Robotic arm control method and apparatus, autonomous mobile cleaning device, and computer-readable storage medium

Abstract

Provided in the present disclosure are a robotic arm control method and apparatus, an autonomous mobile cleaning device, and a computer-readable storage medium. The method comprises: acquiring operating parameters of a robotic arm of an autonomous mobile cleaning device; and on the basis of the operating parameters, determining an operating state of the robotic arm.

Description

Robotic arm control methods and devices, self-moving cleaning equipment and computer-readable storage media

[0001] This disclosure claims priority to Chinese Patent Application No. 202510031999.4, filed on January 8, 2025, entitled "Method and Apparatus for Controlling a Robotic Arm and a Self-Moving Cleaning Device", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure relates to the field of electrical technology, and in particular to a robotic arm control method and apparatus, a self-moving cleaning device, and a computer-readable storage medium. Background Technology

[0003] With the development of smart appliance technology, self-propelled cleaning equipment has become an important cleaning tool, which can be configured for cleaning in homes and public places. In related technologies, to further enhance the cleaning capabilities of self-propelled cleaning equipment, a robotic arm is installed. This robotic arm can be configured to perform tasks such as overcoming obstacles, organizing items, sorting garbage, and handling large-volume waste.

[0004] However, in actual cleaning scenarios, the objects that the robotic arm needs to pick up are diverse and their weights vary greatly. Once the weight of an object exceeds the robotic arm's maximum picking capacity, forcibly grabbing the object will cause the robotic arm's structure and parts to bear forces beyond its safe bearing range, putting the robotic arm in an unsafe working state, affecting its lifespan, and may even directly cause damage to the robotic arm.

[0005] Therefore, how to effectively identify whether a robotic arm is in an unsafe working state, so as to take timely countermeasures, has become an urgent technical problem to be solved. (Application Content)

[0006] This disclosure provides a robotic arm control method and apparatus, a self-moving cleaning device, and a computer-readable storage medium, aiming to solve the technical problem in the related art that it is difficult to effectively identify the abnormal working state of the robotic arm, which leads to easy damage to the robotic arm.

[0007] In a first aspect, embodiments of this disclosure provide a robotic arm control method, including:

[0008] The operating parameters of the robotic arm obtained from the mobile cleaning equipment;

[0009] Based on the aforementioned operating parameters, the working state of the robotic arm is determined.

[0010] Optionally, in one embodiment of this disclosure, the operating parameters of the robotic arm obtained from the mobile cleaning equipment include:

[0011] The working parameters of the robotic arm of the self-moving cleaning device when performing an object acquisition action are obtained, wherein the object acquisition action includes at least one of clamping, grasping, and lifting.

[0012] Optionally, in one embodiment of this disclosure, the operating parameters of the robotic arm obtained from the mobile cleaning equipment include:

[0013] Obtain the working parameters of the robotic arm of the self-moving cleaning device when it is not performing an object acquisition action.

[0014] In one embodiment of this disclosure, the operating parameters may be acquired in real time.

[0015] Optionally, in one embodiment of this disclosure, the operating parameters of the robotic arm obtained from the mobile cleaning equipment include:

[0016] The cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm are obtained, wherein the preset calibration coefficient is configured to reflect the ratio of cross-axis current to output torque in the at least one joint motor.

[0017] Optionally, in one embodiment of this disclosure, obtaining the quadrature-axis current of at least one joint motor of the robotic arm includes:

[0018] The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to Clark transformation to obtain the quadrature axis current corresponding to the at least one joint motor.

[0019] Optionally, in one embodiment of this disclosure, obtaining the lever arm length of at least one joint motor of the robotic arm includes:

[0020] For each of at least one joint motor of the robotic arm, the lever arm length of the joint motor is determined as follows:

[0021]

[0022] Where r represents the lever arm length of the current joint motor, n is the number of arm segments from the last arm segment of the robotic arm to the current arm segment corresponding to the current joint motor, and i represents the arm segment number, i∈[1,n], where the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, and l i θ represents the arm length from the last arm segment to the i-th arm segment in the current arm segment. i This represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

[0023] Optionally, in one embodiment of this disclosure, the method further includes:

[0024] If the current arm segment is the first arm segment of the robotic arm closest to the self-moving cleaning device, determine θ. i The angle between the first arm segment and the plane where the self-moving cleaning device is located;

[0025] If the current arm segment is not the first arm segment, θ i =θ i+1 -μ i , where μ i This represents the offset angle of the i-th arm segment relative to the (i+1)-th arm segment.

[0026] In one embodiment of this disclosure, optionally, determining the working state of the robotic arm based on the working parameters includes:

[0027] Based on the operating parameters, the weight of the object is determined when the robotic arm performs the object acquisition action.

[0028] In one embodiment of this disclosure, optionally, determining the working state of the robotic arm based on the working parameters includes:

[0029] Based on the operating parameters, the object acquisition weight of the at least one joint motor is determined;

[0030] The working state of the at least one joint motor of the robotic arm is determined based on the weight of the object obtained from the at least one joint motor.

[0031] Optionally, in one embodiment of this disclosure, determining the object acquisition weight of the at least one joint motor based on the operating parameters includes:

[0032] For each of the at least one joint motor, the ratio of the product of the cross-axis current and the preset calibration coefficient of the joint motor to the lever arm length is determined as the object weight of the joint motor.

[0033] Optionally, in one embodiment of this disclosure, determining the object acquisition weight of the at least one joint motor based on the operating parameters includes:

[0034] Based on the cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, the object acquisition weight of the at least one joint motor is determined, wherein...

[0035]

[0036] W represents the weight of the object acquired by a single joint motor, I q Let be the quadrature-axis current of a single joint motor, r be the lever arm length of the arm segment directly driven by the single joint motor, K be the preset calibration coefficient of the single joint motor, α be the angular acceleration of the arm segment directly driven by the single joint motor during motion, j be the moment of inertia of the joint where the single joint motor is located, and F be the moment of inertia of the joint. f The frictional torque is the force applied during the movement of the arm segment directly driven by a single joint motor.

[0037] In one embodiment of this disclosure, optionally, determining the operating state of the at least one joint motor of the robotic arm based on the weight of the object obtained from the at least one joint motor includes:

[0038] If the object acquisition weight of any of the at least one joint motor exceeds a safe weight threshold, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

[0039] If the object weight acquired by any of the at least one joint motors is greater than the safe weight threshold in a specified number of consecutive object weight acquisition detections, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

[0040] Optionally, in one embodiment of this disclosure, if it is determined that the robotic arm is in an abnormal working state, the method further includes:

[0041] Generate a stop object acquisition command, and based on the stop object acquisition command, control the robotic arm to cancel the object acquisition action; and

[0042] Generate an overload alarm message.

[0043] In one embodiment of this disclosure, optionally, before obtaining the operating parameters of the robotic arm from the mobile cleaning device, the method further includes:

[0044] Determine the target location of the object to be acquired, which is required for the object acquisition action;

[0045] Set the current posture of the robotic arm to a grasping posture for the target position.

[0046] In one embodiment of this disclosure, optionally, before determining the target location of the item to be acquired for the object acquisition action, the method further includes:

[0047] The item to be acquired is identified by an item recognition device, wherein the item recognition device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

[0048] In one embodiment of this disclosure, optionally, setting the current posture of the robotic arm to a grasping posture for the target position includes:

[0049] Based on the target position, determine the posture configuration information of the robotic arm when it is in the grasping posture, wherein...

[0050] The attitude configuration information includes:

[0051] The angle between the first arm segment of the robotic arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located;

[0052] The offset angle of each arm segment in the robotic arm, excluding the first arm segment, relative to its adjacent first arm segment in the forearm segment; and

[0053] The length of each arm segment in the robotic arm.

[0054] In one embodiment of this disclosure, optionally, before obtaining the operating parameters of the robotic arm from the mobile cleaning device, the method further includes:

[0055] In response to a start command for the robotic arm, it is detected whether each joint motor of the robotic arm is in an effective working state. If each joint motor of the robotic arm is in an effective working state, the step of obtaining the working parameters of the robotic arm from the mobile cleaning equipment is allowed.

[0056] In one embodiment of this disclosure, optionally, after setting the current posture of the robotic arm to a grasping posture for the target position, the method further includes:

[0057] Adjust the robotic arm from the grasping posture to the weighing posture.

[0058] Optionally, in one embodiment of this disclosure, the operating parameters of the robotic arm obtained from the mobile cleaning equipment include:

[0059] During the adjustment process of the robotic arm from the grasping posture to the weighing posture, the working parameters of the robotic arm are monitored in real time to determine the working state of the robotic arm based on the working parameters.

[0060] as well as

[0061] If the robotic arm is in an abnormal working state, the adjustment process is interrupted and an overload protection strategy is executed.

[0062] If the robotic arm is in a normal working state, continue the adjustment process.

[0063] In one embodiment of this disclosure, optionally, determining the working state of the robotic arm based on the working parameters further includes:

[0064] If the object weight acquired by any of the at least one joint motor exceeds its corresponding safe weight threshold, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state.

[0065] If any one of the at least one joint motors detects an object weight greater than its corresponding safe weight threshold in a specified number of consecutive object weight detections, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state.

[0066] Secondly, embodiments of this disclosure provide a robotic arm control device, comprising:

[0067] The robotic arm working parameter acquisition unit is configured to acquire the working parameters of the robotic arm from the mobile cleaning equipment.

[0068] The robotic arm working state determination unit is configured to determine the working state of the robotic arm based on the working parameters.

[0069] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit includes:

[0070] The first execution unit is configured to acquire working parameters when the robotic arm of the self-moving cleaning device performs an object acquisition action, wherein the object acquisition action includes at least one of clamping, grasping, and lifting.

[0071] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit includes:

[0072] The second execution unit is configured to acquire working parameters of the robotic arm of the self-moving cleaning device when it does not perform an object acquisition action.

[0073] In one embodiment of this disclosure, the operating parameters may be acquired in real time.

[0074] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit includes:

[0075] The fourth execution unit is configured to acquire at least one of the following: cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is configured to reflect the ratio of cross-axis current to output torque in the at least one joint motor.

[0076] In one embodiment of this disclosure, optionally, the robotic arm operating parameter acquisition unit acquires the quadrature-axis current of at least one joint motor of the robotic arm in the following manner:

[0077] The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to Clark transformation to obtain the quadrature axis current corresponding to the at least one joint motor.

[0078] In one embodiment of this disclosure, optionally, the robotic arm operating parameter acquisition unit acquires the lever arm length of at least one joint motor of the robotic arm in the following manner:

[0079] For each of at least one joint motor of the robotic arm, the lever arm length of the joint motor is determined as follows:

[0080]

[0081] Where r represents the lever arm length of the current joint motor, n is the number of arm segments from the last arm segment of the robotic arm to the current arm segment corresponding to the current joint motor, and i represents the arm segment number, i∈[1,n], where the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, and l i θ represents the arm length from the last arm segment to the i-th arm segment in the current arm segment. i This represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

[0082] Optionally, in one embodiment of this disclosure, the device further includes:

[0083] Angle determination unit is configured to determine θ if the current arm segment is the first arm segment of the robotic arm closest to the self-moving cleaning device. i θ is the angle between the first arm segment and the plane where the self-moving cleaning device is located; if the current arm segment is not the first arm segment, θ i =θ i+1 -μ i , where μ i This represents the offset angle of the i-th arm segment relative to the (i+1)-th arm segment.

[0084] In one embodiment of this disclosure, the robotic arm working state determination unit is optionally configured to: determine the weight of the object when the robotic arm performs the object acquisition action based on the working parameters.

[0085] Optionally, in one embodiment of this disclosure, the robotic arm working state determination unit includes:

[0086] The object acquisition weight determination unit determines the object acquisition weight of the at least one joint motor based on the operating parameters.

[0087] The working state determination unit is configured to determine the working state of the at least one joint motor of the robotic arm based on the weight of the object obtained from the at least one joint motor.

[0088] Optionally, in one embodiment of this disclosure, the object weight determination unit includes:

[0089] The fifth execution unit is configured to, for each of the at least one joint motors, determine the ratio of the product of the cross-axis current of the joint motor and the preset calibration coefficient to the lever arm length, as the object weight of the joint motor.

[0090] Optionally, in one embodiment of this disclosure, the object weight determination unit includes:

[0091] The sixth execution unit is configured to determine the object acquisition weight of the at least one joint motor based on the cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, wherein...

[0092]

[0093] W represents the weight of the object acquired by a single joint motor, I q Let be the quadrature-axis current of a single joint motor, r be the lever arm length of the arm segment directly driven by the single joint motor, K be the preset calibration coefficient of the single joint motor, α be the angular acceleration of the arm segment directly driven by the single joint motor during motion, j be the moment of inertia of the joint where the single joint motor is located, and F be the moment of inertia of the joint. f The frictional torque is the force applied during the movement of the arm segment directly driven by a single joint motor.

[0094] Optionally, in one embodiment of this disclosure, the working state determination unit is configured to:

[0095] If the object acquisition weight of any of the at least one joint motors is greater than the safe weight threshold, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state. Alternatively, if the object acquisition weight of any of the at least one joint motors is greater than the safe weight threshold in a specified number of consecutive object acquisition weight detections, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

[0096] Optionally, in one embodiment of this disclosure, the device further includes:

[0097] The sixth execution unit is configured to generate a stop object acquisition command if it is determined that the robotic arm is in an abnormal working state, and control the robotic arm to cancel the object acquisition action based on the stop object acquisition command;

[0098] The overweight alarm unit is configured to generate overweight alarm information.

[0099] Optionally, in one embodiment of this disclosure, the device further includes:

[0100] The target location determination unit is configured to determine the target location of the object to be acquired, which is required for the object acquisition action, before the robotic arm working parameter acquisition unit acquires the working parameters.

[0101] The grasping posture setting unit is configured to set the current posture of the robotic arm to a grasping posture for the target position.

[0102] Optionally, in one embodiment of this disclosure, the device further includes:

[0103] The item identification unit is configured to identify the item to be acquired by an item identification device before the target location determination unit determines the target location, wherein the item identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

[0104] Optionally, in one embodiment of this disclosure, the grasping posture setting unit is configured to:

[0105] Based on the target position, the posture configuration information of the robotic arm when it is in the grasping posture is determined, wherein the posture configuration information includes:

[0106] The angle between the first arm segment of the robotic arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located;

[0107] The offset angle of each arm segment in the robotic arm, excluding the first arm segment, relative to its adjacent first arm segment in the forearm segment; and

[0108] The length of each arm segment in the robotic arm.

[0109] Optionally, in one embodiment of this disclosure, the device further includes:

[0110] The robotic arm initial detection unit is configured to detect whether each joint motor of the robotic arm is in an effective working state in response to a start command for the robotic arm before the robotic arm working parameter acquisition unit acquires the working parameters. If each joint motor of the robotic arm is in an effective working state, the robotic arm working parameter acquisition unit is allowed to acquire the working parameters.

[0111] Optionally, in one embodiment of this disclosure, the device further includes:

[0112] The weighing posture adjustment unit is configured to adjust the robotic arm from the grasping posture to the weighing posture after the grasping posture setting unit sets the current posture of the robotic arm to a grasping posture for the target position.

[0113] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit includes:

[0114] The adjustment process monitoring unit is configured to monitor the working parameters of the robotic arm in real time during the adjustment process of adjusting the robotic arm from the grasping posture to the weighing posture, so as to determine the working state of the robotic arm based on the working parameters.

[0115] The sixth execution unit is configured to interrupt the adjustment process and execute an overload protection strategy if the working state of the robotic arm is an abnormal working state.

[0116] The seventh execution unit is configured to continue the adjustment process if the working state of the robotic arm is the normal working state.

[0117] Optionally, in one embodiment of this disclosure, the robotic arm working state determination unit is configured to:

[0118] If the object acquisition weight of any of the at least one joint motors is greater than its corresponding safe weight threshold, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state. Alternatively, if the object acquisition weight of any of the at least one joint motors is greater than its corresponding safe weight threshold in a specified number of consecutive object acquisition weight detections, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state.

[0119] Thirdly, embodiments of this disclosure provide a self-moving cleaning device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the method described in any one of the first aspects above.

[0120] Fourthly, embodiments of this disclosure provide a computer-readable storage medium storing computer-executable instructions configured to perform the method described in the first aspect above.

[0121] The above technical solution addresses the problem in related technologies where it is difficult to effectively identify abnormal operating states of robotic arms, leading to easy damage. It determines the current operating state of the robotic arm by analyzing its working parameters. Specifically, it infers whether the robotic arm is in an unsafe operating state based on its current performance, facilitating timely identification and response in real-world scenarios where the robotic arm is carrying an excessively heavy load. This solution avoids prolonged overloading of the robotic arm, increasing its flexibility and safety, improving the overall performance of the self-moving cleaning equipment, and enhancing the user experience. Attached Figure Description

[0122] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0123] Figure 1 shows a flowchart of a robotic arm control method according to an embodiment of the present disclosure;

[0124] Figure 2 shows a flowchart of a robotic arm control method according to another embodiment of the present disclosure;

[0125] Figure 3 shows a schematic diagram of a robotic arm structure according to an embodiment of the present disclosure;

[0126] Figure 4 shows a flowchart of a robotic arm control method according to another embodiment of the present disclosure;

[0127] Figure 5 shows a flowchart of a robotic arm control method according to yet another embodiment of the present disclosure;

[0128] Figure 6 shows a block diagram of a robotic arm control device according to an embodiment of the present disclosure;

[0129] Figure 7 shows a block diagram of a self-moving cleaning device according to an embodiment of the present disclosure. Detailed Implementation

[0130] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0131] Figure 1 shows a flowchart of a robotic arm control method according to an embodiment of the present disclosure.

[0132] As shown in Figure 1, a robotic arm control method according to an embodiment of the present disclosure includes:

[0133] Step 102: Obtain the working parameters of the robotic arm from the mobile cleaning equipment.

[0134] The robotic arm of a self-propelled cleaning device performs tasks including but not limited to assisting the device in overcoming obstacles, organizing items, sorting waste, and handling large-volume waste. Its working parameters refer to the parameter configuration of the robotic arm during these tasks. In other words, the working parameters of the robotic arm reflect its performance in the current working state.

[0135] In one possible design, the operating parameters include quadrature-axis current, lever arm length, and preset calibration coefficients.

[0136] In another possible design, the operating parameters include quadrature axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque.

[0137] Therefore, more specifically, the working parameters of a robotic arm reflect its performance under the influence of its actual load in the current working state.

[0138] In one possible design, step 102 includes: acquiring the working parameters of the robotic arm of the self-moving cleaning device when performing an object acquisition action.

[0139] At this point, the robotic arm, in its current working state, is actually carrying the object it needs to acquire for its object acquisition action. During the object acquisition process, the robotic arm of the self-moving cleaning device may encounter situations where the acquired item is too heavy, potentially leading to an unsafe operating state for the device. In other words, the working parameters of the robotic arm when performing the object acquisition action are a specific manifestation of its current working state.

[0140] The object acquisition action includes at least one of clamping, grasping, and lifting.

[0141] Optionally, the robotic arm has at least one gripper configured to grip an item.

[0142] Optionally, the robotic arm has at least one gripper configured to grasp an item.

[0143] Optionally, the robotic arm has at least one shovel, configured to scoop up and lift the item.

[0144] In one possible design, the gripper, the claw, or the shovel may be located at the end of any segment of the robotic arm. Optionally, the gripper, the claw, or the shovel may be located at the end of the last segment of the robotic arm that is furthest from the self-moving cleaning device.

[0145] In one possible design, step 102 includes: acquiring the operating parameters of the robotic arm of the self-moving cleaning device when it is not performing an object acquisition action.

[0146] When the robotic arm is not performing an object-grabbing action, the self-moving cleaning device may be in standby mode or in an operating state where the robotic arm is not in use. In this case, although the robotic arm is not performing an object-grabbing action, it may still encounter situations where the retrieved items are overweight. For example, the user may hang other items, such as decorations or daily necessities, on the robotic arm. Furthermore, during the movement of the self-moving cleaning device, or when the robotic arm was previously performing an object-grabbing action, items may become entangled, hooked, or trapped on the robotic arm, causing the actual weight of the items to be assigned to the robotic arm. It can be understood that in this situation, the robotic arm's actual load in its current operating state is either empty or passively loaded with objects from a previous object-grabbing action.

[0147] All of the above situations may cause the self-propelled cleaning equipment to be in an unsafe operating state. Since the operating parameters of the robotic arm when it is not performing an object acquisition action are a specific manifestation of the robotic arm's current operating state, the current operating state of the robotic arm can be determined by these parameters, so as to effectively identify whether the robotic arm is in an unsafe operating state.

[0148] Step 104: Determine the working state of the robotic arm based on the working parameters.

[0149] Since the working parameters of a robotic arm can reflect its performance under the influence of its actual load in the current working state, we can infer the current working state of the robotic arm based on this performance.

[0150] The above technical solution determines the current working state of the robotic arm by analyzing its operating parameters. Specifically, it infers whether the robotic arm is in an unsafe operating state based on its current performance, facilitating timely identification and response in scenarios where the robotic arm is carrying an excessively heavy load. This solution allows for the timely interruption of overloaded operations, preventing prolonged overloading, increasing the flexibility and safety of the robotic arm, and ultimately improving the overall performance and user experience of the self-moving cleaning equipment.

[0151] In one possible design, step 104 includes: when determining the working state of the robotic arm, determining the object acquisition weight of the at least one joint motor based on the working parameters; and then determining the working state of the at least one joint motor of the robotic arm based on the object acquisition weight of the at least one joint motor.

[0152] The object acquisition weight mentioned here refers to the total load of the current arm segment directly driven by the joint motor. In one possible design, the object acquisition weight of a single joint motor is the sum of the weight of all arm segments from the current arm segment directly driven by the joint motor to the end arm segment of the robotic arm adjacent to the object to be acquired, and the weight of the object to be acquired.

[0153] Therefore, the working status of several joint motors in the robotic arm can be used to reflect whether the robotic arm is carrying an object that is too heavy, or in other words, whether the robotic arm is in an unsafe working state of carrying an object that is too heavy.

[0154] In one possible design, step 104 includes: determining the weight of the object when the robotic arm performs the object acquisition action based on the operating parameters. The weight of the object when the robotic arm performs the object acquisition action is the effective load-bearing capacity of the robotic arm during this action, reflecting its ability to support the acquired content. Optionally, if this effective load-bearing capacity exceeds the maximum effective load that the robotic arm can bear, it can be determined that the robotic arm is in an unsafe operating state of carrying an overloaded object. Therefore, the weight of the object when the robotic arm performs the object acquisition action can also serve as a valid basis for identifying the robotic arm's operating state.

[0155] Optionally, for any joint motor, the weight of all arm segments from the current arm segment directly driven by the joint motor to the end arm segment of the robotic arm adjacent to the object to be acquired can be obtained, and the difference between the object acquisition weight corresponding to the joint motor and the weight of all arm segments can be determined as the weight of the object when the robotic arm performs the object acquisition action.

[0156] The weight of the object picked up by the robotic arm during an object-grabbing action reflects the overall actual load-bearing capacity of the robotic arm. This actual load-bearing capacity can, to some extent, indicate whether the robotic arm is overloaded, or whether it is operating in an unsafe condition due to excessive load. Therefore, the weight of the object picked up by the robotic arm during an object-grabbing action can serve as a valid basis for identifying the robotic arm's working status.

[0157] The technical solution of this disclosure will now be described in detail by combining two methods for calculating the weight of an object using a joint motor.

[0158] Based on the embodiment shown in FIG1, FIG2 shows a flowchart of a robotic arm control method according to another embodiment of the present disclosure.

[0159] As shown in Figure 2, a robotic arm control method according to another embodiment of this disclosure includes:

[0160] Step 202: Obtain the cross-axis current, lever arm length, and preset calibration coefficient of at least one joint motor of the robotic arm.

[0161] In one possible design, the cross-axis current of at least one joint motor of the robotic arm is obtained by: acquiring the three-phase current of the at least one joint motor, and performing a Clark transform on the three-phase current to obtain the cross-axis current corresponding to the at least one joint motor. To a certain extent, the cross-axis current of the joint motor can be regarded as the output torque of the joint motor in the current dimension.

[0162] The preset calibration coefficient is configured to reflect the ratio of quadrature-axis current to output torque in the at least one articulated motor. Specifically, during the production process of each articulated motor, the ratio of test quadrature-axis current to test output torque for each load can be measured by applying multiple loads respectively. Finally, the preset calibration coefficient corresponding to the articulated motor is determined by the ratio of multiple loads. The preset calibration coefficient of each articulated motor is stored in the controller of the articulated motor or in the central processing unit of the self-moving cleaning equipment to which the articulated motor belongs, for use when calculating the weight of the object obtained by the articulated motor.

[0163] Optionally, the average of the proportions of multiple loads can be set as the preset calibration coefficient corresponding to the joint motor.

[0164] In one possible design, the lever arm length of at least one joint motor of the robotic arm is obtained as follows: For each of the at least one joint motors of the robotic arm, the lever arm length of that joint motor is determined as:

[0165]

[0166] Where r represents the lever arm length of the current joint motor, n is the number of arm segments from the last arm segment of the robotic arm to the current arm segment corresponding to the current joint motor, and i represents the arm segment number, i∈[1,n], where the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, and l i θ represents the arm length from the last arm segment to the i-th arm segment in the current arm segment. i Let θ represent the angle between the i-th arm segment and the plane containing the self-moving cleaning device. Specifically, if the current arm segment is the first arm segment of the robotic arm closest to the self-moving cleaning device, then θ is determined. i θ is the angle between the first arm segment and the plane containing the self-moving cleaning device. If the current arm segment is not the first arm segment, θ i =θ i+1 -μ i , where μ i This represents the offset angle of the i-th arm segment relative to the (i+1)-th arm segment.

[0167] Based on the above and Figure 3, if the self-moving cleaning device includes a first arm segment away from the main body of the self-moving cleaning device and a second arm segment adjacent to the main body of the self-moving cleaning device, the first arm segment is controlled by a first joint motor, and the second arm segment is controlled by a second joint motor, then the angle between the second arm segment and the plane where the self-moving cleaning device is located is a known quantity A in the posture configuration information when the robotic arm is in the grasping posture, and the offset angle of the first arm segment relative to the direction of the second arm segment is a known quantity B in the posture configuration information, then the angle between the first arm segment and the plane where the self-moving cleaning device is located is AB.

[0168] Based on this, the lever arm length of the first joint motor is actually equivalent to segment x shown in Figure 3, which is the first product of the length L1 of the first joint and cos(AB). The lever arm length of the second joint motor is actually equivalent to the sum of segment x and segment y shown in Figure 3, where segment x is the second product of the length L2 of the second joint and cos A. Therefore, the sum of segment x and segment y is the sum of the first product and the second product.

[0169] Of course, the number of arm segments of the robotic arm of the self-moving cleaning device can be any number that meets the actual object acquisition needs, and is not limited to the two segments shown in Figure 3.

[0170] Step 204: Based on the cross-axis current, lever arm length, and preset calibration coefficient of at least one joint motor of the robotic arm, determine the object acquisition weight of the at least one joint motor.

[0171] The cross-axis current, lever arm length, and preset calibration coefficient of any joint motor each reflect the load-bearing capacity of the joint motor in different dimensions. Therefore, the actual weight weighed by the joint motor can be determined based on the three factors. That is, the weight borne by the arm segment directly driven by the joint motor when the robotic arm acquires the object, which is also the weight of the acquired object.

[0172] In one possible design, for each of the at least one joint motor, the ratio of the product of the cross-axis current of the joint motor and the preset calibration coefficient to the lever arm length is determined as the object weight of the joint motor.

[0173] Specifically, when the robotic arm picks up an object, the joint motor needs to overcome additional resistance to do work. At this time, the current increases, and this increase is proportional to the quadrature-axis current. The output torque of the joint motor is calculated as follows:

[0174] T e =K×I q ,

[0175] Among them, T e This represents the output torque of the articulated motor, where K is the preset calibration coefficient of the articulated motor, and I... q It is the q-axis current value after decoupling of the articulated motor, that is, the quadrature-axis current of the articulated motor.

[0176] When the robotic arm picks up an object, its load torque can be expressed as:

[0177] T l =α*j+F f +T g ,

[0178] Where α is the angular acceleration of the arm joint movement directly driven by the articulated motor, j is the moment of inertia of the joint where the articulated motor is located, and F f T is the frictional torque in the arm joint movement directly driven by the articulated motor. g The weight of the object acquired by the robotic arm and the weight of the robotic arm segments themselves, when the robotic arm is in a steady state (stationary or uniform motion), is the output torque T of the joint motor. e and load torque T l Equal, that is:

[0179] K*I q =α*j+F f +T g .

[0180] Furthermore, T g =W*r, where W is the weight of the object acquired by the articulated motor, and r is the lever arm length of the arm segment directly driven by the articulated motor. Therefore, the calculation method for the weight of the object acquired by the articulated motor can be deduced as follows:

[0181]

[0182] Based on this, if we ignore the effects of angular acceleration and frictional torque, that is, set angular acceleration and frictional torque to zero, the calculation method for the weight of the object obtained by the joint motor is as follows:

[0183]

[0184] That is, the weight of the object obtained by the joint motor is the ratio of the product of the cross-axis current of the joint motor and the preset calibration coefficient to the lever arm length.

[0185] Step 206: Based on the weight of the object obtained from the at least one joint motor, determine the working state of the at least one joint motor of the robotic arm.

[0186] For a single articulated motor, the object acquisition weight is the weight it bears when acquiring the object. In other words, the object acquisition weight of the articulated motor reflects the actual load situation when acquiring the object, and this complex actual situation is a characteristic manifestation of the working state of the articulated motor. Therefore, its working state can be determined based on the object acquisition weight of the articulated motor.

[0187] The above technical solution calculates the actual load on the joint motor when acquiring an object by using the joint motor's cross-axis current, lever arm length, and preset calibration coefficients. This calculation serves as the basis for judging the joint motor's working status, facilitating timely identification and response to situations where the robotic arm is carrying an excessively heavy object. This solution avoids prolonged periods of excessive weight on the robotic arm, increasing its flexibility and safety, improving the overall performance of self-propelled cleaning equipment, and enhancing the user experience.

[0188] Based on the embodiment shown in FIG2, FIG4 shows a flowchart of a robotic arm control method according to another embodiment of the present disclosure.

[0189] As shown in Figure 4, a robotic arm control method according to another embodiment of the present disclosure includes:

[0190] Step 402: Obtain the cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm.

[0191] Step 404: Based on the cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, determine the object acquisition weight of the at least one joint motor, wherein...

[0192]

[0193] W represents the weight of the object acquired by a single joint motor, I q Let be the quadrature-axis current of a single joint motor, r be the lever arm length of the arm segment directly driven by the single joint motor, K be the preset calibration coefficient of the single joint motor, α be the angular acceleration of the arm segment directly driven by the single joint motor during motion, j be the moment of inertia of the joint where the single joint motor is located, and F be the moment of inertia of the joint. f The frictional torque is the force applied during the movement of the arm segment directly driven by a single joint motor.

[0194] Step 406: Based on the weight of the object obtained from the at least one joint motor, determine the working state of the at least one joint motor of the robotic arm.

[0195] In the above technical solution, the effects of rotational inertia, angular acceleration and frictional torque are considered when calculating the weight of the object. This allows for a more accurate calculation of the actual load-bearing capacity of the joint motor, which in turn facilitates the precise determination of the working state of the joint motor and enables more accurate identification of the situation where the robotic arm is carrying an overweight object in actual scenarios.

[0196] Furthermore, the derivation process of the formula for calculating the weight of the object in the embodiment shown in Figure 4 has been described in the embodiment shown in Figure 2, and will not be repeated here.

[0197] Of course, in one embodiment, any of the following information items can be obtained from at least one joint motor of the robotic arm: cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque, as a basis for determining the working state of the robotic arm, and is not limited to the examples given in Figures 2 and 4.

[0198] Based on the embodiments shown in Figures 2 and 4, optionally, the working state of the at least one joint motor of the robotic arm is determined as follows: if the object acquisition weight of any of the at least one joint motor is greater than a safe weight threshold, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

[0199] Each joint motor has a corresponding safe weight threshold, which reflects the maximum weight load capacity of the corresponding joint motor when acquiring an object without exceeding the safe weight threshold. Based on this, if any joint motor in the robotic arm acquires an object with a weight greater than the safe weight threshold, it indicates that the current weight load capacity of that joint motor exceeds its maximum weight load capacity without exceeding the safe weight threshold. This can be determined as overloading of the joint motor, causing the robotic arm to be in an abnormal working state.

[0200] Based on the embodiments shown in Figures 2 and 4, optionally, the working state of the at least one joint motor of the robotic arm is determined as follows: if the object acquisition weight of any of the at least one joint motor is greater than the safe weight threshold in the object acquisition weight detection for a specified number of consecutive times, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

[0201] Each joint motor corresponds to a safe weight threshold, which reflects the maximum weight load capacity of the corresponding joint motor when acquiring an object without exceeding the safe weight threshold. Based on this, if the weight of an object acquired by any joint motor in at least one of the robotic arm's joint motors exceeds the safe weight threshold for a specified number of consecutive tests, it indicates that the current weight load capacity of that joint motor has consistently exceeded its maximum weight load capacity without exceeding the safe weight threshold during the specified number of tests. Therefore, it can be determined that the joint motor is operating at excessive weight, causing the robotic arm to be in an abnormal operating state.

[0202] All of the above technical solutions can effectively identify whether the joint motor is overloaded, thereby further effectively determining whether the robotic arm is in an abnormal working state.

[0203] Optionally, based on any of the above embodiments, if it is determined that the robotic arm is in an abnormal working state, a stop object acquisition command is generated, and based on the stop object acquisition command, the robotic arm is controlled to cancel the object acquisition action. That is, once the robotic arm is in an abnormal working state, the current object acquisition action will no longer be executed, and the overload work of the joint motor and the robotic arm will be terminated in a timely manner.

[0204] In addition, when generating the command to stop acquiring objects, an overload alarm is also generated to alert the user to the robotic arm's overload operation. Optionally, the overload alarm may include, but is not limited to, sending audio information or displaying information on a screen via the self-moving cleaning device and / or other electronic devices connected to the self-moving cleaning device.

[0205] In addition, based on any of the above embodiments, any working parameters are acquired in real time, that is, the working parameters are directly acquired during the real-time operation of the self-moving cleaning equipment, so as to identify the working status of the robotic arm in a timely, fast and effective manner.

[0206] Figure 5 shows a flowchart of a robotic arm control method according to yet another embodiment of the present disclosure.

[0207] As shown in Figure 5, a robotic arm control method according to another embodiment of this disclosure includes:

[0208] Step 502: In response to the start command for the robotic arm of the self-moving cleaning device, detect whether each joint motor of the robotic arm is in an effective working state.

[0209] The fact that the joint motors are in an effective working state indicates that the joint motors can operate normally and have the ability to drive the arm segments. If each joint motor of the robotic arm is in an effective working state, it means that the robotic arm has the ability to normally acquire objects. Based on this, the working state of the robotic arm can be further detected.

[0210] Step 504: If each joint motor of the robotic arm is in an effective working state, the item to be acquired is identified by the item recognition device.

[0211] Before acquiring an object, it is necessary to first identify the object to be acquired in order to perform further operations such as grasping, clamping, and pushing on the object.

[0212] The item recognition device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor. Of course, the item recognition device can also be any other device that meets the actual needs of item recognition, and is not limited to the examples above.

[0213] Step 506: Determine the target location of the object to be acquired for the object acquisition action, and set the current posture of the robotic arm to a grasping posture for the target location.

[0214] After identifying the item to be retrieved, the relative position between the item and the self-moving cleaning device can be identified by a sensor with ranging function, which serves as the target position. Based on this target position, the current posture of the robotic arm is transformed into a grasping posture that allows it to grab the item at that target position through mechanical motion.

[0215] Optionally, while changing the current posture of the robotic arm, the self-moving cleaning device can be driven to move towards the item to be acquired, so that the self-moving cleaning device moves to a position where its own robotic arm can effectively acquire the item.

[0216] When setting the grasping posture, the posture configuration information of the robotic arm in the grasping posture can be determined based on the target position. That is, the posture configuration information of each arm segment of the robotic arm is determined by the relative position of the target position and the self-moving cleaning device.

[0217] The posture configuration information includes: the angle between the first segment of the robotic arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located; the offset angle of each segment of the robotic arm (excluding the first segment) relative to its nearest neighbor in the direction of the first segment; and the arm length of each segment of the robotic arm. Based on the aforementioned angle, offset angle, and arm length, the relative positional relationship of each segment can be determined, thereby determining the grasping posture of the entire robotic arm.

[0218] Step 508: Adjust the robotic arm from the grasping posture to the weighing posture.

[0219] It is understandable that the grasping posture is the posture of the robotic arm when it is positioned to grasp the object to be grasped. Under the grasping posture, the robotic arm does not attempt to grasp the object to be grasped.

[0220] The weighing posture is the posture of the robotic arm when it attempts to acquire an object, causing a change in the object's displacement. This process is very brief; it is the initial, short-term attempt by the robotic arm to acquire the object after it has positioned itself in a grasping posture. During this process, the displacement of the object is very small.

[0221] Furthermore, step 508 can be understood as initiating the action of adjusting the robotic arm from the grasping posture to the weighing posture.

[0222] Step 510: During the adjustment process of the robotic arm from the grasping posture to the weighing posture, the working parameters of the robotic arm are monitored in real time to determine the working state of the robotic arm based on the working parameters.

[0223] Step 512: If the working state of the robotic arm is abnormal, the adjustment process is interrupted and the overload protection strategy is executed; otherwise, if the working state of the robotic arm is normal, the adjustment process continues.

[0224] In other words, during the brief period after the robotic arm has positioned itself to grasp the object, it attempts to acquire it. The robotic arm's working status is monitored in real time. If the robotic arm's working status becomes abnormal, the process of acquiring the object is interrupted, and an overload protection strategy is implemented.

[0225] Optionally, the overload protection strategy includes any action that can prompt the user to pay attention to the behavior of the robotic arm, such as generating an overload alarm message.

[0226] Optionally, the overload protection strategy includes any operation that interrupts the overload operation of the robotic arm, such as commanding the robotic arm to be unloaded or retracting the robotic arm.

[0227] Furthermore, if the object acquisition weight detected by any of the at least one joint motor exceeds its corresponding safe weight threshold, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state. Alternatively, if the object acquisition weight detected by any of the at least one joint motor exceeds its corresponding safe weight threshold in a specified number of consecutive object acquisition weight detections, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state. This solution has been explained above and will not be repeated here.

[0228] The above technical solution allows for the detection of the robotic arm's working capacity level both before and during the adjustment process from the grasping posture to the weighing posture after startup. This facilitates timely identification of insufficient robotic arm capacity in various working scenarios, particularly accurately identifying situations where the robotic arm is carrying an overloaded object and taking appropriate countermeasures. This solution enables the timely interruption of overloaded operations, preventing prolonged overloading, increasing the flexibility and safety of the robotic arm, and ultimately improving the overall performance of the self-moving cleaning equipment and enhancing the user experience.

[0229] Figure 6 shows a block diagram of a robotic arm control device according to an embodiment of the present disclosure.

[0230] As shown in Figure 6, this embodiment of the present disclosure provides a robotic arm control device 600, including:

[0231] The robotic arm working parameter acquisition unit 602 is configured to acquire the working parameters of the robotic arm from the mobile cleaning equipment.

[0232] The robotic arm working state determination unit 604 is configured to determine the working state of the robotic arm based on the working parameters.

[0233] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit 602 includes:

[0234] The first execution unit is configured to acquire working parameters when the robotic arm of the self-moving cleaning device performs an object acquisition action, wherein the object acquisition action includes at least one of clamping, grasping, and lifting.

[0235] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit 602 includes:

[0236] The second execution unit is configured to acquire working parameters of the robotic arm of the self-moving cleaning device when it does not perform an object acquisition action.

[0237] In one embodiment of this disclosure, the operating parameters may be acquired in real time.

[0238] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit 602 includes:

[0239] The fourth execution unit is configured to acquire at least one of the following: cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is configured to reflect the ratio of cross-axis current to output torque in the at least one joint motor.

[0240] In one embodiment of this disclosure, optionally, the robotic arm operating parameter acquisition unit 602 acquires the quadrature-axis current of at least one joint motor of the robotic arm in the following manner:

[0241] The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to Clark transformation to obtain the quadrature axis current corresponding to the at least one joint motor.

[0242] In one embodiment of this disclosure, optionally, the robotic arm operating parameter acquisition unit 602 acquires the lever arm length of at least one joint motor of the robotic arm in the following manner:

[0243] For each of at least one joint motor of the robotic arm, the lever arm length of the joint motor is determined as follows:

[0244]

[0245] Where r represents the lever arm length of the current joint motor, n is the number of arm segments from the last arm segment of the robotic arm to the current arm segment corresponding to the current joint motor, and i represents the arm segment number, i∈[1,n], where the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, and l i θ represents the arm length from the last arm segment to the i-th arm segment in the current arm segment. i This represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

[0246] Optionally, in one embodiment of this disclosure, the robotic arm control device 600 further includes:

[0247] Angle determination unit is configured to determine θ if the current arm segment is the first arm segment of the robotic arm closest to the self-moving cleaning device. i θ is the angle between the first arm segment and the plane where the self-moving cleaning device is located; if the current arm segment is not the first arm segment, θ i =θi+1 -μ i , where μ i This represents the offset angle of the i-th arm segment relative to the (i+1)-th arm segment.

[0248] In one embodiment of this disclosure, optionally, the robotic arm working state determination unit 604 is configured to: determine the weight of the object when the robotic arm performs the object acquisition action based on the working parameters.

[0249] Optionally, in one embodiment of this disclosure, the robotic arm working state determination unit 604 includes:

[0250] The object acquisition weight determination unit determines the object acquisition weight of the at least one joint motor based on the operating parameters.

[0251] The working state determination unit is configured to determine the working state of the at least one joint motor of the robotic arm based on the weight of the object obtained from the at least one joint motor.

[0252] Optionally, in one embodiment of this disclosure, the object weight determination unit includes:

[0253] The fifth execution unit is configured to, for each of the at least one joint motors, determine the ratio of the product of the cross-axis current of the joint motor and the preset calibration coefficient to the lever arm length, as the object weight of the joint motor.

[0254] Optionally, in one embodiment of this disclosure, the object weight determination unit includes:

[0255] The sixth execution unit is configured to determine the object acquisition weight of the at least one joint motor based on the cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, wherein...

[0256]

[0257] W represents the weight of the object acquired by a single joint motor, I q Let be the quadrature-axis current of a single joint motor, r be the lever arm length of the arm segment directly driven by the single joint motor, K be the preset calibration coefficient of the single joint motor, α be the angular acceleration of the arm segment directly driven by the single joint motor during motion, j be the moment of inertia of the joint where the single joint motor is located, and F be the moment of inertia of the joint. f The frictional torque is the force applied during the movement of the arm segment directly driven by a single joint motor.

[0258] Optionally, in one embodiment of this disclosure, the working state determination unit is configured to:

[0259] If the object acquisition weight of any of the at least one joint motors is greater than the safe weight threshold, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state. Alternatively, if the object acquisition weight of any of the at least one joint motors is greater than the safe weight threshold in a specified number of consecutive object acquisition weight detections, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

[0260] Optionally, in one embodiment of this disclosure, the robotic arm control device 600 further includes:

[0261] The sixth execution unit is configured to generate a stop object acquisition command if it is determined that the robotic arm is in an abnormal working state, and control the robotic arm to cancel the object acquisition action based on the stop object acquisition command;

[0262] The overweight alarm unit is configured to generate overweight alarm information.

[0263] Optionally, in one embodiment of this disclosure, the robotic arm control device 600 further includes:

[0264] The target location determination unit is configured to determine the target location of the object to be acquired, which is required for the object acquisition action, before the robotic arm working parameter acquisition unit 602 acquires the working parameters.

[0265] The grasping posture setting unit is configured to set the current posture of the robotic arm to a grasping posture for the target position.

[0266] Optionally, in one embodiment of this disclosure, the robotic arm control device 600 further includes:

[0267] The item identification unit is configured to identify the item to be acquired by an item identification device before the target location determination unit determines the target location, wherein the item identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

[0268] Optionally, in one embodiment of this disclosure, the grasping posture setting unit is configured to:

[0269] Based on the target position, the posture configuration information of the robotic arm when it is in the grasping posture is determined, wherein the posture configuration information includes:

[0270] The angle between the first arm segment of the robotic arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located;

[0271] The offset angle of each arm segment in the robotic arm, excluding the first arm segment, relative to its adjacent first arm segment in the forearm segment; and

[0272] The length of each arm segment in the robotic arm.

[0273] Optionally, in one embodiment of this disclosure, the robotic arm control device 600 further includes:

[0274] The robotic arm initial detection unit is configured to detect whether each joint motor of the robotic arm is in an effective working state in response to a start command for the robotic arm before the robotic arm working parameter acquisition unit 602 acquires the working parameters. If each joint motor of the robotic arm is in an effective working state, the robotic arm working parameter acquisition unit 602 is allowed to acquire the working parameters.

[0275] Optionally, in one embodiment of this disclosure, the robotic arm control device 600 further includes:

[0276] The weighing posture adjustment unit is configured to adjust the robotic arm from the grasping posture to the weighing posture after the grasping posture setting unit sets the current posture of the robotic arm to a grasping posture for the target position.

[0277] Optionally, in one embodiment of this disclosure, the robotic arm operating parameter acquisition unit 602 includes:

[0278] The adjustment process monitoring unit is configured to monitor the working parameters of the robotic arm in real time during the adjustment process of adjusting the robotic arm from the grasping posture to the weighing posture, so as to determine the working state of the robotic arm based on the working parameters.

[0279] The sixth execution unit is configured to interrupt the adjustment process and execute an overload protection strategy if the working state of the robotic arm is an abnormal working state.

[0280] The seventh execution unit is configured to continue the adjustment process if the working state of the robotic arm is the normal working state.

[0281] Optionally, in one embodiment of this disclosure, the robotic arm working state determination unit 604 is configured to:

[0282] If the object acquisition weight of any of the at least one joint motors is greater than its corresponding safe weight threshold, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state. Alternatively, if the object acquisition weight of any of the at least one joint motors is greater than its corresponding safe weight threshold in a specified number of consecutive object acquisition weight detections, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state.

[0283] The robotic arm control device 600 uses the solution described in any one of the above embodiments, and therefore has all the above-mentioned technical effects, which will not be repeated here.

[0284] Figure 7 shows a block diagram of a self-moving cleaning device according to an embodiment of the present disclosure.

[0285] As shown in Figure 7, a self-moving cleaning device 700 according to an embodiment of this disclosure includes at least one memory 702 and a processor 704 communicatively connected to the at least one memory 702; wherein the memory stores instructions executable by the at least one processor 704, the instructions being configured to perform the scheme described in any of the above embodiments. Therefore, this self-moving cleaning device 700 has the same technical effects as any of the above embodiments, and will not be repeated here.

[0286] Additionally, embodiments of this disclosure provide a computer-readable storage medium storing computer-executable instructions configured to perform the following steps:

[0287] The operating parameters of the robotic arm obtained from the mobile cleaning equipment;

[0288] Based on the aforementioned operating parameters, the working state of the robotic arm is determined.

[0289] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0290] The technical solution of this disclosure has been described in detail above with reference to the accompanying drawings. This technical solution determines the current working state of the robotic arm by analyzing its operating parameters. Specifically, it infers whether the robotic arm is in an unsafe working state based on its current operating state, facilitating timely identification and response in real-world scenarios where the robotic arm is carrying an excessively heavy load. This technical solution allows for the timely interruption of the robotic arm's overloaded operation, preventing prolonged overloading, increasing the flexibility and safety of the robotic arm's operation, improving the overall performance of the self-moving cleaning equipment, and enhancing the user experience.

[0291] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0292] It should be understood that although the terms "first," "second," etc., may be used to describe execution units in the embodiments of this disclosure, these execution units should not be limited to these terms. These terms are only used to distinguish execution units from one another. For example, without departing from the scope of the embodiments of this disclosure, a first execution unit may also be referred to as a second execution unit, and similarly, a second execution unit may also be referred to as a first execution unit.

[0293] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0294] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure. The singular forms “a,” “the,” and “the” as used in the embodiments of this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0295] In the several embodiments provided in this disclosure, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0296] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0297] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this disclosure can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0298] The above-described embodiments are only used to illustrate the technical solutions of this disclosure, and are not intended to limit it. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be included within the protection scope of this disclosure.

Claims

1. A robotic arm control method, wherein, include: The operating parameters of the robotic arm obtained from the mobile cleaning equipment; as well as, Based on the aforementioned operating parameters, the working state of the robotic arm is determined.

2. The method according to claim 1, wherein, The operating parameters of the robotic arm obtained from the mobile cleaning equipment include: The working parameters of the robotic arm of the self-moving cleaning device when performing an object acquisition action are obtained, wherein the object acquisition action includes at least one of clamping, grasping, and lifting.

3. The method according to claim 1, wherein, The operating parameters of the robotic arm obtained from the mobile cleaning equipment include: Obtain the working parameters of the robotic arm of the self-moving cleaning device when it is not performing an object acquisition action.

4. The method according to claim 2 or 3, wherein, The operating parameters are acquired in real time.

5. The method according to claim 1, wherein, The operating parameters of the robotic arm obtained from the mobile cleaning equipment include: The cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm are obtained, wherein the preset calibration coefficient is configured to reflect the ratio of cross-axis current to output torque in the at least one joint motor.

6. The method according to claim 5, wherein, The step of obtaining the quadrature-axis current of at least one joint motor of the robotic arm includes: The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to Clark transformation to obtain the quadrature axis current corresponding to the at least one joint motor.

7. The method according to claim 5, wherein, The step of obtaining the lever arm length of at least one joint motor of the robotic arm includes: For each of at least one joint motor of the robotic arm, the lever arm length of the joint motor is determined as follows: Where r represents the lever arm length of the current joint motor, n is the number of arm segments from the last arm segment of the robotic arm to the current arm segment corresponding to the current joint motor, and i represents the arm segment number, i∈[1,n], where the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, and l i θ represents the arm length from the last arm segment to the i-th arm segment in the current arm segment. i This represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

8. The method according to claim 7, wherein, Also includes: If the current arm segment is the first arm segment of the robotic arm closest to the self-moving cleaning device, determine θ. i The angle between the first arm segment and the plane containing the self-moving cleaning device; and, If the current arm segment is not the first arm segment, θ i =θ i+1 -μ i , where μ i This represents the offset angle of the i-th arm segment relative to the (i+1)-th arm segment.

9. The method according to claim 1, wherein, Determining the working state of the robotic arm based on the working parameters includes: Based on the operating parameters, the weight of the object is determined when the robotic arm performs the object acquisition action.

10. The method according to claim 5, wherein, Determining the working state of the robotic arm based on the working parameters includes: Based on the operating parameters, determine the object acquisition weight of the at least one joint motor; and, The working state of the at least one joint motor of the robotic arm is determined based on the weight of the object obtained from the at least one joint motor.

11. The method according to claim 10, wherein, Determining the object acquisition weight of the at least one joint motor based on the operating parameters includes: For each of the at least one joint motor, the ratio of the product of the cross-axis current and the preset calibration coefficient of the joint motor to the lever arm length is determined as the object weight of the joint motor.

12. The method according to claim 10, wherein, Determining the object acquisition weight of the at least one joint motor based on the operating parameters includes: Based on the cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, the object acquisition weight of the at least one joint motor is determined, wherein... W represents the weight of the object acquired by a single joint motor, I q Let be the quadrature-axis current of a single joint motor, r be the lever arm length of the arm segment directly driven by the single joint motor, K be the preset calibration coefficient of the single joint motor, α be the angular acceleration of the arm segment directly driven by the single joint motor during motion, j be the moment of inertia of the joint where the single joint motor is located, and F be the moment of inertia of the joint. f The frictional torque is the force applied during the movement of the arm segment directly driven by a single joint motor.

13. The method according to any one of claims 10 to 12, wherein, The process of obtaining the weight of the object based on the at least one joint motor and determining the operating state of the at least one joint motor of the robotic arm includes: If the object weight acquired by any of the at least one joint motor exceeds its corresponding safe weight threshold, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state. If any one of the at least one joint motors detects an object weight greater than its corresponding safe weight threshold in a specified number of consecutive object weight detections, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

14. The method according to claim 13, wherein, If it is determined that the robotic arm is in an abnormal working state, the following steps are also included: Generate a stop object acquisition command, and based on the stop object acquisition command, control the robotic arm to cancel the object acquisition action; and, Generate an overload alarm message.

15. The method according to claim 2, wherein, Before acquiring the operating parameters of the robotic arm from the mobile cleaning equipment, the method further includes: Determine the target location of the object to be acquired, which is required for the object acquisition action; and, Set the current posture of the robotic arm to a grasping posture for the target position.

16. The method according to claim 15, wherein, Before determining the target location of the item to be acquired for the object acquisition action, the method further includes: The item to be acquired is identified by an item recognition device, wherein the item recognition device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

17. The method according to claim 15, wherein, Setting the current posture of the robotic arm to a grasping posture for the target position includes: Based on the target position, determine the posture configuration information of the robotic arm when it is in the grasping posture, wherein... The attitude configuration information includes: The angle between the first arm segment of the robotic arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located; The offset angle of each arm segment in the robotic arm, excluding the first arm segment, relative to its adjacent first arm segment in the forearm segment; and, The length of each arm segment in the robotic arm.

18. The method according to claim 1, wherein, Before acquiring the operating parameters of the robotic arm from the mobile cleaning equipment, the method further includes: In response to a start command for the robotic arm, it is detected whether each joint motor of the robotic arm is in an effective working state. If each joint motor of the robotic arm is in an effective working state, the step of obtaining the working parameters of the robotic arm from the mobile cleaning equipment is allowed.

19. The method according to claim 15, wherein, After setting the current posture of the robotic arm to a grasping posture for the target position, the method further includes: Adjust the robotic arm from the grasping posture to the weighing posture.

20. The method according to claim 19, wherein, The operating parameters of the robotic arm obtained from the mobile cleaning equipment include: During the adjustment process of the robotic arm from the grasping posture to the weighing posture, the working parameters of the robotic arm are monitored in real time to determine the working state of the robotic arm based on the working parameters. If the robotic arm is in an abnormal operating state, the adjustment process is interrupted, and an overload protection strategy is implemented; and, If the robotic arm is in a normal working state, continue the adjustment process.

21. The method according to claim 20, wherein, Determining the working state of the robotic arm based on the working parameters further includes: If the object weight acquired by any of the at least one joint motor exceeds its corresponding safe weight threshold, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state. If any one of the at least one joint motors detects an object weight greater than its corresponding safe weight threshold in a specified number of consecutive object weight detections, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state.

22. A robotic arm control device, wherein, include: The robotic arm working parameter acquisition unit is configured to acquire the working parameters of the robotic arm from the mobile cleaning equipment. as well as, The robotic arm working state determination unit is configured to determine the working state of the robotic arm based on the working parameters.

23. The apparatus according to claim 22, wherein, The robotic arm operating parameter acquisition unit includes: The first execution unit is configured to acquire working parameters when the robotic arm of the self-moving cleaning device performs an object acquisition action, wherein the object acquisition action includes at least one of clamping, grasping, and lifting.

24. The apparatus according to claim 22, wherein, The robotic arm operating parameter acquisition unit includes: The second execution unit is configured to acquire working parameters of the robotic arm of the self-moving cleaning device when it does not perform an object acquisition action.

25. The apparatus according to claim 23 or 24, wherein, The operating parameters are acquired in real time.

26. The apparatus according to claim 22, wherein, The robotic arm operating parameter acquisition unit includes: The fourth execution unit is configured to acquire at least one of the following: cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is configured to reflect the ratio of cross-axis current to output torque in the at least one joint motor.

27. The apparatus according to claim 26, wherein, The robotic arm operating parameter acquisition unit acquires the quadrature-axis current of at least one joint motor of the robotic arm in the following ways: The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to Clark transformation to obtain the quadrature axis current corresponding to the at least one joint motor.

28. The apparatus according to claim 26, wherein, The robotic arm operating parameter acquisition unit acquires the lever arm length of at least one joint motor of the robotic arm in the following ways: For each of at least one joint motor of the robotic arm, the lever arm length of the joint motor is determined as follows: Where r represents the lever arm length of the current joint motor, n is the number of arm segments from the last arm segment of the robotic arm to the current arm segment corresponding to the current joint motor, and i represents the arm segment number, i∈[1,n], where the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, and l i θ represents the arm length from the last arm segment to the i-th arm segment in the current arm segment. i This represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

29. The apparatus according to claim 28, wherein, Also includes: Angle determination unit is configured to determine θ if the current arm segment is the first arm segment of the robotic arm closest to the self-moving cleaning device. i θ is the angle between the first arm segment and the plane where the self-moving cleaning device is located; if the current arm segment is not the first arm segment, θ i =θ i+1 -μ i , where μ i This represents the offset angle of the i-th arm segment relative to the (i+1)-th arm segment.

30. The apparatus according to claim 22, wherein, The robotic arm working state determination unit is configured to: determine the weight of the object when the robotic arm performs the object acquisition action based on the working parameters.

31. The apparatus according to claim 26, wherein, The robotic arm working state determination unit includes: The object acquisition weight determination unit determines the object acquisition weight of the at least one joint motor based on the operating parameters; and, The working state determination unit is configured to determine the working state of the at least one joint motor of the robotic arm based on the weight of the object obtained from the at least one joint motor.

32. The apparatus according to claim 31, wherein, The object weight determination unit includes: The fifth execution unit is configured to, for each of the at least one joint motors, determine the ratio of the product of the cross-axis current of the joint motor and the preset calibration coefficient to the lever arm length, as the object weight of the joint motor.

33. The apparatus according to claim 31, wherein, The object weight determination unit includes: The sixth execution unit is configured to determine the object acquisition weight of the at least one joint motor based on the cross-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration, and frictional torque of at least one joint motor of the robotic arm, wherein... W represents the weight of the object acquired by a single joint motor, I q Let be the quadrature-axis current of a single joint motor, r be the lever arm length of the arm segment directly driven by the single joint motor, K be the preset calibration coefficient of the single joint motor, α be the angular acceleration of the arm segment directly driven by the single joint motor during motion, j be the moment of inertia of the joint where the single joint motor is located, and F be the moment of inertia of the joint. f The frictional torque is the force applied during the movement of the arm segment directly driven by a single joint motor.

34. The apparatus according to any one of claims 31 to 33, wherein, The working status determination unit is configured as follows: If the object acquisition weight of any of the at least one joint motors is greater than the safe weight threshold, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state. Alternatively, if the object acquisition weight of any of the at least one joint motors is greater than the safe weight threshold in a specified number of consecutive object acquisition weight detections, the robotic arm is determined to be in an abnormal working state; otherwise, the robotic arm is determined to be in a normal working state.

35. The apparatus according to claim 34, wherein, Also includes: The sixth execution unit is configured to, if it is determined that the robotic arm is in an abnormal working state, generate a stop object acquisition command, and based on the stop object acquisition command, control the robotic arm to cancel the object acquisition action; and, The overweight alarm unit is configured to generate overweight alarm information.

36. The apparatus according to claim 35, wherein, Also includes: The target location determination unit is configured to determine the target location of the object to be acquired, which is required for the object acquisition action, before the robotic arm working parameter acquisition unit acquires the working parameters; and The grasping posture setting unit is configured to set the current posture of the robotic arm to a grasping posture for the target position.

37. The apparatus according to claim 36, wherein, Also includes: The item identification unit is configured to identify the item to be acquired by an item identification device before the target location determination unit determines the target location, wherein the item identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

38. The apparatus according to claim 36, wherein, The grasping posture setting unit is configured as follows: Based on the target position, the posture configuration information of the robotic arm when it is in the grasping posture is determined, wherein the posture configuration information includes: The angle between the first arm segment of the robotic arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located; The offset angle of each arm segment in the robotic arm, excluding the first arm segment, relative to its adjacent first arm segment in the forearm segment; and, The length of each arm segment in the robotic arm.

39. The apparatus according to claim 22, wherein, Also includes: The robotic arm initial detection unit is configured to detect whether each joint motor of the robotic arm is in an effective working state in response to a start command for the robotic arm before the robotic arm working parameter acquisition unit acquires the working parameters. If each joint motor of the robotic arm is in an effective working state, the robotic arm working parameter acquisition unit is allowed to acquire the working parameters.

40. The apparatus according to claim 36, wherein, Also includes: The weighing posture adjustment unit is configured to adjust the robotic arm from the grasping posture to the weighing posture after the grasping posture setting unit sets the current posture of the robotic arm to a grasping posture for the target position.

41. The apparatus according to claim 40, wherein, The robotic arm operating parameter acquisition unit includes: The adjustment process monitoring unit is configured to monitor the working parameters of the robotic arm in real time during the adjustment process of changing the robotic arm from the grasping posture to the weighing posture, so as to determine the working state of the robotic arm based on the working parameters; and The sixth execution unit is configured to interrupt the adjustment process and execute an overload protection strategy if the working state of the robotic arm is an abnormal working state. The seventh execution unit is configured to continue the adjustment process if the working state of the robotic arm is the normal working state.

42. The apparatus according to claim 41, wherein, The robotic arm working state determination unit is configured as follows: If the object acquisition weight of any of the at least one joint motors is greater than its corresponding safe weight threshold, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state. Alternatively, if the object acquisition weight of any of the at least one joint motors is greater than its corresponding safe weight threshold in a specified number of consecutive object acquisition weight detections, the robotic arm is determined to be in the abnormal working state; otherwise, the robotic arm is determined to be in the normal working state.

43. A self-propelled cleaning device, wherein, include: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, the instructions being configured to cause the processor to perform the method according to any one of claims 1 to 21.

44. A computer-readable storage medium, wherein, The device stores computer-executable instructions configured to perform the method as described in any one of claims 1 to 21.

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