorithm to eliminate the gravity of the gripper at the end of the dual arms. Influence, get the actual contact torque of the double-arm end gripper , The expression is as follows:

[0113] E M a = [ E F a E T a ] = [ E F m E T m ] − [ E F G E T G ] ;

[0114] in, and are the actual force and torque at the end of the dual-arm robot’s manipulator arm; and are the force and torque of the torque sensor of the dual-arm robot; and are the gravity and gravity torque of the end-of-arm gripper in the end-of-arm tool coordinate system {E}, respectively; is the gravity of the end-of-arm gripper in the world coordinate system {W}, and its center of gravity coordinates are expressed in the end-of-arm tool coordinate system {E} [ l x , l y , l z ] T 、 are the positions of the center of gravity coordinates on the x, y, and z axes of the double-arm end tool coordinate system {E}, respectively. The superscript T indicates the transpose of the matrix; is the rotation matrix from the dual-arm end tool coordinate system {E} to the world coordinate system {W}, then and Satisfy the following formula:

[0115] ;

[0116] in, is the gravity of the end-arm gripper in the world coordinate system {W}; is the gravity of the end-of-arm gripper in the end-of-arm tool coordinate system {E};

[0117] Step 22: Based on the gravity compensation algorithm in step 21, obtain the left arm end contact force of the left arm end tool coordinate system {E1} The right end of the arm contact force with the right end of the arm tool coordinate system {E2} And the contact force at the end of the left arm in the world coordinate system {W} is obtained by coordinate transformation. Contact force with the end of the right arm , according to the different stages of the gel operation, determine whether there are any abnormalities in the operation process:

[0118] If the gel is currently being demoulded and transported, the contact force at the end of the left arm should be Contact force with the end of the right arm Satisfy the following formula:

[0119] ;

[0120] in, represents the module of the orientation vector; represents the contact force of the left arm end on the gel in the gel demolding and carrying process in the world coordinate system {W}; represents the contact force of the right arm end on the gel in the gel demolding and carrying process in the world coordinate system {W}; represents the torque of the right arm end on the gel in the gel demolding and carrying process in the world coordinate system {W}; represents the torque of the left arm end on the gel in the gel demolding and carrying process in the world coordinate system {W}; represents the maximum contact force and torque of the gel in the gel demolding and carrying process, respectively; represents the maximum contact force and torque of the gel in the gel demolding and carrying process, respectively;

[0121] If the current is in the gel stretching characterization stage, due to the unidirectional stretching characteristics of the gel in the characterization process, and there is a stretching force generated by the deformation of the gel, the contact force of the left arm end and the contact force of the right arm end satisfy the following formula:

[0122] ;

[0123] wherein, and represent the minimum contact force and torque of the gel in the gel stretching process, respectively;

[0124] Step 23, in step 22, if the contact force and torque of the double-arm robot at the end of the double arm in the carrying or characterization stage do not satisfy the corresponding formula condition, it is confirmed that an abnormal situation occurs, and the gel is discarded. In this way, it can avoid the subsequent characterization data unreliable due to excessive deformation of the gel in the carrying process, and the data error and resource waste caused by the gel rupture in the stretching process.

[0125] Step 3, under the monitoring of step 2, the double-arm robot completes the gel demolding and carrying and gel stretching characterization task according to the double-arm joint trajectory planned in step 2, and collects the gel performance data during gel stretching characterization, including the following steps:

[0126] Step 31, set the cooperative speed and acceleration of the double-arm robot, and configure the kinematics parameters of the double-arm joint trajectory;

[0127] Step 32, during the execution of the gel demolding and stretching characterization task, the double-arm robot collects the gel deformation distance and deformation torque in real time, receives the polarization plate angle and light intensity and other gel characterization data, and sends them to the public computer for collecting data, for subsequent analysis and evaluation by the experimenters.

[0128] Step 4: After the dual-arm robot completes Step 3, it performs a reset operation, ending the current task flow. Specifically, the dual-arm robot's two manipulator arms move to the waste gel disposal device, discard the stretched gel, and reset the dual-arm robot to its initial position.

[0129] Furthermore, after step 4, if there are subsequent gel characterization experiment tasks, steps 1 to 4 are repeated until all gel characterization experiment tasks are completed.

[0130] In summary, the method of the present invention implements trajectory planning for a dual-arm robot under constraints using the AtlasRRT algorithm. This effectively reduces gel deformation during handling, improves the controllability of stretching operations, and enhances the consistency of experimental data. Combined with monitoring by the dual-arm end-torque sensors, it enables real-time detection and resolution of anomalies. This method covers the entire process of chemical gel characterization experiments, adapts to diverse experimental scenarios and task requirements, and improves the efficiency and accuracy of gel performance data collection.

[0131] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a program. The program can be stored in a computer-readable storage medium. When executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0132] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims. The information disclosed in the background technology section of this article is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as an admission or any form of implication that the information constitutes prior art already known to those skilled in the art.

Claims

1. A method for controlling a dual-arm robot to perform a chemical gel characterization experiment, characterized in that: Model the gel operation platform as a scene model, including: Step 1: Set the dual-arm motion constraints of the dual-arm robot according to the gel characterization experiment task, and use the trajectory planning algorithm in the scene model to plan the dual-arm joint trajectory that meets the dual-arm motion constraints; including: Step 11, according to the scheduling instruction of the dual-arm robot to perform the gel characterization experiment task, set the dual-arm motion constraint conditions of the dual-arm robot in the following manner; If the dual-arm robot executes the scheduling instruction of the gel demoulding and handling task, the dual-arm motion constraint equation is: ； If the dual-arm robot executes the scheduling instruction of the gel stretching characterization task and characterizes the unidirectional deformation of the gel during the characterization process, the dual-arm motion constraint equation is: ； In the above two equations, the meaning of each parameter is: and They are the dual-arm position constraint and posture constraint of the dual-arm robot, which together constitute the dual-arm motion constraint , , is the entire configuration space of the dual-arm robot's dual-arm motion, represents a set of real numbers, and n is the dimension of the constraint; is the transposed matrix of the rotation matrix from the left arm end coordinate system {E1} of the dual-arm robot to the world coordinate system {W}; is the relative position of the ends of the two arms of the dual-arm robot in the world coordinate system; is the desired relative position of the ends of the two arms of the dual-arm robot; To extract the row selection function of the i-th row of the matrix, i takes values ​​of 2, 3, and 4; is the inverse of the desired relative posture of the left arm end of the dual-arm robot The left matrix, quaternion is the end posture of the dual-arm robot in the world coordinate system; The inverse of the posture of the left arm end of the dual-arm robot The left matrix of is the posture of the right arm end of the dual-arm robot; the superscript T in each item represents the transpose of the matrix; Step 2: Use the torque sensors at the ends of the dual-arm robot's arms to monitor and process abnormal information during the operation of the dual-arm robot in real time; Step 3: Under the monitoring of step 2, the dual-arm robot completes the gel demoulding and handling tasks and the gel stretching characterization tasks according to the dual-arm joint trajectory planned in step 1, and collects gel performance data during the gel stretching characterization tasks; Step 4: After the dual-arm robot completes the operation in step 3, it performs a reset operation to end the current gel characterization experiment task.

2. The method for controlling a dual-arm robot to perform a chemical gel characterization experiment according to claim 1, characterized in that: In the method, the gel operation platform is modeled as a scene model using an MVSNet method or a SLAM method.

3. The method for controlling a dual-arm robot to perform a chemical gel characterization experiment according to claim 1, characterized in that: In step 1, the trajectory planning algorithm used to plan the dual-arm joint trajectory that meets the dual-arm motion constraint conditions in the scene model is the AtlasRRT algorithm.

4. The method for controlling a dual-arm robot to perform a chemical gel characterization experiment according to claim 1 or 3, characterized in that: In step 1, a trajectory planning algorithm is used to plan the dual-arm joint trajectory that meets the dual-arm motion constraint conditions in the scene model in the following manner, including: Step 12: Under the dual-arm motion constraints set in step 11, In step 1, remove the obstacle area caused by the scene model , we get the configuration space of the collision-free constraint manifold of the dual-arm robot , and then plan a path in the entire configuration space , connection starting position With target location The collision-free path is represented by the function ,in , , and for each , whether there is a collision path ; Step 13, in the entire configuration space In the example, we use the AtlasRRT algorithm from the starting position Perform random uniform sampling to obtain the initial configuration , the initial configuration is converted to Projection onto the configuration space of the collision-free constraint manifold , and obtain a collision-free path Internal configuration ; Step 14: Define the valid atlas , for the configuration obtained in step 13 With valid atlas Each configuration in Compare and include the constrained configurations that satisfy the following constraints into the valid atlas : ； in, Position In-position The projection into tangent space at , Position In-position The transposed matrix of the orthogonal basis matrix in the tangent space; Position Relative to configuration The minimum distance in the tangent space; Position Relative to configuration The orthogonal basis matrix of the tangent space at ; Position and configuration The cosine of the angle in tangent space; Valid atlas The maximum radius of the bounded coverage area; Through configuration The logarithmic mapping of the tangent space is obtained; Position In-position The projection into tangent space at is: ； is the mapping from parameter space to tangent space; is an exponential mapping from parameter space to the configuration space of collision-free constraint manifolds; Position In-position The orthogonal basis matrix of the tangent space at ; According to the above constraints, the Newton-Raphson method is used to align the shape Increment per iteration Perform iterative updates as follows: ； in, For motion constraints In-position The Jacobian matrix at ; Is in position Motion constraints at Repeat the iterative update until the configuration Satisfy the constraints and change the configuration Included in the valid atlas as a constrained configuration If the maximum number of iterations is exceeded, skip step 14 and return to step 13 for resampling; Step 15: Repeat steps 13 and 14, and use the RRTConnect algorithm to calculate the Sampling is performed to obtain constrained configurations until a connection initial position is obtained from each constrained configuration plan With target location Collision-free path As the planned double-arm joint trajectory that meets the double-arm motion constraints; During the planning process, if the current planning time exceeds the preset maximum planning time , then the planning is terminated and the incomplete dual-arm joint trajectory is output as the planned dual-arm joint trajectory that meets the dual-arm motion constraints.

5. The method for controlling a dual-arm robot to perform a chemical gel characterization experiment according to any one of claims 1-2, characterized in that: In step 2, the torque sensors at the ends of the dual arms of the dual-arm robot are used to monitor and process abnormal information of the dual arms during operation in real time in the following manner, including: Step 21: Use the torque sensor at the end of the dual-arm robot to obtain measurement data, and use the gravity compensation algorithm to eliminate the gravity of the dual-arm end gripper. Influence, get the actual contact torque of the double-arm end gripper , The expression is as follows: ； in, and are the actual force and torque at the end of the dual-arm robot’s manipulator arm; and are the force and torque of the torque sensor of the dual-arm robot; and are the gravity and gravity torque of the end-of-arm gripper in the end-of-arm tool coordinate system {E}, respectively; is the gravity of the end-of-arm gripper in the world coordinate system {W}, and its center of gravity coordinates are expressed in the end-of-arm tool coordinate system {E} 、 are the x-axis position, y-axis position, and z-axis position of the center of gravity coordinates in the double-arm end tool coordinate system {E}, respectively. The superscript T represents the transpose of the matrix; is the rotation matrix from the dual-arm end tool coordinate system {E} to the world coordinate system {W}, then and Satisfy the following formula: ； Step 22, after processing by the gravity compensation algorithm in step 21, obtain the left arm end contact force of the left arm end tool coordinate system {E1} The right end of the arm contact force with the right end of the arm tool coordinate system {E2} And the contact force at the end of the left arm in the world coordinate system {W} is obtained by coordinate transformation. Contact force with the end of the right arm , according to the different stages of the gel operation, determine whether there are any abnormalities in the operation process: If the gel is currently being demoulded and transported, the contact force at the end of the left arm should be Contact force with the end of the right arm Satisfy the following formula: ； in, The modulus represents the orientation quantity; is the contact force at the end of the left arm exerted on the gel during the gel demoulding and transportation process in the world coordinate system {W}; is the contact force at the end of the right arm exerted on the gel during the gel demoulding and transportation process in the world coordinate system {W}; is the torque at the end of the right arm applied to the gel during the gel demoulding and handling process in the world coordinate system {W}; is the torque at the end of the left arm applied to the gel during the gel demoulding and handling process in the world coordinate system {W}; and are the maximum contact force and torque that the gel is subjected to during the gel demoulding and handling process; If the current stage is gel stretch characterization, due to the unidirectional stretching characteristics of the gel during the characterization process and the tensile force generated by the gel deformation, the contact force at the end of the left arm Contact force with the end of the right arm Satisfy the following formula: ； in, and are the minimum contact force and torque that the gel is subjected to during the set gel stretching process; Step 23, in step 22, if the contact force and torque at the ends of the dual arms of the dual-arm robot do not satisfy the corresponding formula conditions during the handling or characterization stage, it is determined that an abnormality has occurred and the gel is discarded.

6. The method for controlling a dual-arm robot to perform a chemical gel characterization experiment according to any one of claims 1-2, characterized in that: In step 3, under the monitoring of step 2, the dual-arm robot completes the gel demoulding and handling task and the gel stretching characterization task according to the dual-arm joint trajectory planned in step 1, and collects gel performance data during the gel stretching characterization task in the following manner, including: Step 31: Set the dual-arm robot's dual-arm collaboration speed and acceleration, and configure the kinematic parameters of the dual-arm joint trajectory; Step 32: During the gel stretching characterization task, the dual-arm robot collects the gel deformation distance and deformation torque in real time, receives the gel characterization data, and sends them to a public computer used for data collection for subsequent analysis and evaluation by experimenters.

7. The method for controlling a dual-arm robot to perform a chemical gel characterization experiment according to claim 6, characterized in that: The received gel characterization data includes polarizer angle and light intensity.

8. A processing device, characterized in that include: at least one memory for storing one or more programs; At least one processor is capable of executing one or more programs stored in the memory, and when the one or more programs are executed by the processor, the processor is capable of implementing the method according to any one of claims 1 to 7.

9. A readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 can be implemented.

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