Intelligent trolley and method for template hoisting

Abstract

The application discloses an intelligent trolley for template hoisting, which comprises an AGV trolley base, a central box body, a three-dimensional mechanical arm and an intelligent gripper which are connected in sequence; the AGV trolley base is provided with four Mecanum wheels which can move in all directions; the central box body is used for integrated processing of control information; the three-dimensional mechanical arm is designed with four degrees of freedom and is used for driving the intelligent gripper to move with multiple degrees of freedom; the intelligent gripper is designed with a variable diameter and comprises a first double-degree-of-freedom base, a hydraulic rod arm, a second double-degree-of-freedom base, a hook claw, a hook claw lock and a sensor integrated module; and the application further provides a method for template hoisting. The intelligent trolley has a physical swing damping function, can inhibit swing in the template hoisting process, realizes stable grabbing and accurate hoisting of the template, and can adapt to diversified template hoisting requirements; the intelligent trolley is highly automatically controlled, can reduce manual labor, improves the safety of construction, reduces the labor cost, and improves the construction efficiency.

Description

Technical Field

[0001] This invention relates to the field of formwork hoisting technology, and in particular to an intelligent trolley and method for formwork hoisting. Background Technology

[0002] Precast concrete formwork, or formwork, is a type of pre-formed concrete or reinforced concrete template installed on the surface of a structure and left there after pouring concrete. It is widely used in water conservancy projects, building construction, and other fields. In current formwork construction, formwork hoisting typically relies on cranes or manual operation. Manual labor involves frequently engaging the hooks to engage the formwork's lifting rings and assisting in replacing large steel beams used for hoisting the formwork, resulting in low efficiency, poor safety, and demanding site requirements. Especially in complex environments, formwork hoisting is prone to swaying, affecting positioning accuracy, and traditional equipment struggles to achieve adaptive control. Given current cable well designs, excessively large excavation areas can impede normal vehicle traffic. Therefore, there is an urgent need for automated hoisting equipment that does not require changing the grab head for different formwork types, adapts to confined working environments, and possesses intelligent recognition and anti-sway capabilities. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent trolley and method for template hoisting, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent trolley for template hoisting, comprising an AGV trolley base, a central housing, a three-dimensional robotic arm, and an intelligent gripper connected in sequence;

[0005] The AGV trolley base is equipped with four Mecanum wheels that can move in all directions;

[0006] The central enclosure is used to integrate and process control information;

[0007] The three-dimensional robotic arm adopts a four-degree-of-freedom design to drive the intelligent gripper to perform multi-degree-of-freedom movements;

[0008] The intelligent gripper adopts a variable diameter design and includes a first dual-degree-of-freedom base connected to a three-dimensional robotic arm. The first dual-degree-of-freedom base is connected to four hydraulic rods with variable diameter adjustment. Each hydraulic rod arm is connected to a second dual-degree-of-freedom base at the end furthest from the first dual-degree-of-freedom base. Each second dual-degree-of-freedom base is connected to a claw, and each claw has a claw lock on its inner side. Each second dual-degree-of-freedom base integrates a sensor module.

[0009] In a further optimization, each of the Mecanum wheels is connected to an electric motor for driving its movement, and the AGV base is also equipped with a chassis drive controller for controlling the electric motor.

[0010] Further optimization involves a layered layout structure inside the central housing, with a communication layer at the top, a core processing layer in the middle, and a power supply layer at the bottom. Each of the two opposite sides of the central housing is equipped with a retractable bracket, and a cooling fan assembly is provided on one side of the central housing.

[0011] Further optimization involves installing communication modules in the communication layer, with the modules connected to each other via a backplane.

[0012] The core processing layer is equipped with a central industrial control computer, a lidar, a lidar point cloud processing module, and an image processing module. The central industrial control computer is horizontally set, and the lidar point cloud processing module and the image processing module are arranged side by side. A lidar window is provided on one side of the central housing and on the side away from the cooling fan group, and the lidar is arranged corresponding to the lidar window.

[0013] The power supply layer is equipped with a battery pack and a capacitor pack, with the battery pack located at the center of gravity of the central housing.

[0014] Further optimization includes a three-dimensional robotic arm comprising a dual-degree-of-freedom lumbar joint, a prismatic shoulder joint, an upper arm joint, a forearm joint, and a wrist joint connected in sequence. An image acquisition camera is mounted on the forearm joint. The dual-degree-of-freedom lumbar joint employs a dual-axis hinge design to drive the prismatic shoulder joint in horizontal and vertical rotation. The prismatic shoulder joint uses a linear translation and rotation design to drive the upper arm joint in lifting and vertical rotation. Both the upper arm and forearm joints employ a single-axis rotation design. The wrist joint drives the intelligent gripper in pitch motion, and a quick-change interface is provided between the wrist joint and the intelligent gripper.

[0015] Further optimization involves the integration of a displacement sensor and a balance sensor into the sensor module.

[0016] The present invention also provides a method for formwork hoisting, including the intelligent trolley for formwork hoisting described above, the steps of which are as follows:

[0017] Step S1, Environmental Perception and Map Building: The intelligent vehicle is guided into the construction area by remote control. The intelligent vehicle uses LiDAR to scan the surrounding environment and the template stacking position through the LiDAR window. The LiDAR point cloud processing module performs frame matching and backend optimization on the massive point cloud data collected based on SLAM, and builds a three-dimensional environmental map in real time that includes obstacles, passages and template stacking positions, and determines its own pose.

[0018] Step S2, Task Planning: Based on the preset template installation locations and steps, the central industrial control computer performs global path planning and motion trajectory generation according to the preset template installation locations on the constructed environment map.

[0019] Step S3, autonomous path finding and material grabbing: The AGV trolley base automatically moves to the material stacking position according to the planned path, and the three-dimensional robotic arm controls the intelligent gripper to grab the template lifting ring according to the planned collaborative visual recognition system;

[0020] Step S4, intelligent hoisting and active sway elimination: Based on planning, the three-dimensional robotic arm lifts the template, and during the hoisting process, the sensor integrated module monitors the swing amplitude and tilt angle of the hook in real time. The central box calculates the compensation amount in real time according to the feedback data of the sensor integrated module and actively eliminates sway by controlling the movement of the intelligent gripper, ensuring that the template remains stable during the movement and is accurately delivered to the installation position.

[0021] Step S5: The hook detaches. After the template is installed in the designated position, the hook lock opens, the hook detaches from the lifting hole, and the template hoisting is completed.

[0022] Further optimization involves using A* and other algorithms for path planning in step S2, where the motion trajectory is a smooth motion trajectory of each joint of the three-dimensional robotic arm, obtained by solving inverse kinematics to transform the grasping and hoisting path into a smooth motion trajectory.

[0023] Further optimization involves step S3, where the visual recognition system's tasks include visual feedback from the image acquisition camera and real-time distance detection from the sensor integration module.

[0024] Further optimization involves, in step S4, the anti-oscillation step, which includes:

[0025] (1) The swing angle error of the hook is collected in real time through the sensor integration module. and displacement error And sampling is performed according to a set frequency to meet real-time requirements; among which, Indicates time, Indicates the horizontal angle of the hook claw. This indicates the actual angle of the hook claw. This indicates the horizontal displacement of the hook. This indicates the actual displacement of the hook claw;

[0026] (2) Calculate the PID term using the PID algorithm, including the proportional term. Integral terms and differential terms The total compensation amount was calculated after dimensional conversion. ;in, , , Both represent gain parameters. for or , This represents the sampling time interval, i.e., the time difference between two consecutive samples taken by the control system, usually expressed in seconds. Indicates the first The error values ​​at each sampling time point, where Integer index ( =0,1,2,...);

[0027] (3) Calculate the total compensation amount Send to the smart gripper, based on the total compensation amount The positive and negative control intelligent gripper is fine-tuned.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] This intelligent vehicle consists of an AGV base, a central housing, a 3D robotic arm, and an intelligent gripper. The AGV base enables omnidirectional movement, lateral movement, and in-situ rotation of the intelligent vehicle in confined construction environments, ensuring its flexibility in complex sites. The central housing integrates a laser point cloud processing module, an image processing module, a lidar, and a central industrial control computer, employing a distributed architecture to achieve collaborative control of each module and integrated processing of control information. The 3D robotic arm drives the intelligent gripper to perform complex movements such as translation, rotation, and pitch, enabling multi-degree-of-freedom motion. The intelligent gripper precisely grasps the template with high gripping strength and locking function. Furthermore, the intelligent gripper adopts a variable-diameter adaptive structure, allowing it to handle templates of different sizes without replacement, significantly improving work efficiency.

[0030] By adopting laser point cloud and SLAM technology, autonomous route planning can be performed, reducing manual labor; the detachable connection between the wrist joint and the intelligent gripper via the quick-change interface makes it easy to replace hooks of different specifications to adapt to diverse formwork hoisting needs.

[0031] The coordinated rotation of the first and second dual-degree-of-freedom bases provides the hook with multi-degree-of-freedom attitude adjustment capabilities, including pitch, yaw, and roll. The mechanical structure design of the first and second dual-degree-of-freedom bases, combined with the precision telescopic drive of the hydraulic arm, forms the physical basis for anti-swaying. Based on real-time feedback from the sensor integration module, the hydraulic arm receives PID compensation commands calculated by the central housing, dynamically outputs fine-tuning signals, and then drives the hydraulic arm to perform millimeter-level telescopic compensation. This actively suppresses the inertial sway of the template during hoisting, achieving precise gripping and stable hoisting of the template.

[0032] This intelligent vehicle achieves a high degree of automated control, which can reduce manual labor, improve construction safety, reduce labor costs, and improve construction efficiency; it effectively solves the problems of traditional formwork hoisting, such as the need for manual replacement of hoisting balance beams, limited working space, low positioning accuracy, and difficulty in swing control. Attached Figure Description

[0033] Figure 1 This is a structural schematic diagram of the intelligent trolley for template hoisting disclosed in this invention;

[0034] Figure 2 This is a schematic diagram of the structure of the AGV trolley base disclosed in this invention;

[0035] Figure 3 This is a schematic diagram of the structure of the central box disclosed in this invention;

[0036] Figure 4 This is a schematic diagram of the structure of the three-dimensional robotic arm disclosed in this invention;

[0037] Figure 5 This is a schematic diagram of the structure of the intelligent gripper disclosed in this invention.

[0038] Reference numerals: 1-AGV trolley base, 101-Mecanum wheel, 102-Motor, 103-Chassis drive controller, 2-Central housing, 201-LiDAR window, 202-Bracket, 203-Communication module, 204-Central industrial control computer, 205-LiDAR, 206-LiDAR point cloud processing module, 207-Image processing module, 208-Battery pack, 209-Capacitor pack, 210-Cooling fan pack, 3-3D robotic arm, 301-Dual-degree-of-freedom waist joint, 302-Pyramidal shoulder joint, 303-Upper arm joint, 304-Forearm joint, 305-Wrist joint, 306-Image acquisition camera, 4-Intelligent gripper, 401-First dual-degree-of-freedom base, 402-Hydraulic lever arm, 403-Second dual-degree-of-freedom base, 404-Sensor integration module, 405-Hook, 406-Hook lock. Detailed Implementation

[0039] The following are specific embodiments of the present invention, which are described in conjunction with the accompanying drawings. However, the present invention is not limited to these embodiments.

[0040] like Figure 1 , Figure 2 and Figure 5 As shown, this application discloses an intelligent trolley for template hoisting, including an AGV trolley base 1, a central box 2, a three-dimensional robotic arm 3, and an intelligent gripper 4 connected in sequence;

[0041] The AGV base 1 is equipped with four Mecanum wheels 101 that can move in all directions;

[0042] Central housing 2 is used for integrating and processing control information;

[0043] The three-dimensional robotic arm 3 adopts a four-degree-of-freedom design to drive the intelligent gripper 4 to perform multi-degree-of-freedom movements;

[0044] The intelligent gripper 4 adopts a variable diameter design and includes a first dual-degree-of-freedom base 401 connected to the three-dimensional robotic arm 3. The first dual-degree-of-freedom base 401 is connected to four hydraulic rod arms 402 with variable diameter adjustment. Each hydraulic rod arm 402 is connected to a second dual-degree-of-freedom base 403 at the end away from the first dual-degree-of-freedom base 401. Each second dual-degree-of-freedom base 403 is connected to a hook 405. Each hook 405 has a hook lock 406 on its inner side. Each second dual-degree-of-freedom base 403 integrates a sensor integration module 404.

[0045] In this application, the intelligent trolley is used for template hoisting operations. It features an intelligent recognition system and active anti-sway function, enabling automated template hoisting. The intelligent trolley includes an AGV base 1, a central housing 2, a three-dimensional robotic arm 3, and an intelligent gripper 4. The AGV base 1 is used for the automated movement of the entire device; the central housing 2 is mounted on the AGV base 1 and integrates and processes control information; the three-dimensional robotic arm 3 is mounted on the central housing 2 and drives the multi-degree-of-freedom movement of the intelligent gripper 4. The intelligent gripper 4 is used to grasp the template. Through the cooperation of the AGV base 1, the central housing 2, the three-dimensional robotic arm 3, and the intelligent gripper 4, the intelligent trolley achieves automatic movement, enabling precise grasping and hoisting of the template.

[0046] In this application, the AGV base 1 is equipped with Mecanum wheels 101, which enable omnidirectional movement, allowing the intelligent vehicle to move omnidirectionally, laterally, and rotate in place in narrow construction environments, thus ensuring the flexibility of the equipment in complex sites.

[0047] In this application, the three-dimensional robotic arm 3 adopts a four-degree-of-freedom design, which can reduce structural and cost complexity, optimize kinematic and dynamic performance, realize multi-degree-of-freedom motion, and achieve more efficient and reliable motion control while meeting specific task requirements.

[0048] In this application, the intelligent gripper 4 adopts a variable diameter design, which adapts to the template to be gripped. It can grip templates of different specifications without changing the hook 405, which significantly improves work efficiency. The intelligent gripper 4 includes a first dual-degree-of-freedom base 401, a hydraulic lever arm 402, a second dual-degree-of-freedom base 403, a sensor integration module 404, a claw 405, and a claw lock 406. Through the coordinated rotation of the first dual-degree-of-freedom base 401 and the second dual-degree-of-freedom base 403, the claw 405 is provided with multi-degree-of-freedom attitude adjustment capabilities such as pitch, yaw, and roll. The mechanical structure design of the first dual-degree-of-freedom base 401 and the second dual-degree-of-freedom base 403, combined with the precision telescopic drive of the hydraulic lever arm 402, constitutes the physical basis for anti-swaying. Based on the real-time feedback from the sensor integration module 404 integrated at the claw 405, the hydraulic lever arm 402 receives PID compensation commands calculated by the central housing 2, dynamically outputs fine-tuning signals, and then drives the hydraulic lever arm 402 to perform millimeter-level telescopic compensation, thereby actively suppressing the inertial sway of the template during the hoisting process and achieving precise gripping and stable hoisting of the template. Four hooks 405, connected to four hydraulic levers 402, enable four-point gripping of the template, ensuring the firmness and stability of the grip and reducing template sway. A sensor integration module 404 monitors the displacement and attitude balance of the hooks 405 in real time and feeds the signals back to the central housing 2.

[0049] In this application, both the first dual-degree-of-freedom base 401 and the second dual-degree-of-freedom base 403 feature a dual-axis hinge design, achieving vertical and horizontal rotation via servo motor drive, ultimately enabling the hook 405 to adjust its attitude in multiple degrees of freedom, including pitch, yaw, and roll. A hook lock 406 is located on the inner side of the hook 405 near the claw tip. The lifting ring of the template can push the hook lock 406 inwards towards the hook 405, opening it. When the lifting ring slides into a certain position, the hook lock 406 automatically springs back, locking the lifting ring within the hook 405. When the template needs to be released, the hook lock 406 is driven by its connected motor to move inwards towards the hook 405 to unlock, and automatically springs back to its original position after the lifting ring slides out of the hook 405.

[0050] In this application, the claws 405 can adaptively adjust their gripping method according to the orientation of the template to improve gripping stability and efficiency. Specifically: First, when gripping a template perpendicular to the ground, the claws 405 grip in pairs, that is, adjacent claws 405 work together to form a compact gripping point, reducing the risk of swaying; Second, when gripping a module horizontal to the ground, the four claws 405 grip the four corners of the template respectively, and the balance status is monitored in real time by the sensor integration module 404 to ensure uniform load distribution. This adaptive gripping strategy is implemented collaboratively by the image processing module 207 and the laser point cloud processing module 206 in the central housing 2. By analyzing the template orientation data, the first dual-degree-of-freedom base 401 and the second dual-degree-of-freedom base 403 are automatically driven to adjust the attitude of the claws 405.

[0051] like Figure 2 As shown, in one embodiment of this application, each Mecanum wheel 101 is connected to an electric motor 102 for driving its movement, and the AGV trolley base 1 is also provided with a chassis drive controller 103 for controlling the electric motor 102.

[0052] In this embodiment, each Mecanum wheel 101 is connected to a corresponding electric motor 102. Each Mecanum wheel 101 can move independently, enabling forward, backward, lateral, stationary, and diagonal movement. Omnidirectional movement is achieved through four-wheel coordinated control and force decomposition. The chassis drive controller 103 receives commands to control the start and stop of each electric motor 102, ultimately enabling the intelligent vehicle to move omnidirectionally, laterally, and rotate in place in narrow construction environments, ensuring the flexibility of the intelligent vehicle in complex terrain.

[0053] like Figure 3 As shown, in another embodiment of this application, the interior of the central housing 2 adopts a layered layout structure, with the top layer being the communication layer, the middle layer being the core processing layer, and the bottom layer being the power supply layer. A retractable bracket 202 is provided on each of the two opposite sides of the central housing 2, and a cooling fan group 210 is provided on one side of the housing of the central housing 2.

[0054] In this embodiment, the central housing 2 adopts a layered layout design, which optimizes heat dissipation and signal transmission. The top layer is the communication layer, used for signal transmission; the middle layer is the core processing layer, used for data processing, calculation, and instruction output, which is the brain of the intelligent vehicle and controls the operation of all structures in the vehicle; the bottom layer is the power supply layer, used to provide power to the intelligent vehicle.

[0055] In this embodiment, the central housing 2 is equipped with supports 202 on both sides. The supports 202 are telescopic structures, each with two legs. The height and spacing between the two legs are telescopically adjustable, allowing adjustment in both horizontal and vertical directions. After the AGV is in place, the supports 202 secure the AGV base 1, ensuring the entire AGV is fixed and providing support, thus ensuring the stability and safety of the AGV during hoisting. A cooling fan assembly 210 is located at the rear of the central housing 2, forming a continuous cooling duct with good heat dissipation performance, ensuring the stability of the equipment during long-term operation.

[0056] Furthermore, the communication layer is equipped with communication modules 203. The modules of communication modules 203 are connected through a backplane, which can ensure that signal reception is not affected by the shielding of the underlying metal components and guarantee the quality of data transmission.

[0057] The core processing layer houses a central industrial control computer 204, a lidar 205, a laser point cloud processing module 206, and an image processing module 207. The central industrial control computer 204 is horizontally positioned, which lowers its center of gravity, reducing stress concentration caused by tilting. Its large mounting surface area also reduces vibration, ensuring system stability and reliability. The central industrial control computer 204 employs an embedded structure, running intelligent decision-making algorithms to coordinate the movement of the AGV base 1, the motion of the 3D robotic arm 3, and the control of the intelligent gripper 4. The laser point cloud processing module 206 and the image processing module 207 are arranged side-by-side, minimizing interference and facilitating data exchange between them. The laser point cloud processing module 206 uses SLAM technology to construct an environmental mapping, providing the intelligent vehicle with autonomous navigation and obstacle avoidance capabilities. The image processing module 207 uses a deep learning model to identify template types and lifting points. Through the cooperation of the central industrial control computer 204, the laser point cloud processing module 206, and the image processing module 207, data processing and command output are realized. A laser radar window 201 is provided on one side of the central housing 2, away from the cooling fan group 210, and a laser radar 205 is arranged corresponding to the laser radar window 201. The laser radar 205 can scan the surrounding environment and material stacking positions through the laser radar window 201. The laser point cloud processing module 206 performs frame matching and back-end optimization on the massive point cloud data collected based on SLAM, and constructs a three-dimensional environmental map in real time that includes obstacles, channels, and material stacking positions, and determines its own pose.

[0058] The power supply layer is equipped with a battery pack 208 and a capacitor pack 209. The battery pack 208 is located at the center of gravity of the central housing 2. The battery pack 208 provides power to the entire intelligent vehicle. Its location at the center of gravity of the central housing 2 helps maintain the vehicle's balance and further improves the vehicle's stability. The capacitor pack 209 provides instantaneous high current support to meet the power requirements when the three-dimensional robotic arm 3 starts up.

[0059] like Figure 4 As shown, in another embodiment of this application, the three-dimensional robotic arm 3 includes a dual-degree-of-freedom waist joint 301, a prism shoulder joint 302, an upper arm joint 303, a forearm joint 304, and a wrist joint 305 connected in sequence. An image acquisition camera 306 is provided on the forearm joint 304. The dual-degree-of-freedom waist joint 301 adopts a dual-axis hinge design to drive the prism shoulder joint 302 to perform horizontal and vertical rotational movements. The prism shoulder joint 302 adopts a linear translation and rotation design to drive the upper arm joint 303 to perform lifting and vertical rotational movements. Both the upper arm joint 303 and the forearm joint 304 adopt a single-axis rotational design. The wrist joint 305 is used to drive the intelligent gripper 4 to perform pitching movements. A quick-change interface is provided between the wrist joint 305 and the intelligent gripper 4.

[0060] In this embodiment, the dual-degree-of-freedom waist joint 301, prism shoulder joint 302, upper arm joint 303, forearm joint 304, and wrist joint 305 form a multi-degree-of-freedom motion mechanism. Each joint is driven by a robotic arm control module (integrated within the central housing 2) to achieve complex movements such as translation, rotation, and pitch. The dual-degree-of-freedom waist joint 301 serves as the basic directional joint, employing a dual-axis hinge design. The vertical rotation axis is driven by a servo motor to achieve horizontal rotation, while the horizontal rotation axis is responsible for longitudinal pitch. The prism shoulder joint 302 combines linear movement and rotation functions. Its prism portion achieves lifting motion through a gear and rack mechanism, and the slidable rotating component drives the upper arm joint 303 to rotate, serving as a power transmission hub. The upper arm joint 303 and forearm joint 304, as the main connecting rods, both adopt a single-axis rotation design. Torque is amplified by an RV reducer. The upper arm joint 303 drives the forearm joint 304 to achieve extension and bending, and the motion trajectory is smoothly coordinated through an inverse kinematics algorithm. The wrist joint 305 serves as the end effector interface, providing a single degree of freedom for pitch. It connects to the smart gripper 4 via a quick-change interface and utilizes a micro servo motor to achieve fine posture adjustment with a response time of <50ms.

[0061] In this embodiment, the collaborative workflow of each joint is as follows: the dual-degree-of-freedom waist joint 301 first rotates horizontally to align with the work point; the prism shoulder joint 302 adjusts the height by raising and lowering; the upper arm joint 303 and forearm joint 304 extend the arm; and the wrist joint 305 fine-tunes the posture of the intelligent gripper 4. The entire process is assisted by the image acquisition camera 306 for positioning, ensuring precise suppression of swaying during hoisting. The forearm joint 304 is equipped with an image acquisition camera 306, which is used to acquire image information of the template to be hoisted in real time and transmit the data to the image processing module 207 in the central housing 2 for identification and positioning. Based on the template image information acquired by the image acquisition camera 306 and the spatial point cloud data acquired by the lidar 205, motion trajectory commands for the three-dimensional robotic arm 3 can be generated to control the multi-degree-of-freedom movement of the three-dimensional robotic arm 3, thereby enabling the translation, rotation, and pitch movements of the intelligent gripper 4.

[0062] In another embodiment of this application, the sensor integration module 404 includes a displacement sensor and a balance sensor. The displacement sensor can monitor the distance between the hook 405 and the template surface in real time, and the balance sensor can monitor the tilt angle of the hook 405 in real time. The core processing layer in the central housing 2 dynamically adjusts the extension and pressure of the hydraulic arm 402 through the feedback signals of the displacement sensor and the balance sensor, which can suppress the swaying during the hoisting process and realize the stable gripping and precise hoisting of the template.

[0063] This invention also discloses a method for hoisting formwork, which uses intelligent operation of a smart vehicle to hoist the formwork. The steps are as follows:

[0064] Step S1, Environmental Perception and Map Building: The intelligent vehicle is guided into the construction area by remote control. The intelligent vehicle uses LiDAR 205 to scan the surrounding environment and template stacking position through LiDAR window 201. The LiDAR point cloud processing module 206 performs frame matching and backend optimization on the massive point cloud data collected based on SLAM, and builds a three-dimensional environmental map in real time that includes obstacles, passages and template stacking position, and determines its own pose.

[0065] Step S2, task planning: Based on the preset template installation position and steps, the central industrial control computer 204 performs global path planning and motion trajectory generation according to the preset template installation position and the environmental map constructed in step 1. The path planning uses algorithms such as A* to plan the optimal travel path, and the chassis drive controller 103 controls the Mecanum wheels 101 to achieve omnidirectional movement. The motion trajectory is obtained by solving inverse kinematics to transform the grasping and lifting path into a smooth motion trajectory of each joint of the three-dimensional robotic arm 3.

[0066] Step S3, autonomous path finding and material grabbing: The AGV base 1 automatically moves to the material stacking position according to the planned path. The three-dimensional robotic arm 3 controls the intelligent gripper 4 to grab the template lifting ring according to the planned collaborative visual recognition system. The visual recognition system accurately adjusts the end posture through visual feedback from the image acquisition camera 306 and real-time distance detection through the sensor integration module 404.

[0067] Step S4, intelligent hoisting and active sway elimination: Based on the planning in step S2, the three-dimensional robotic arm 3 lifts the template. During the hoisting process, the sensor integration module 404 monitors the swing amplitude and tilt angle of the hook 405 in real time. The central box 2 calculates the compensation amount in real time according to the feedback data of the sensor integration module 404 and actively eliminates sway by controlling the movement of the intelligent gripper 4 to ensure that the template remains stable during the movement and is accurately delivered to the installation position.

[0068] In step S5, the hook detaches. After the template is installed in the designated position, the hook lock 406 opens, and the second double-degree-of-freedom base 403 drives the hook 405 to adjust its angle so that the hook 405 smoothly disengages from the template lifting hole, completing the template lifting. Then the three-dimensional robotic arm 3 retracts, and the intelligent trolley prepares to perform the next lifting task.

[0069] In the hoisting step S4 of the present invention, the anti-sway step includes:

[0070] (1) The swing angle error of the hook 405 is collected in real time by the sensor integration module 404. and displacement error And sampling is performed according to a set frequency to meet real-time requirements; among which, Indicates time, This indicates the horizontal angle of the 405 hook. This indicates the actual angle of the 405 hook. This indicates the horizontal displacement of the 405 hook. This indicates the actual displacement of the hook 405.

[0071] (2) Calculate the PID term using the PID algorithm, including the proportional term. Integral terms and differential terms The total compensation amount was calculated after dimensional conversion. ;in, , , Both represent gain parameters. for or , This represents the sampling time interval, i.e., the time difference between two consecutive samples taken by the control system, usually expressed in seconds. Indicates the first The error values ​​at each sampling time point, where Integer index ( =0,1,2,...);

[0072] (3) Calculate the total compensation amount Send to Smart Grasp 4, based on total compensation amount The positive and negative control intelligent gripper 4 is fine-tuned.

[0073] During the oscillation elimination process, the compensation amount needs to be calculated in real time using a PID algorithm to determine the total compensation amount. Sending data to the hydraulic lever arm (402) via a servo driver, based on... The positive and negative drive hydraulic lever 402 is used for fine-tuning extension and retraction, for example... The hydraulic lever arm extends when the synchrotron is positive and shortens when the synchrotron is negative, actively counteracting inertial sway and ensuring the template remains stable during movement and is precisely delivered to the installation position. The performance of the PID algorithm depends on the gain parameter (…). , , For the tuning of ), this invention adopts the Ziegler-Nichols tuning method, based on the tuning of ) , Set as zero-time control Critical gain that causes critical oscillations as it gradually increases and oscillation period The parameters are calculated. The core processing layer of the central box 2 can integrate adaptive PID algorithms, such as fuzzy PID or gain scheduling. For example, when the swing amplitude is large, it automatically increases... and To quickly suppress; to reduce when the oscillation approaches zero. Avoid overshoot and increase To precisely eliminate residual errors.

[0074] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A method for formwork hoisting, characterized in that, It includes an intelligent trolley for template hoisting, the intelligent trolley comprising an AGV trolley base (1), a central housing (2), a three-dimensional robotic arm (3), and an intelligent gripper (4) connected in sequence. The AGV base (1) is equipped with four Mecanum wheels (101) that can move in all directions. The central box (2) is used to integrate and process control information; The three-dimensional robotic arm (3) adopts a four-degree-of-freedom design to drive the intelligent gripper (4) to perform multi-degree-of-freedom motion; The intelligent gripper (4) adopts a variable diameter design and includes a first dual-degree-of-freedom base (401) connected to the three-dimensional robotic arm (3). The first dual-degree-of-freedom base (401) is connected to four hydraulic rods (402) with variable diameter adjustment. Each hydraulic rod (402) is connected to a second dual-degree-of-freedom base (403) at the end away from the first dual-degree-of-freedom base (401). Each second dual-degree-of-freedom base (403) is connected to a claw (405). Each claw (405) has a claw lock (406) on its inner side. Each second dual-degree-of-freedom base (403) is integrated with a sensor integration module (404). The steps for this method of formwork hoisting are as follows: Step S1, Environmental perception and map building: The intelligent vehicle is guided into the construction area by remote control by personnel. The intelligent vehicle uses LiDAR (205) to scan the surrounding environment and template stacking position through the LiDAR window (201). The LiDAR point cloud processing module (206) performs frame matching and backend optimization on the massive point cloud data collected based on SLAM, and builds a three-dimensional environmental map in real time that includes obstacles, passages and template stacking position, and determines its own pose. Step S2, Task Planning: The central industrial control computer (204) performs global path planning and motion trajectory generation based on the preset template installation location and steps, on the constructed environment map; Step S3, autonomous path finding and material grabbing: the AGV base (1) automatically moves to the material stacking position according to the planned path, and the three-dimensional robotic arm (3) controls the intelligent gripper (4) to grab the template lifting ring according to the planned collaborative visual recognition system; Step S4, intelligent hoisting and active sway elimination: Based on planning, the three-dimensional robotic arm (3) lifts the template, and during the hoisting process, the sensor integration module (404) monitors the swing amplitude and tilt angle of the hook (405) in real time. The central box (2) calculates the compensation amount in real time according to the feedback data of the sensor integration module (404) and actively eliminates sway by controlling the movement of the intelligent gripper (4), ensuring that the template remains stable during the movement and is accurately delivered to the installation position; wherein, the sway elimination steps include: (1) The swing angle error of the hook (405) is collected in real time by the sensor integration module (404). and displacement error And sampling is performed according to a set frequency to meet real-time requirements; among which, Indicates time, This indicates the horizontal angle of the grappling hook (405). This indicates the actual angle of the grappling hook (405). This indicates the horizontal displacement of the hook (405). This represents the actual displacement of the hook (405); (2) Calculate the PID term using the PID algorithm, including the proportional term. Integral terms and differential terms The total compensation amount was calculated after dimensional conversion. ;in, , , , represents the gain parameter, for or , This represents the sampling time interval, i.e., the time difference between two consecutive samples taken by the control system, usually expressed in seconds. Indicates the first The error values ​​at each sampling time point, where Integer index ( =0,1,2,...); (3) Calculate the total compensation amount Send to the smart gripper (4), based on the total compensation amount The positive and negative control intelligent gripper (4) is fine-tuned; Step S5: The hook detaches. After the template is installed in the designated position, the hook lock (406) is opened, and the hook (405) disengages from the lifting hole, completing the hoisting of the template.

2. The method for formwork hoisting according to claim 1, characterized in that, Each of the Mecanum wheels (101) is connected to an electric motor (102) for driving its movement, and the AGV base (1) is also provided with a chassis drive controller (103) for controlling the electric motor (102).

3. The method for formwork hoisting according to claim 1, characterized in that, The internal structure of the central box (2) adopts a layered layout. The top layer is the communication layer, the middle layer is the core processing layer, and the bottom layer is the power supply layer. A retractable bracket (202) is provided on each of the two opposite sides of the central box (2). A cooling fan group (210) is provided on one side of the central box (2).

4. A method for formwork hoisting according to claim 3, characterized in that, The communication layer is equipped with communication modules (203), and the modules of the communication modules (203) are connected to each other through a backplane; The core processing layer is equipped with a central industrial control computer (204), a lidar (205), a lidar point cloud processing module (206), and an image processing module (207). The central industrial control computer (204) is horizontally arranged, and the lidar point cloud processing module (206) and the image processing module (207) are arranged side by side. A lidar window (201) is provided on one side of the central housing (2) away from the cooling fan group (210), and the lidar (205) is arranged corresponding to the lidar window (201). The power supply layer is equipped with a battery pack (208) and a capacitor pack (209), with the battery pack (208) located at the center of gravity of the central housing (2).

5. A method for formwork hoisting according to claim 1, characterized in that, The three-dimensional robotic arm (3) includes a dual-degree-of-freedom waist joint (301), a prism shoulder joint (302), an upper arm joint (303), a forearm joint (304), and a wrist joint (305) connected in sequence. An image acquisition camera (306) is provided on the forearm joint (304). The dual-degree-of-freedom waist joint (301) adopts a dual-axis hinge design to drive the prism shoulder joint (302) to perform horizontal and vertical rotation. The prism shoulder joint (302) adopts a linear movement and rotation design to drive the upper arm joint (303) to perform lifting and vertical rotation. The upper arm joint (303) and the forearm joint (304) both adopt a single-axis rotation design. The wrist joint (305) is used to drive the intelligent gripper (4) to perform pitch movement. A quick-change interface is provided between the wrist joint (305) and the intelligent gripper (4).

6. A method for formwork hoisting according to claim 1, characterized in that, The sensor integration module (404) includes a displacement sensor and a balance sensor.

7. A method for formwork hoisting according to claim 1, characterized in that, In step S2, the path planning adopts the A* algorithm, and the motion trajectory is the smooth motion trajectory of each joint of the three-dimensional robotic arm (3) by solving the inverse kinematics to transform the grasping and hoisting path into a smooth motion trajectory.

8. A method for formwork hoisting according to claim 1, characterized in that, In step S3, the operation of the visual recognition system includes visual feedback from the image acquisition camera (306) and real-time distance detection from the sensor integration module (404).

Images