Handling system and method of controlling the same

Abstract

The present application provides a carrying system and a control method thereof. The system comprises a mobile carrier, a mechanical arm, a lifting mechanism, a first sensor, a second sensor and at least one controller. The controller controls the first movement of the platform of the lifting mechanism according to the target height detected by the first sensor. In response to the first movement, the controller controls the second movement of the platform according to the height difference between the platform and the target position measured by the second sensor. Thus, the accuracy and stability of the carrying system in alignment can be effectively improved.

Description

Technical Field

[0001] This invention relates to an automation technology, and more particularly to a material handling system and its control method. Background Technology

[0002] With the rapid development of industrial automation and intelligent warehousing technologies, material handling systems such as Autonomous Mobile Robots (AMRs) or Automated Guided Vehicles (AGVs) are increasingly widely used in material handling, production line collaboration, and logistics sorting. One of the core tasks of these systems is to accurately move objects from one location to another.

[0003] In many high-precision applications, such as plugging and unplugging servers in data centers, transferring wafer carriers in semiconductor production lines, or stacking goods in automated warehouses, material handling systems not only need to lift objects to the target height, but also require extremely high accuracy and stability in their alignment process. Any tiny error in height can lead to failed placement of objects, damage to the objects themselves or equipment at the target location (such as cabinets or shelves), or even trigger more serious system errors. Summary of the Invention

[0004] This invention relates to a handling system and its control method, which can achieve fast, stable and high-precision high alignment.

[0005] According to an embodiment of the present invention, the handling system includes (but is not limited to) a mobile carrier, a robotic arm, a lifting mechanism, a first sensor, a second sensor, and a controller. The robotic arm is mounted on the mobile carrier and is used to grip an object. The lifting mechanism is mounted on the mobile carrier and has a platform for placing the object. The first sensor is used to detect a target height corresponding to a target position. The second sensor is used to measure the height difference between the platform and the target position. The controller is electrically connected to the aforementioned components and configured to perform: controlling the platform to perform a first movement based on the target height, and responding to the first movement by controlling the platform to perform a second movement based on the height difference.

[0006] According to an embodiment of the present invention, the control method includes (but is not limited to) the following steps: providing a handling system, the handling system including a robotic arm, a lifting mechanism, a first sensor, a second sensor, and a controller. The robotic arm is used to grip an object, and the lifting mechanism has a platform for placing the object. Next, a target height corresponding to a target position is detected by the first sensor. Then, the height difference between the platform and the target position is measured by the second sensor. The controller first controls the platform to perform a first movement based on the target height, and responds to the first movement of the platform, then controls the platform to perform a second movement based on the height difference.

[0007] Based on the above, this embodiment of the invention provides a two-stage control flow of "first movement" and "second movement". Specifically, the system first moves the platform quickly to the vicinity of the target position based on the target height detected by the first sensor (i.e., the first movement, which can be regarded as a coarse adjustment procedure). Subsequently, the remaining minute height difference is directly measured using the second sensor, and a compensatory second movement is performed based on this precise difference value (i.e., a fine adjustment procedure). This "coarse adjustment first, then fine adjustment" control strategy not only ensures the speed of alignment but also significantly improves the final positioning accuracy and stability, thereby effectively avoiding the risk of damage to objects or equipment caused by height differences. Attached Figure Description

[0008] Figure 1 This is a block diagram of a handling system according to an embodiment of the present invention;

[0009] Figure 2 This is a perspective view of a handling system according to an embodiment of the present invention;

[0010] Figure 3 This is a block diagram of a mobile vehicle according to an embodiment of the present invention;

[0011] Figure 4A This is a perspective view of a mobile vehicle according to an embodiment of the present invention;

[0012] Figure 4B This is a top view of a mobile vehicle according to an embodiment of the present invention;

[0013] Figure 4C This is a bottom view of a mobile vehicle according to an embodiment of the present invention;

[0014] Figure 5 This is a block diagram of a robotic arm according to an embodiment of the present invention;

[0015] Figure 6 This is a three-dimensional schematic diagram of a robotic arm according to an embodiment of the present invention;

[0016] Figure 7 A block diagram of a lifting mechanism according to an embodiment of the present invention;

[0017] Figure 8 A perspective view of a lifting mechanism according to an embodiment of the present invention;

[0018] Figure 9 This is a schematic diagram of a handling system according to an embodiment of the present invention in an application scenario;

[0019] Figure 10 This is an operation flowchart of the handling system according to an embodiment of the present invention;

[0020] Figure 11This is a flowchart of a control method according to an embodiment of the present invention. Detailed Implementation

[0021] Reference will now be made in detail to exemplary embodiments of the invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same element references are used in the drawings and description to denote the same or similar parts.

[0022] Figure 1 This is a block diagram of a handling system 100 according to an embodiment of the present invention, and Figure 2 This is a perspective view of a conveying system 100 according to an embodiment of the present invention. Please refer to... Figure 1 and Figure 2 The material handling system 100 can be used in automated warehouses, smart factories or data centers to handle and place objects 50 (such as server hosts, boxes or raw materials).

[0023] The handling system 100 includes (but is not limited to) a mobile carrier 110, a robotic arm 120, a lifting mechanism 130, a first sensor 140, a second sensor 150, and one or more controllers 160.

[0024] Figure 3 This is a block diagram of a mobile vehicle 110 according to an embodiment of the present invention. Figure 4A This is a perspective view of a mobile vehicle 110 according to an embodiment of the present invention. Figure 4B This is a top view schematic diagram of a mobile vehicle 110 according to an embodiment of the present invention, and Figure 4C This is a bottom view of the mobile vehicle 110 according to an embodiment of the present invention. Please refer to... Figure 3 and Figures 4A to 4C The mobile vehicle 110 may be an autonomous mobile robot (AMR), an automated guided vehicle (AGV), or other unmanned vehicles. The mobile vehicle 110 includes (but is not limited to) a main controller 161, a vehicle controller 111, a motor driver 112, a mobility assembly 113, a communication transceiver 114, a collision sensor 115, a neural network processor 116, and a localization and mapping processor 117.

[0025] The main controller 161 may be a central processing unit (CPU), a microcontroller (MCU), or an embedded system. In one embodiment, one or more main controllers 161 are used to perform or lead all or part of the operations of the mobile vehicle 110 or the handling system 100. For example, they are responsible for navigation operations of the mobile vehicle 110, control of drivers, sensor processing, and control decisions.

[0026] Vehicle controller 111 is electrically connected to main controller 161. Vehicle controller 111 may be a central processing unit (CPU), microcontroller (MCU), or embedded system. In one embodiment, vehicle controller 111 is used to receive and parse navigation and mission commands from upper-level main controller 161, and coordinate the internal operations of mobile vehicle 110, such as path tracking, motor drive, speed control, and status monitoring.

[0027] Motor driver 112 is electrically connected to vehicle controller 111. Motor driver 112 may be an electronic power circuit. In one embodiment, motor driver 112 receives a power control signal from vehicle controller 111 and converts it into current to drive a motor in mobility assembly 113, thereby controlling the speed and / or direction of the wheels of mobility assembly 113.

[0028] The mobility assembly 113 can be a plurality of wheels or track structures. For example... Figure 4A and Figure 4C As shown, the mobility assembly 113 can be specifically implemented as four sets of Mecanum wheels or omnidirectional wheels. This design enables the mobility vehicle 110 to move in all directions, including forward, backward, lateral and rotation, thereby exhibiting excellent mobility in narrow spaces.

[0029] The communication transceiver 114 is electrically connected to the main controller 161 and the vehicle controller 111. The communication transceiver 114 may be a transceiver circuit or a wired transmission interface (e.g., USB or UART) that conforms to wireless communication protocols such as Wi-Fi, Bluetooth, 5G or Zigbee, and is used to establish a stable data network with other components or other external systems.

[0030] The collision sensor 115 may be an ultrasonic sensor, an infrared sensor, an image sensor, or a physical collision bar. In one embodiment, the collision sensor 115 is used to detect surrounding obstacles so that the main controller 161 can plan a route to avoid the obstacles.

[0031] The neural network processor 116 is electrically connected to the collision sensor 115 and the main controller 161. The neural network processor 116 can be a dedicated hardware accelerator such as a graphics processing unit (GPU), a tensor processing unit (TPU), or a field-programmable gate array (FPGA). The neural network processor 116 can execute algorithms such as advanced path planning based on artificial intelligence, dynamic obstacle avoidance based on sensing data from the collision sensor 115, or visual servoing. For example, it can perform precise positioning using markers (QR codes or augmented reality markers), short-range positioning assisted by infrared signals, and improve positioning accuracy by detecting changes in ground magnetic strips or magnetic fields using magnetic sensors.

[0032] The localization and mapping (SLAM) processor 117 is electrically connected to the main controller 161 and the first sensor 140. The localization and mapping processor 117 may be a dedicated digital signal processor (DSP), graphics processing unit (GPU), field-programmable gate array (FPGA), or a software module running on a high-performance CPU. In one embodiment, the localization and mapping processor 117 is used to synchronously calculate the attitude and position of the mobile vehicle 110 based on data from the first sensor 140 (e.g., LiDAR, image sensor, motion sensor such as an inertial measurement unit (IMU) or a combination thereof, as detailed later), and to construct a map of the surrounding environment.

[0033] In some applications, the mobile vehicle 110 may also include an emergency stop button for stopping the operation of the transport system 100 or other devices, and / or an over-the-air update module for remotely updating navigation algorithms and / or sensor calibration.

[0034] Figure 5 This is a block diagram of a robotic arm 120 according to an embodiment of the present invention, and Figure 6 This is a perspective view of a robotic arm 120 according to an embodiment of the present invention. Please refer to... Figure 5 and Figure 6 The robotic arm 120 includes (but is not limited to) a main controller 161 (which may be shared with the mobile carrier 110 or there may be multiple main controllers 161, and multiple main controllers 161 transmit or receive data between each other via a communication transceiver 114), an arm controller 121, a servo motor 122, a joint encoder 123, a torque sensor 124, a neural network processor 125, a gripper 126, and a gripper controller 127.

[0035] The main controller 161 can be referred to the above description, and will not be repeated here.

[0036] The arm controller 121 is electrically connected to the main controller 161. The arm controller 121 can be a dedicated motion controller or a microcontroller. In one embodiment, the arm controller 121 is used to receive and parse motion trajectory instructions from the upper main controller 161, and convert them into target angles, velocities, and accelerations required by each joint and control instructions for the gripper controller 127 through inverse kinematics calculations.

[0037] Servo motor 122 is electrically connected to arm controller 121. Servo motor 122 may include a motor body, a driver, and a feedback sensor. In one embodiment, servo motor 122 drives multiple joints (3 to 6 axes) of robotic arm 120, enabling it to move flexibly in three-dimensional space. For example, multi-directional movement: grasping, rotating, lifting, or positioning. In some applications, servo motor 122 may be paired with a speed reducer to improve torque accuracy.

[0038] The joint encoder 123 is electrically connected to the arm controller 121. The joint encoder 123 may be located at each joint. In one embodiment, the joint encoder 123 is used to provide real-time feedback on the actual rotation angle of each joint.

[0039] The torque sensor 124 can be a six-axis force / torque sensor or pressure sensor based on a strain gauge. In some applications, the torque sensor 124 can be mounted on the wrist of the robotic arm 120 or on the gripper 126 to detect changes in force and torque generated upon contact with the external environment, enabling flexible gripping or collision detection. In some embodiments, the robotic arm 120 can use image sensors (e.g., cameras or laser rangefinders) to assist in identifying target positions, and / or magnetic sensors to detect magnetic markers and improve docking accuracy.

[0040] The neural network processor 125 is electrically connected to the main controller 161 and the torque sensor 124. The neural network processor 125 may be a graphics processing unit (GPU) or an application-specific integrated circuit (ASIC) to execute deep learning-based visual servoing algorithms, such as real-time correction of the end effector position of the robotic arm 120 to align with a target object using camera images. In some embodiments, the neural network processor 125 may use sensing data from an image sensor (e.g., a camera or laser rangefinder) to assist in identifying the target location.

[0041] In one embodiment, such as Figure 6 As shown, a gripper 126 is disposed at the end of the robotic arm 120 and is used to grip the object 50, and its form can be a two-finger, three-finger, or adaptive gripper. In one embodiment, the gripper 126 is further provided with a pressure sensor (not shown) and is used to detect the pressure value at the end of the robotic arm 120 (corresponding to the gripper 126).

[0042] The gripper controller 127 is electrically connected to the arm controller 121 and the gripper 126. The gripper controller 127 may be a dedicated microcontroller, an integrated motor driver, or software or firmware running on the arm controller 121. In one embodiment, the gripper controller 127 is used to control the opening and closing stroke and gripping force of the gripper 126 according to instructions.

[0043] In some embodiments, the robotic arm 120 may be secured to the mobile carrier 110 by fasteners (e.g., mechanical latches) to improve operational stability.

[0044] Figure 7 This is a block diagram of the lifting mechanism 130 according to an embodiment of the present invention, and Figure 8 This is a perspective view of the lifting mechanism 130 according to an embodiment of the present invention. Please refer to... Figure 7 and Figure 8 The lifting mechanism 130 includes (but is not limited to) a main controller 161 (which may be shared with the mobile vehicle 110 or there may be multiple main controllers 161, and multiple main controllers 161 transmit or receive data through a communication transceiver 114), a lifting controller 131, an actuator 132, a displacement sensor 133, an actuator controller 134, a collision sensor 135, and a platform 136.

[0045] The main controller 161 can be referred to the above description, and will not be repeated here.

[0046] The lifting controller 131 is electrically connected to the main controller 161. The lifting controller 131 can be a dedicated programmable logic controller (PLC) or a microcontroller (MCU). In one embodiment, the lifting controller 131 is used to receive adjustment instructions from the upper-level main controller 161 and execute control algorithms. In another embodiment, the lifting controller 131 is used to receive control quantity indications or control signals from the actuator controller 134.

[0047] Actuator 132 can be a hydraulic cylinder, a pneumatic cylinder, or an electric actuator driven by a ball screw. For example, a scissor-link structure, in an X-shape, can raise or lower platform 136 by extending or retracting. The dual hydraulic cylinder includes a fixed end and a piston rod end. The fixed end connects to the lower scissor link or base frame to ensure stable support force when the hydraulic cylinder retracts; it is typically located near the center of the lower side of the scissor link to provide an optimal lever arm ratio for more efficient lifting and lowering of platform 136. The piston rod end connects to the central pivot point of the upper scissor link and moves with the extension and retraction of the hydraulic cylinder, thereby actuating the scissor mechanism to complete the lifting action. Alternatively, dual electric screws offer a lightweight design and provide more precise height adjustment.

[0048] The displacement sensor 133 may be an optical scale, a position encoder, or a linear potentiometer mounted on the mechanism. In one embodiment, the displacement sensor 133 is used to measure and report the current vertical height of the platform 136 in real time.

[0049] Actuator controller 134 is electrically connected to lifting controller 131 and displacement sensor 133. In one embodiment, actuator controller 134 converts logic control signals from lifting controller 131 into power signals sufficient to drive actuator 132. For example, in an embodiment where actuator 132 is a hydraulic cylinder, actuator controller 134 may be an electronically controlled proportional valve or servo valve, precisely regulating the flow and direction of hydraulic oil. In one embodiment, actuator controller 134 integrates a proportional-integral-derivative (PID) control algorithm and acts as a PID controller to calculate precise control quantities based on height feedback from displacement sensor 133.

[0050] The collision sensor 135 may be an ultrasonic sensor, an infrared sensor, or a contact sensor (including a pressure sensor strip). In one embodiment, the collision sensor 135 is used to detect obstacles above or around the device, so that the main controller 161 or the lifting controller 131 can adjust the lifting height to avoid the obstacles.

[0051] The collision sensor 135 may be a processing unit that processes signals from a pressure sensor bar or a proximity sensor to immediately interrupt the lifting action for safety when an unexpected physical contact is detected during the lifting process. The platform 136 is a planar structure that carries the object 50.

[0052] Platform 136 is a planar structure that supports object 50.

[0053] In one embodiment, the lifting mechanism 130 further includes a torque sensor (not shown). The torque sensor is electrically connected to the lifting controller 131 and / or the main controller 161. The torque sensor may be a strain gauge-based six-axis force / torque sensor or a pressure sensor. In one embodiment, the torque sensor is used to detect the weight of the object 50 placed on the platform 136.

[0054] In one embodiment, such as Figure 2 As shown, both the robotic arm 120 and the lifting mechanism 130 are mounted on the body of the mobile carrier 110. The mobile carrier 110 is responsible for autonomous movement within the work area. The lifting mechanism 130 has the following features: Figure 8 The platform shown is used to support the object 50 and is responsible for vertical height adjustment. The robotic arm 120 is used to grip the object 50 and transfer the object 50 between the target position and the platform of the lifting mechanism 130.

[0055] Please refer to Figure 1 The first sensor 140 is electrically connected to the controller 160. For example... Figure 3As shown, the first sensor 140 is electrically connected to the main controller 161. The first sensor 140 may be a LiDAR, structured light, or a Time-of-Flight (ToF) depth camera. The first sensor 140 may be mounted on the mobile vehicle 110 or other devices. In one embodiment, the first sensor 140 is used to perform environmental scanning and positioning, and to initially detect the three-dimensional spatial coordinates and / or distance values ​​of the target position (corresponding to the position of object 50).

[0056] The second sensor 150 is electrically connected to the controller 160. The second sensor 150 may be a high-precision (e.g., error less than permissible) laser triangulation sensor or confocal displacement sensor. In some applications, the second sensor 150 has higher resolution and update rate than the first sensor 140, and is specifically designed, for example, to measure more accurate relative height differences between the near-field platform 136 and the target location (e.g., the location of object 50 or its adjacent reference).

[0057] The controller 160 may be a central processing unit (CPU), a graphics processing unit (GPU), or other programmable general-purpose or special-purpose microprocessors, digital signal processors (DSPs), programmable controllers, field-programmable gate arrays (FPGAs), or application-specific integrated circuits (ASICs). The controller 160 is electrically connected to the mobile carrier 110, the robotic arm 120, the lifting mechanism 130, the first sensor 140, and the second sensor 150. In one embodiment, the controller 160 coordinates the movement of the mobile carrier 110, the height adjustment of the lifting mechanism 130, and the gripping and placing actions of the robotic arm 120 to complete automated handling tasks.

[0058] One or more controllers 160 may include Figure 3 Main controller 161, vehicle controller 111, neural network processor 116, localization and mapping processor 117 Figure 5 Main controller 161, arm controller 121, neural network processor 125, gripper controller 127 Figure 7 The main controller 161, the lifting controller 131, and / or the actuator controller 134.

[0059] Figure 9 This is a schematic diagram of the handling system 100 according to an embodiment of the present invention in an application scenario. Please refer to... Figure 9In this application scenario, multiple server racks 901 are provided. Each rack 901 provides multiple slots 902 for placing the server host 903. In the data center application scenario, the task of the handling system 100 is to accurately insert the server host 903 (i.e., object 50) into the corresponding slot 902 of the rack 901 or to remove the server host 903 from the slot 902.

[0060] However, Figure 9 The application scenarios shown are merely illustrative examples, and users can modify them according to their actual needs. For example, the application scenario could be set in a logistics factory or a manufacturing plant, and is not limited to these settings.

[0061] To facilitate understanding of the operation flow of the embodiments of this case, numerous embodiments will be used below to illustrate the operation flow of the embodiments of this case. In the following text, [the text will be accompanied by...]. Figures 1 to 8 The components or modules in this document illustrate the method of the embodiments of this case.

[0062] Figure 10 This is an operation flowchart of the handling system 100 according to an embodiment of the present invention. Please refer to... Figure 10 This reveals the complete operational sequence from lifting alignment to end-point alignment. In step S1010, the lifting mechanism 130 is activated. This step corresponds to the coarse adjustment procedure for height adjustment. The controller 160 receives multiple input information, such as the height of the target slot 902, the current height of the lifting mechanism 130, and the load weight information on the platform 136. Based on this input information, the controller 160 calculates a rough target height using a lifting control algorithm (e.g., PID control) and performs load compensation, and drives the platform 136 to move rapidly to near the target height (i.e., the first movement of the platform 136).

[0063] More specifically, the input information is:

[0064] The height corresponding to the target position as measured by the first sensor 140 (e.g., a red-green-blue depth camera or a laser rangefinder). Figure 9 The height of slot 902 or server host 903 (i.e., object 50);

[0065] The weight value measured by torque sensor 124 can be used to measure the weight value of object 50 if object 50 is placed on platform 136.

[0066] The height of platform 136 is reported in real time by displacement sensor 133.

[0067] In one embodiment, controller 160 determines the target height based on measurements from first sensor 140 and the weight of object 50. The target height corresponds to a target position (corresponding to the position of object 50). When a load (e.g., object 50) is applied to platform 136, the height of platform 136 may decrease. Therefore, the estimation of the target height needs to compensate for this decrease in height caused by the load.

[0068] In one embodiment, controller 160 generates a first control command for moving platform 136 based on the difference between the height of platform 136 and the target height (for use by lift controller 131 or actuator 132 to move platform 136).

[0069] For example, the lifting control algorithm is as follows:

[0070] …(1)

[0071] …(2)

[0072] …(3)

[0073] For the target height, This is based on the difference between the height of platform 136 and the target height. This is a load compensation function used to estimate the amount of sinking of platform 136 due to its weight. For example, assuming platform 136 rises to a target height of 100 cm with a load of 50 kg (e.g., the weight of object 50): platform 136 sinks 2 mm due to structural elasticity (i.e., the height decreases to 998.3 mm). Figure 9 For example, in an application scenario where server host 903 is moved from platform 136 to rack 901, server host 903 needs to be pushed into slot 902. If platform 136 is unloaded, platform 136 will rise to approximately 1000.3 mm to align with the target position. Figure 9 For example, in an application scenario where server host 903 is moved from rack 901 to platform 136, server host 903 needs to be pulled out of slot 902. Therefore, if the weight value If the value is zero, then the height detected by the first sensor 140 is zero. It can be directly used as the target height corresponding to the target location.

[0074] Proportional (P) control item Based on the current gap size, a basic correction amount is generated. It offers a fast response; the larger the gap, the stronger the output, and the faster the reaction speed. (Coefficient) The response intensity corresponding to this control item.

[0075] Integral (I) control item This involves generating a correction factor to eliminate residual discrepancies based on the accumulation of past discrepancies. This eliminates steady-state errors and prevents long-term deviations. (Coefficient) The response intensity corresponding to this control item.

[0076] Differential (D) control term Based on the rate of change of the gap, a predictive correction is generated to suppress oscillations and prevent overshoot, thereby improving stability. (Coefficient) The response intensity corresponding to this control item.

[0077] Output information:

[0078] The output of function (1) is the target height. That is, the (rough) target height for the first movement of platform 136.

[0079] The output of function (3) is the control quantity corresponding to the control command for the first movement of the control platform 136. This control quantity is based on proportional-integral-derivative (PID) control. That is, the controller 160 can use proportional-integral-derivative control to determine the control quantity corresponding to the control command. For example, driving the motor to rotate a certain number of revolutions with a specific voltage and current, or opening the electronically controlled valve by 20%.

[0080] In step S1020, a fine-tuning of the height is performed. After the coarse adjustment (i.e., the first movement based on the target height) is completed, the controller 160 receives an instantaneous feedback value from a higher-precision sensor (e.g., the second sensor 150). This feedback value directly reflects the slight height difference (hereinafter referred to as the height difference) between the platform 136 and the target slot 902. The controller 160 performs a fine-tuning based on this height difference using another lifting control algorithm (e.g., PID control) to ensure that the position of the platform 136 after the second movement is precisely aligned with the target position. In other words, the second movement of the platform 136 is a height fine-tuning response to its first movement. In some application scenarios, the lifting range of the first movement may be greater than that of the second movement.

[0081] More specifically, the input information is:

[0082] The target height output in step S1010;

[0083] The position of platform 136 relative to the target position (e.g., measured by the second sensor 150) is as follows: Figure 9 The height difference between the slot 902 and the position of the slot 902.

[0084] In one embodiment, controller 160 may generate control commands for a second movement based on the height difference (to be used by lift controller 131 or actuator 132 to move platform 136).

[0085] For example, the lifting control algorithm is as follows:

[0086] …(4)

[0087]

[0088] …(5)

[0089] This is the final height of the second movement. The height difference between the platform 136 and the target position as measured by the second sensor 150.

[0090] Proportional (P) control item Based on the current height difference, a basic correction amount is generated. It features a fast response; the larger the height difference, the stronger the output and the faster the reaction speed. (Coefficient) The response intensity corresponding to this control item.

[0091] Integral (I) control item Based on the accumulation of past height differences, a correction amount is generated to eliminate residual height differences. This eliminates steady-state errors and avoids long-term deviations. (Coefficient) The response intensity corresponding to this control item.

[0092] Differential (D) control term Based on the rate of change of the height difference, a predictive correction is generated to suppress oscillations and prevent overshoot, thereby improving stability. (Coefficient) The response intensity corresponding to this control item.

[0093] Output information:

[0094] The output of function (4) is the final height. This refers to the (fine) final height used for the second movement of platform 136 to achieve precise docking.

[0095] The output of function (5) is the control quantity corresponding to the control command for the second movement of the control platform 136. This control quantity is based on proportional-integral-derivative (PID) control. That is, the controller 160 can determine the control quantity corresponding to the control command using PID control. For example, driving the motor to rotate a certain number of revolutions with a specific voltage and current, or opening the electronically controlled valve by 5%.

[0096] For example, if the controller 160 detects that the platform 136 is 0.3 mm higher than the target position, it will lower the platform 136 by 0.3 mm via a control command. Or, for example, if the controller 160 detects that the platform 136 is 1.7 mm lower than the target position, it will raise the platform 136 by 1.7 mm via a control command.

[0097] After the platform 136 is precisely aligned (i.e., the second movement) is completed, in step S1030, the robotic arm 120 moves to the side of the lifting mechanism 130. The controller 160 can perform path planning using algorithms such as inverse kinematics based on the final position of the platform 136 of the lifting mechanism 130 and the current position of the robotic arm 120, and use obstacle avoidance sensors to monitor the surrounding environment to ensure that the robotic arm 120 moves safely to the position where it is ready to grasp the object 50.

[0098] More specifically, the input information is:

[0099] The location of platform 136 determined by localization and mapping processor 117 (e.g., based on Simultaneous Localization and Mapping (SLAM)). The final height of platform 136 determined in step S1020 .

[0100] The current angle of each joint is sensed in real time by the joint encoder 123.

[0101] Data detected by collision sensor 115 and / or collision sensor 135 and used for environmental obstacle avoidance.

[0102] : Motion planning parameter set. For maximum speed, For maximum acceleration, Joint restrictions.

[0103] In one embodiment, in response to a second movement of platform 136 (i.e., after a minor height adjustment of platform 136), controller 160 can control a third movement of robotic arm 120. The endpoint of this third movement corresponds to the endpoint of the second movement of platform 136. For example, the third movement is to move robotic arm 120 next to platform 136.

[0104] For example, the path planning algorithm is:

[0105] ...(6)

[0106] ...(7)

[0107] Tell robotic arm 120 to move to the position next to platform 136. And prepare to grab the height at the final height. Object 50. The current joint angles of the robotic arm 120 are determined using forward kinematics functions. Converted to the Cartesian spatial position of its clamp end. This serves as the starting point (i.e., the initial position) for path planning. The target position of the robotic arm 120 is then set. Move it to position 136 on the lifting platform. And prepare for the final grab height of object 50. Perform the assignment.

[0108] ...(8)

[0109] The Path Plan algorithm is invoked, with the initial and target positions as the main inputs, and the environment map is taken into account. And the limitations of the robotic arm 120 Output a collision-free path from the starting point to the target point. .

[0110] The current joint angle vector of the robotic arm 120;

[0111] The initial position of robotic arm 120;

[0112] Target position of robotic arm 120;

[0113] Position 136 of the lifting platform and the final object grabbing height 50;

[0114] Environmental information / map;

[0115] Limitations of robotic arms.

[0116]

[0117] : Main input variables (initial position and target position of robotic arm 120);

[0118] : Environmental parameters or conditions (boundaries, maps, restrictions).

[0119] like If no feasible solution is found (i.e. obstacle avoidance planning fails), the current movement command is paused, and a "path blocked" error code is reported or a waiting state is entered.

[0120] …(9).

[0121] Using the inverse kinematics function Inverse_Kinematics, the target's Cartesian space position is determined. Convert the target joint angle required for the robotic arm 120 to perform the movement. This step involves converting spatial coordinate instructions, which are understood by humans or systems, into angle instructions that machines can execute.

[0122] Output information:

[0123] Output of function (9) This is the motion trajectory for the control command used for the third movement. This control command for the third movement can be transmitted to the arm controller 121, causing the arm controller 121 to drive the corresponding joint to move or rotate along a safe and smooth trajectory.

[0124] In step S1040, the gripper 126 aligns with the object 50. This step may include: using a vision sensor (e.g., a red-green-blue-depth (RGB-D) camera) and a torque sensor 124 to precisely align the gripper 126 of the robotic arm 120 with the object 50 (e.g., ...). Figure 9 The capture location of the server host (903).

[0125] More specifically, the input information is:

[0126] The position of object 50 as identified by the visual sensor.

[0127] : The geometric offset vector (hereinafter referred to as offset) estimated by the image analysis of the neural network processor 125.

[0128] : End pressure feedback detected by torque sensor 124.

[0129] : System preset security parameters.

[0130] In one embodiment, the controller 160 may correct the offset of the gripper 126 of the robotic arm 120.

[0131] For example, the alignment algorithm:

[0132] …(10)

[0133] …(11)

[0134] This refers to the gripping position of fixture 126. In other words, the offset can be directly added to the position of object 50 obtained from image recognition to compensate for the deviation in image recognition.

[0135] Output information:

[0136] The gripping position of clamp 126 is achieved by synchronizing alignment through visual and force feedback.

[0137] In step S1050, the clamp 126 grips the object 50. The controller 160 determines the optimal clamping force based on a preset clamping pressure setting or based on the weight of the object 50 and feedback from the pressure sensor on the clamp 126, and executes the clamping action through the clamp controller 127.

[0138] More specifically, the output information is:

[0139] : The gripping position of clamp 126.

[0140] : The load weight measured by the torque sensor (i.e., the weight of the load on platform 136).

[0141] The pressure value is reported instantly by the pressure sensor at the end.

[0142] In one embodiment, controller 160 may determine control commands (e.g., indicating response intensity) for clamp 126 based on the weight value of the load on platform 136 and the pressure value at the end.

[0143] For example, the grasping control algorithm is:

[0144] …(12)

[0145] in, : This represents the target clamping pressure or target clamping force. The clamp 126 needs to apply the expected pressure or force to the object 50 to ensure that the object 50 will not slip during movement or be damaged.

[0146] in, For the control mapping function designed based on experience, models can be built using linear, piecewise (lightweight low pressure / medium pressure / heavy pressure), lookup table, or machine learning methods.

[0147] It can be embedded with a safety factor α for conservative clamping, for example: ,

[0148] …(13)

[0149] in, This is a proportional gain function specific to fixture 126, used to determine the response intensity. It can be a constant, a lookup table, or an adaptive gain.

[0150] The output information is:

[0151] The control commands for the clamp are used to stabilize the grip and achieve a successful grasp.

[0152] In step S1060, the gripper 126 removes the object 50. The controller 160 plans the motion trajectory of the robotic arm's joints using a smooth motion planning algorithm. Thus, Figure 9 For example, the server host 903 can be smoothly removed from the rack 901 and placed on the platform 136, or it can be picked up from the platform 136 and installed into the slot 902 of the rack 901.

[0153] More specifically, the input information is:

[0154] Place coordinates, and can be or

[0155] When step S105θ completes the gripping, the joint encoder 123 reports the current angle of the joint, which is used to represent the immediate state of the end effector.

[0156] : Motion planning parameter set.

[0157] Force feedback signal (e.g., pressure value) estimated by joint torque or pressure sensor at the end.

[0158] : Safe handling force limit value in handling tasks.

[0159] The motion control algorithm is as follows:

[0160] …(14)

[0161] …(15)

[0162] in, The smooth motion planning function is used to make the movement of the robotic arm 120 smoother and less oscillating without violating acceleration / velocity limits. Equivalent implementations exist in robot-related development platforms or algorithm simulation software, with names such as trajectory planner, jtraj, servoj, and motion profile.

[0163] …(16)

[0164] The output information is:

[0165] : Used for safe and smooth movement commands for robotic arms, enabling objects to be successfully docked or placed onto the platform.

[0166] Figure 11 This is a flowchart of a control method according to an embodiment of the present invention. Please refer to... Figure 11 In step S1110, the aforementioned handling system 100 is provided. As described above, the handling system 100 includes a robotic arm 120, a lifting mechanism 130, a first sensor 140, a second sensor 150, and at least one controller 160. The robotic arm 120 is used to grip the object 50, and the lifting mechanism 130 has a platform 136 for placing the object 50.

[0167] In step S1120, the target position is detected by the first sensor 140 (e.g., Figure 9 The target height corresponding to slot 902.

[0168] In step S1130, the controller 160 controls the platform 136 of the lifting mechanism 130 to perform a first movement according to the target height. This step achieves... Figure 10 The coarse adjustment function in step S1010.

[0169] In step S1140, the height difference between the platform 136 and the target position is measured by the second sensor 150.

[0170] In step S1150, in response to the first movement of platform 136, controller 160 controls platform 136 to perform a second movement based on the height difference. This step thus achieves... Figure 10 Fine-tuning function in step S1020.

[0171] Figure 11 For detailed instructions on each step, please refer to [link / reference]. Figure 10 The explanation will not be repeated here.

[0172] In summary, the material handling system and control method of this invention divide the platform height adjustment process into a coarse adjustment procedure called "first movement" and a fine adjustment procedure called "second movement." The system first uses a first sensor for a rough and rapid initial alignment, and then uses a high-precision second sensor for precise compensation of the height difference after the first movement. This "coarse adjustment first, then fine adjustment" strategy, combined with PID control and load compensation mechanisms, not only significantly improves the final accuracy and stability of platform alignment but also considers operational efficiency, effectively solving the overshoot, oscillation, or steady-state discrepancy problems that may occur in a single positioning operation in existing technologies. Therefore, this invention provides a more reliable, accurate, and efficient automated material handling solution, particularly suitable for precision operation scenarios with stringent requirements for height alignment.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention 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 or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A handling system, characterized in that, include: Mobile vehicles; A robotic arm is mounted on the mobile carrier and is used to grip objects; A lifting mechanism is provided on the mobile vehicle and has a platform for placing the object; A first sensor is used to detect the target height corresponding to the target position, wherein the target position corresponds to the position of the object; The second sensor is used to measure the height difference between the platform and the target position; At least one controller is electrically connected to the mobile vehicle, the robotic arm, the first sensor, the second sensor, and the lifting mechanism, and is configured to: The platform's first movement is controlled according to the target height; and In response to the first movement of the platform, a second movement of the platform is controlled based on the height difference.

2. The conveying system according to claim 1, wherein the lifting mechanism further comprises: A displacement sensor, electrically connected to the at least one controller, is used to detect the height of the platform, wherein the at least one controller is further configured to: Control commands for the first movement are generated based on the difference between the height of the platform and the target height.

3. The conveying system according to claim 2, wherein the lifting mechanism further comprises: A torque sensor, electrically connected to the at least one controller, is used to detect the weight of the object, wherein the at least one controller is further configured to: The target height is determined based on the measurement value from the first sensor and the weight value.

4. The handling system of claim 1, wherein the at least one controller is further configured to: Control commands for the second movement are generated based on the height difference.

5. The handling system according to claim 2 or 4, wherein the control quantity corresponding to the control command is based on proportional-integral-derivative control.

6. The handling system of claim 1, wherein the at least one controller is further configured to: In response to the second movement of the platform, the robotic arm is controlled to make a third movement, wherein the endpoint of the third movement corresponds to the endpoint of the platform in the second movement.

7. The handling system of claim 6, wherein the at least one controller is further configured to: Correct the offset of the gripper of the robotic arm.

8. The conveying system according to claim 6, wherein the lifting mechanism further comprises: A torque sensor, electrically connected to the at least one controller, is used to detect the weight of the object, wherein the weight is used to determine control commands for the gripper of the robotic arm.

9. The handling system according to claim 8, wherein the robotic arm further comprises: A pressure sensor, disposed in the gripper, electrically connected to the at least one controller, and used to detect the pressure value at the end of the robotic arm, wherein the at least one controller is further configured to: The control commands for the clamp are determined based on the weight value and the pressure value.

10. A control method, comprising: A handling system is provided, wherein the handling system includes a robotic arm, a lifting mechanism, a first sensor, a second sensor, and at least one controller, the robotic arm being used to grip an object, and the lifting mechanism having a platform for placing the object; The target height corresponding to the target position is detected by the first sensor, wherein the target position corresponds to the position of the object; The first movement of the platform is controlled by at least one controller based on the target height; The height difference between the platform and the target position is measured using the second sensor; as well as In response to the first movement of the platform, a second movement of the platform is controlled by at least one controller based on the height difference.

11. The control method according to claim 10, wherein the lifting mechanism further includes a displacement sensor, and the control method further includes: The height of the platform is detected by the displacement sensor; as well as The at least one controller generates control commands for the first movement based on the difference between the height of the platform and the target height.

12. The control method according to claim 11, wherein the lifting mechanism further includes a torque sensor, and the control method further includes: The weight of the object is detected by the torque sensor; as well as The target height is determined by the at least one controller based on the measurement value of the first sensor and the weight value.

13. The control method of claim 11, wherein the step of generating control commands for the first movement comprises: The control quantity corresponding to the control command is determined by the at least one controller based on proportional-integral-derivative control.

14. The control method of claim 10, wherein the at least one controller is further configured to: The at least one controller generates control commands for the second movement based on the height difference.

15. The control method of claim 14, wherein the step of generating control commands for the first movement comprises: The control quantity corresponding to the control command is determined by the at least one controller based on proportional-integral-derivative control.

16. The control method according to claim 10, further comprising: In response to the second movement of the platform, the robotic arm is controlled by the at least one controller to make a third movement, wherein the endpoint of the third movement corresponds to the endpoint of the platform in the second movement.

17. The control method according to claim 16, further comprising: The at least one controller corrects the offset of the gripper of the robotic arm.

18. The control method according to claim 16, wherein the lifting mechanism further includes a torque sensor, the robotic arm further includes a pressure sensor, and the control method further includes: The weight of the object is detected by the torque sensor, and the weight is used to determine the control commands for the gripper of the robotic arm.

19. The control method of claim 18, wherein the robotic arm further includes a pressure sensor, and the control method further includes: The pressure value at the end of the robotic arm is detected by the pressure sensor; as well as The at least one controller determines the control command for the clamp based on the weight value and the pressure value.

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