A box unloading operation robot and a control method thereof
By using a container unloading robot with foldable forks and a multi-sensor network inside the container, the problems of low efficiency and poor safety in container unloading operations have been solved. It achieves high-precision positioning and flexible maneuverability, ensuring the safety, reliability and efficiency of the operation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG EP EQUIP
- Filing Date
- 2026-03-16
- Publication Date
- 2026-06-09
AI Technical Summary
Existing technologies for unpacking operations inside containers suffer from low efficiency, high labor intensity, poor spatial adaptability, difficulty in sensing and positioning, and high safety risks, making it difficult to meet the requirements of automation and safety.
Employing a foldable fork structure, a multi-LiDAR and surround-view camera sensor network, and a control system that combines SLAM data with 3D vision data, it achieves high-precision positioning and flexible maneuverability. Environmental modeling and path planning are performed through multi-sensor data fusion, and safety is ensured by using impact plates and microswitches.
It enables efficient, safe, and precise unpacking operations in narrow, enclosed spaces, reducing the risk of collisions between equipment and goods and improving operational efficiency and safety.
Smart Images
Figure CN122166692A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of logistics and warehousing technology, and in particular to a robot and its control method for unpacking and stacking goods inside closed or semi-closed containers such as containers and truck compartments. Background Technology
[0002] With the rapid development of global trade and e-commerce logistics, container transportation has become a core link in cargo transshipment. At logistics hubs, ports, and freight stations, goods need to be unloaded from containers (i.e., "unpacking" or "unloading") and transferred to warehouses or the next stage of transportation. Traditional unpacking operations mainly rely on manual operation or manually driven forklifts. However, the extremely narrow and enclosed space inside containers, coupled with the dense stacking of goods, presents numerous challenges to traditional unpacking methods: Low operational efficiency and high labor intensity: Manually driving forklifts into containers requires drivers with extremely high operating skills. Frequent forward, backward, turning, and lifting operations in a confined space are not only slow but also cause driver fatigue and pose safety hazards. Purely manual handling is even less efficient and cannot meet the ever-increasing demand for logistics throughput.
[0003] Space constraints lead to poor equipment adaptability: Ordinary automated guided vehicles or stacker cranes are usually large in size and have a large turning radius, making it difficult to drive directly into the narrow interior of a container for operation. Even if they manage to enter, they cannot flexibly adjust their posture inside the container to achieve precise loading and unloading of goods in different positions, and are prone to rubbing against the container walls and goods, damaging the goods or equipment.
[0004] Perception and positioning difficulties: The interior of containers is dimly lit and has a monotonous environment (such as the plain corrugated board walls), making traditional single laser or visual navigation methods prone to failure. This results in equipment being unable to accurately locate itself and identify the position of goods. Drivers need to frequently get out of the vehicle to observe, making continuous and efficient automated operation impossible. In particular, even slight deviations when the forks extend into the bottom of the pallet can lead to failed retrieval or even damage to the goods.
[0005] High safety risks: Drivers have large blind spots inside the vehicle, making it difficult to fully observe the cargo inside the container and the surrounding environment, increasing the risk of collisions. Furthermore, the lack of real-time monitoring of cargo status during handling means that any tilting or falling cargo cannot be detected and addressed promptly.
[0006] Therefore, designing an automated container unloading operation device that can adapt to narrow, enclosed spaces such as shipping containers, and possesses high-precision positioning, flexibility, and reliability, is a technical problem that urgently needs to be solved by those skilled in the art. While some existing automated forklift or AGV solutions have achieved a degree of unmanned operation, their spatial adaptability, environmental awareness, and operational safety are still significantly insufficient when facing extreme conditions like container unloading, making it difficult to meet practical application needs. Summary of the Invention
[0007] To solve the above-mentioned technical problems, the first objective of this invention is to provide a container unpacking robot that enables dense stacking in confined container environments and improves enterprise work efficiency; the second objective of this invention is to provide a control method for the container unpacking robot.
[0008] To achieve the first objective of the invention, the present invention adopts the following technical solution: A box-unloading robot includes a vehicle body and a gantry mechanism located at the front end of the vehicle body. The gantry mechanism also has a fork carriage that can be raised and lowered vertically. Two forks are spaced apart at the front end of the fork carriage. The forks are hinged to the fork carriage, and a folding cylinder is provided between the forks and the fork carriage to drive the forks to fold or unfold. A blind spot laser and a top surround-view camera are provided at the top rear end of the vehicle body. Side surround-view cameras are provided on both sides of the vehicle body. Obstacle avoidance lasers are provided on both sides of the bottom rear end of the vehicle body. A navigation laser is provided at the top of the gantry mechanism. A bottom recognition laser and a fork end surround-view camera are provided at the bottom of the forks. An industrial control computer, an oil pump, and a solenoid valve are also provided on the vehicle body. The industrial control computer controls the movement of the vehicle body and the raising and lowering of the forks based on data from the navigation laser, blind spot laser, and obstacle avoidance laser.
[0009] As a preferred embodiment, the forks are equipped with a stop plate for determining whether goods have been picked up; the forks are also equipped with a micro switch for determining whether the forks are folded or unfolded into place.
[0010] To achieve the second objective of the invention, the present invention adopts the following technical solution: A control method for a box-opening robot includes the following steps: Step S1: Data is acquired through navigation laser, blind spot laser, and obstacle avoidance laser. The multi-laser SLAM data is aggregated and sent to the industrial control computer. The industrial control computer organizes and aggregates the data and sends it to the upper control system of the unloading truck. The upper control system models the environment, obtains the stacking order of the goods, and initializes the state of the stacking area. In step S2, the upper-level control system calculates and determines the passage area to see if the vehicle can move in front of the goods to be stacked. If the passage requirements are met, the vehicle moves directly to the front of the goods. If the passage area is insufficient, the upper-level software controls the oil pump and solenoid valve of the forks to control the extension and retraction of the folding cylinders of the forks through hydraulic oil, thereby folding and unfolding the forks. When the microswitches on the forks are triggered, they will send a signal to the upper-level control system to indicate the position. The upper-level control system then controls the forks to fold completely, thereby reducing the turning radius and adjusting the vehicle's posture in a narrow space. As needed, the upper-level control system queries the data from the top and side surround-view cameras of the vehicle to determine the size of the space around the vehicle and avoid collisions when adjusting the vehicle's posture. Depending on the complexity of the narrow space, the vehicle's posture is adjusted once or multiple times until it finally moves directly in front of the goods to be stacked. Then, the upper-level control system controls the forks to unfold to a horizontal position. In step S3, the upper control system activates the bottom recognition laser of the forks to identify the goods to be stacked in front of the forks, and controls the forks to rise and move laterally to align with the pallet for picking up the goods. After picking up the goods, the detection plate of the forks is in the triggered state throughout the loading process. At the same time, the upper control system activates the fork end surround-view camera at the bottom of the forks to determine whether the goods have fallen during transportation. If the goods fall, the system immediately stops and notifies the remote end. If the goods do not fall, the goods are transported to the designated location normally.
[0011] As a preferred embodiment, the specific process of environmental modeling in step S1 is as follows: Step S11 constructs a map of the passable area around the robot based on navigation laser, blind spot laser, and obstacle avoidance laser data, which is usually represented by a grid map or geometric features; Step S12: Determine the target point: Based on the position of the goods to be stacked, calculate the target point that the robot needs to reach, which is usually a certain distance in front of the goods. Step S13 Path Search: Attempt to search for a collision-free path from the current location to the target point in the environment map. If a path can be found, it means that the passable area is sufficient. Step S14: Path Feasibility Verification: Verify whether the searched path can be executed by the robot. If the path exists and is feasible, it is determined that the passage area is sufficient, and the robot can move along the path; otherwise, it is determined that the passage area is insufficient. If the passage area is sufficient, move to the front of the goods according to the normal route.
[0012] As a preferred embodiment, the top surround-view camera and the side surround-view camera are activated when the vehicle turns or reverses. The multiple cameras provide multiple image data. The upper-level control system stitches and merges the multiple image data, and then constructs an environmental map and locates itself based on visual SLAM. The upper-level control system then controls the movement of the vehicle through the lower-level control system to ensure high-precision movement of the vehicle in narrow environments.
[0013] As a preferred embodiment, the control process for the folding and unfolding of the forks is as follows: 1. In the fork folding control software, the initial position of the forks is horizontally unfolded. Set the folding angle to 0 and insert the initial 0 position in the upper control system. 2. After the navigation laser mapping is completed, the upper control system calculates that the forks need to be folded at this time, and then controls the folding cylinder on the forks to retract; after the forks are folded, the folding limit micro switch is triggered, and the signal is transmitted to the IO module. The upper control system reads the folding signal at this time, controls the folding cylinder to stop retracting, and sets the folding angle at this time to 1. 3. The upper control system calculates the need to deploy the forks, controls the extension of the folding cylinder, and triggers the deployment limit micro switch when the forks are deployed. The signal is transmitted to the IO module. The upper control system reads the deployment signal at this time and controls the folding cylinder to stop extending, and the folding angle returns to the horizontal deployment position.
[0014] As a preferred embodiment, the calculation process for the obstacle avoidance distance value of the vehicle's obstacle avoidance radar during forward movement is as follows: Warning / Deceleration Distance
[0015] slow stopping distance
[0016] Emergency stopping distance
[0017] in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
[0018] As a preferred embodiment, the calculation process for the obstacle avoidance distance value of the vehicle's obstacle avoidance radar during the reversing process is as follows: Warning / deceleration distance;
[0019] Slow stopping distance;
[0020] Emergency stopping distance;
[0021] in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
[0022] As a preferred embodiment, the calculation process for the obstacle avoidance distance value of the vehicle's obstacle avoidance radar when it is about to reach the destination is as follows: Warning / deceleration distance;
[0023] Slow stopping distance;
[0024] Emergency stopping distance;
[0025] in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
[0026] Compared with the prior art, the beneficial effects of the present invention are as follows: The container unloading robot of the present invention adopts a foldable fork structure. When the robot is traveling or turning outside the container or in a narrow passage, the forks can be folded, which greatly reduces the forward length and turning radius of the whole vehicle, allowing the robot to complete posture adjustment in a very limited space and avoiding collisions with surrounding goods, container walls or equipment due to excessively long forks.
[0027] The container unloading robot of this invention uses multiple sensors, including lasers and surround-view cameras, to collect data. The control system integrates SLAM data with 3D vision data, ensuring the robot's control accuracy and safety in confined and complex environments such as inside containers. Attached Figure Description
[0028] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute a limitation thereof.
[0029] Figure 1 This is a schematic diagram of the overall structure of the unloading robot of the present invention (forks in the lowered state); Figure 2 This is a schematic diagram of the overall structure of the unloading robot of the present invention (forks retracted). Figure 3 This is a side view of the unloading robot of the present invention; Figure 4 This is a schematic diagram of the control logic structure of the box-opening robot of the present invention; Figure 5 This is a schematic diagram of the control process of the box-opening robot of the present invention.
[0030] The labels in the attached diagram are: 1. Vehicle body; 2. Mast mechanism; 21. Navigation laser; 22. Bottom recognition laser; 3. Fork; 30. Fork carriage; 31. Folding cylinder; 32. Bumper plate; 40. Blind spot laser; 41. Top surround view camera; 42. Side surround view camera; 5. Obstacle avoidance laser. Detailed Implementation
[0031] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.
[0032] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.
[0033] Furthermore, in the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.
[0034] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more, unless explicitly defined otherwise.
[0035] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.
[0036] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.
[0037] The present invention will be further described below with reference to the accompanying drawings and embodiments: like Figures 1 to 3 The robot for unloading boxes includes a vehicle body 1 and a gantry mechanism 2 located at the front end of the vehicle body. The gantry mechanism 2 is also equipped with a fork carriage 30 that can be raised and lowered vertically. Two forks 3 are spaced apart at the front end of the fork carriage 30. The forks 3 are hinged to the fork carriage 30, and a folding cylinder 31 is provided between the forks 3 and the fork carriage 30 to drive the forks 3 to fold or unfold. A blind spot laser 40 and a top surround-view camera 41 are provided at the top rear end of the vehicle body 1. Side surround-view cameras 42 are provided on both sides of the vehicle body 1. Obstacle avoidance lasers 5 are provided on both sides of the bottom rear end of the vehicle body 1. A navigation laser 21 is provided at the top of the gantry mechanism 2. A bottom recognition laser 22 and a fork end surround-view camera are provided at the bottom of the forks 3. The vehicle body 1 is also equipped with an industrial control computer, an oil pump, and a solenoid valve. The industrial control computer controls the movement of the vehicle body 1 and the raising and lowering of the forks 3 by using data from the navigation laser 21, the blind spot laser 40, and the obstacle avoidance laser 5.
[0038] The aforementioned structure deploys various LiDAR sensors and surround-view cameras at different locations on the vehicle body (top rear, sides, bottom rear), top of the mast, and bottom of the forks, constructing a multi-layered, multi-angle sensor network to achieve all-around, blind-spot-free environmental perception. Among them, the navigation laser, located at a high position with a wide field of view, is used for long-distance environmental mapping and global path planning; the blind spot laser and side surround view camera, fill in the blind spots behind and on both sides of the vehicle, especially when reversing or turning, can effectively observe the distance between the vehicle and surrounding obstacles to prevent collisions; the obstacle avoidance laser, located on both sides of the bottom, is specifically used to detect low obstacles to ensure driving safety; the bottom recognition laser and fork end surround view camera, deployed directly at the operation execution end, can accurately identify the position and posture of the cargo pallet and monitor the picking process at close range, which is the foundation for achieving high-precision picking and placing of goods.
[0039] Furthermore, navigation and obstacle avoidance decisions are made by integrating data from multiple LiDAR systems (multi-laser SLAM) via an industrial control computer. The folding cylinders are precisely controlled by hydraulic pumps and solenoid valves to achieve the retraction and extension of the forks, thus constructing a redundant and reliable navigation and control system. Single sensors are prone to failure in feature-scarce environments like containers. Multi-laser SLAM provides data redundancy, enhancing the system's robustness in complex environments. Simultaneously, the close integration of perception, decision-making (industrial control computer), and execution (hydraulic pumps, solenoid valves) forms a complete closed-loop automated operation.
[0040] The fork 3 is equipped with a strike plate 32 for determining whether the goods have been picked up; the fork 3 is also equipped with a micro switch for determining whether the fork is folded or unfolded into place. The aforementioned structure incorporates a strike plate on the forks. When the forks insert into the pallet and the cargo is lifted, the cargo touches and presses against the strike plate. This is a simple and reliable mechanical signal feedback. Compared to relying solely on vision or laser judgment, the strike plate signal provides final confirmation that "the cargo is indeed on the forks," effectively preventing "false pickups" (i.e., the control system believes the cargo has been retrieved, but in reality, the cargo is not securely on the forks) caused by cargo identification errors or pallet deformation, thus providing the most basic safety guarantee for subsequent transportation.
[0041] The aforementioned structure also incorporates microswitches at the folding and unfolding limit positions of the forks, providing precise positioning signals to the control system. After the control system issues a "fold" or "unfold" command, the action is only confirmed as complete upon receiving the corresponding microswitch trigger signal. This avoids incomplete actions caused by hydraulic system delays or mechanical jamming, ensuring that the fork state matches the "virtual state" recorded by the control system—a prerequisite for subsequent safe and precise motion control.
[0042] like Figure 4 and Figure 5 The control method of the box-opening robot shown includes the following steps: Step S1: Data is acquired through navigation laser 21, blind spot laser 40, and obstacle avoidance laser 5. The multi-laser SLAM data is summarized and sent to the industrial control computer. The industrial control computer organizes and summarizes the data and sends it to the upper control system of the unloading truck. The upper control system models the environment, obtains the stacking order of the goods, and initializes the state of the stacking area. In step S2, the upper-level control system calculates and judges the passage area range to determine whether the vehicle body 1 can move to the front of the goods to be stacked. If the passage requirements are met, it moves directly to the front of the goods to be stacked. If the passage area is insufficient, the upper-level software controls the oil pump and solenoid valve of the fork 3 to control the extension and retraction of the folding cylinder 31 of the fork 1 through hydraulic oil, so as to realize the folding and unfolding of the fork 3. When the micro switch on the fork 3 is triggered, it will feed back the positioning signal to the upper-level control system. The upper-level control system controls the fork to be fully folded, thereby reducing the turning radius and adjusting the vehicle body posture in a narrow space. As needed, the upper-level control system queries the data of the top surround view camera 41 and the side surround view camera 42 of the vehicle body 1 to determine the size of the space around the vehicle body 1 to avoid collisions when adjusting the vehicle body posture. Depending on the complexity of the narrow space, the vehicle body posture is adjusted once or multiple times. After finally moving to the front of the goods to be stacked, the upper-level control system controls the fork 3 to unfold to a horizontal position. In step S3, the upper control system activates the bottom recognition laser 22 of the fork 3 to identify the goods to be stacked in front of the fork 3, and controls the fork 3 to rise and move sideways to align with the pallet to pick up the goods. After the goods are picked up, the detection plate of the fork 3 is in the triggered state throughout the loading process. At the same time, the upper control system activates the fork end surround view camera at the bottom of the fork 3 to determine whether the goods have fallen during transportation. If the goods fall, the system immediately stops and notifies the remote end. If the goods do not fall, the goods are transported to the designated location normally.
[0043] In step S1 of the above control method, through high-precision modeling, the system can "understand" its complex environment. By acquiring the stacking sequence of goods and the status of the stacking area, the operation is no longer blind but planned and orderly, providing a global perspective for subsequent path planning and decision-making.
[0044] Step S2 in the aforementioned control method demonstrates a high degree of "intelligence" and "adaptability." The robot's forks actively fold to form an obstacle avoidance strategy. When the robot knows it cannot pass, it can proactively "slim down" to solve the problem. Furthermore, it utilizes multi-sensor fusion monitoring: activating the surround-view camera during posture adjustments provides real-time, close-range collision avoidance protection, ensuring absolute safety during complex maneuvers in extremely confined spaces. In addition, the strategy of single or multiple adjustments simulates the operation of a skilled driver, enabling the robot to handle extremely complex box-entry paths.
[0045] Step S3 in the aforementioned control method utilizes a bottom-mounted laser to directly align with the pallet, overcoming the visual positioning challenges caused by forklift obstruction or poor lighting. This is crucial for achieving unmanned and precise forklift handling. It also provides dual safety assurance: a combination of "pallet impact signal (physical confirmation) + surround-view camera (visual monitoring)," offering double protection for cargo transportation. The pallet impact signal ensures the goods are secure, while the surround-view camera detects potential accidental drops during transport, significantly improving operational safety and reducing the risk of cargo damage and equipment accidents.
[0046] As a preferred embodiment, the specific process of environmental modeling in step S1 is as follows: Step S11 constructs a map of the passable area around the robot based on the data of navigation laser 21, blind spot laser 40, and obstacle avoidance laser 5. This map is usually represented using a grid map or geometric features. Step S12: Determine the target point: Based on the position of the goods to be stacked, calculate the target point that the robot needs to reach, which is usually a certain distance in front of the goods. Step S13 Path Search: Attempt to search for a collision-free path from the current location to the target point in the environment map. If a path can be found, it means that the passable area is sufficient. Step S14: Path Feasibility Verification: Verify whether the searched path can be executed by the robot. If the path exists and is feasible, it is determined that the passage area is sufficient, and the robot can move along the path; otherwise, it is determined that the passage area is insufficient. If the passage area is sufficient, move to the front of the goods according to the normal route.
[0047] The above method details the specific algorithmic logic for "determining whether the passage area is sufficient," transforming the abstract concept of "passage capacity" into a computer-executable process. Its technical advantages are: 1. Transforming qualitative judgment into quantitative calculation: By constructing a map (S11), determining the target point (S12), searching for a path (S13), and verifying feasibility (S14), the ambiguous question of "can we get through?" is transformed into the explicit algorithmic question of "does a collision-free and executable path exist?". This is also the foundation for achieving automatic decision-making in step S2. It enables the robot to self-assess its environmental traversal capabilities and is a core component of achieving autonomous navigation.
[0048] 2. Ensuring the reliability of the decision: Not only is it required to find a path (S13), but also to verify the feasibility of that path (S14). Feasibility verification considers the robot's kinematic constraints (such as minimum turning radius and vehicle width) to ensure that the planned path is not a path that "looks good on the map" but is actually unusable by the robot. This avoids the risk of repeated attempts or collisions due to unfeasible planned paths, improving the success rate and safety of the decision-making process.
[0049] The top surround view camera 41 and the side surround view camera 42 are activated when the vehicle body 1 turns or reverses. The multiple cameras provide multiple image data. The upper control system stitches and merges the multiple image data, and then constructs an environmental map and locates itself based on visual SLAM. The upper control system then controls the movement of the vehicle body through the lower control system to ensure high-precision movement of the vehicle body in narrow environments.
[0050] The surround-view cameras in the above structure are activated only during high-risk maneuvers such as turning and reversing, achieving on-demand activation and reducing system load—a highly efficient resource management strategy. Continuously processing multiple channels of high-definition video data consumes significant computing resources. On-demand activation ensures information is provided only when environmental awareness is most needed, while also reducing the burden on the industrial control computer during stable phases such as straight-line driving, thus improving the overall operating efficiency and stability of the system.
[0051] The aforementioned structure also stitches and fuses images from multiple cameras for visual SLAM, building a map and locating the object, achieving fused visual SLAM and improving positioning accuracy and robustness. Inside a container, a single LiDAR may fail to locate the object due to the inability to scan effective features. In this case, visual SLAM that fuses images from multiple cameras provides a powerful and redundant source of positioning information. Multi-camera stitching and fusion expands the field of view, capturing more environmental features (such as cargo textures, container seams, etc.), enabling high-precision positioning even under varying lighting conditions or poor LiDAR data, ensuring precise, "non-collision-free" movement in confined environments.
[0052] The control process for the folding and unfolding of the forks 3 is as follows: 1. In the fork folding control software, the initial position of fork 3 is horizontally unfolded. Set the folding angle to 0 and insert the initial 0 position in the upper control system. 2. After the navigation laser 21 completes the mapping, the upper control system calculates that the forks need to be folded at this time, and then controls the folding cylinder 31 on the forks 3 to retract; after the forks 3 are folded, the folding limit micro switch is triggered, and the signal is transmitted to the IO module. The upper control system reads the folding signal at this time, controls the folding cylinder 31 to stop retracting, and sets the folding angle at this time to 1. 3. The upper control system calculates that the forks need to be extended. The upper control system controls the extension of the folding cylinder 31. The extension of the forks triggers the extension limit micro switch. The signal is transmitted to the IO module. The upper control system reads the extension signal at this time and controls the folding cylinder 31 to stop extending. The folding angle returns to the horizontal extension position.
[0053] A "folding angle" variable is introduced into the control system, with an initial value set (0 for unfolded). When an action is executed and a corresponding microswitch signal is received, this variable value is updated (1 for folded). This mechanism ensures that the control system's "perception" of the fork's physical state is consistent with the actual situation. Even if the state becomes unknown due to unexpected power outages or human intervention, this process can be used for recalibration. This is a safety prerequisite for any subsequent automated operations.
[0054] Furthermore, issuing the control command (cylinder extension / retraction) is not the end point. Only upon receiving the position feedback signal from the microswitch (transmitted via the I / O module) does the control system confirm the completion of the action and stop the actuator. This is a classic closed-loop control. It overcomes the drawbacks of open-loop control (which ignores input after command issuance), automatically compensating for response delays in the hydraulic system and minor differences in mechanical stroke. This ensures that the forks are precisely folded to the most compact position or extended to a horizontal working position each time, guaranteeing safe and precise operation.
[0055] The calculation process for the obstacle avoidance distance value of the obstacle avoidance radar 5 of the vehicle body 1 during forward movement is as follows: Warning / deceleration distance;
[0056] Slow stopping distance;
[0057] Emergency stopping distance;
[0058] in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
[0059] The calculation process for the obstacle avoidance distance value of the obstacle avoidance radar 5 of the vehicle body 1 during the reversing process is as follows: Warning / deceleration distance;
[0060] Slow stopping distance;
[0061] Emergency stopping distance;
[0062] in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
[0063] The calculation process for the obstacle avoidance distance value of the obstacle avoidance radar 5 of the vehicle body 1 when it is about to reach the destination is as follows: Warning / deceleration distance;
[0064] Slow stopping distance;
[0065] Emergency stopping distance;
[0066] in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
[0067] The above obstacle avoidance distance calculation process is based on a method of dynamically calculating the obstacle avoidance distance at the current speed, realizing a "speed-adaptive" obstacle avoidance strategy. This dynamically adjusts the safety distance, balancing safety and efficiency. The obstacle avoidance distance (warning, slow stop, emergency stop) is no longer a fixed value, but is dynamically calculated based on the current linear velocity v. The faster the speed, the larger the calculated safety distance.
[0068] This is a fundamental requirement for intelligent motion control. Using a fixed safety distance may be too conservative at low speeds, leading to frequent erroneous stops and reduced efficiency; at high speeds, insufficient braking distance may result in collisions. Dynamic calculation perfectly resolves this contradiction: at high speeds, it provides sufficient safety margin to ensure safe braking in front of obstacles; at low speeds, the safety distance automatically shortens, allowing the robot to get closer to the target or obstacle, improving space utilization and operational flexibility.
[0069] The control logic is optimized for different motion states: the same dynamic calculation formula is applied to three different key motion states: "forward," "backward," and "approaching the finish line." This reflects the refinement of the control strategy. When moving backward, the field of vision and operational difficulty are usually greater than when moving forward; applying this formula ensures safety during backward movement. When "approaching the finish line," more precise stopping is often required; dynamically adjusted distance parameters (especially the stopping distance parameter, which can be adjusted according to the scenario) help achieve more accurate final positioning while avoiding the impact of sudden stops caused by speed changes.
[0070] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0071] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention. Any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.
Claims
1. A box-opening robot, comprising a vehicle body (1) and a gantry mechanism (2) disposed at the front end of the vehicle body, wherein the gantry mechanism (2) is further provided with a vertically lifting fork carriage (30), and two forks (3) are spaced apart at the front end of the fork carriage (30), characterized in that, The forks (3) are hinged to the fork carriage (30), and a folding cylinder (31) for driving the forks (3) to fold or unfold is provided between the forks (3) and the fork carriage (30). A blind spot laser (40) and a top surround-view camera (41) are provided at the top of the rear end of the vehicle body (1). Side surround-view cameras (42) are provided on both sides of the vehicle body (1). Obstacle avoidance lasers (5) are provided on both sides of the bottom of the rear end of the vehicle body (1). A navigation laser (21) is provided at the top of the mast mechanism (2). A bottom recognition laser (22) and a fork end surround-view camera are provided at the bottom of the forks (3). An industrial control computer, an oil pump and a solenoid valve are provided on the vehicle body (1). The industrial control computer controls the movement of the vehicle body (1) and the folding and unfolding of the forks (3) by using data from the navigation laser (21), the blind spot laser (40) and the obstacle avoidance laser (5).
2. The box-opening robot according to claim 1, characterized in that, The fork (3) is provided with a strike plate (32) for determining whether the goods have been picked up; the fork (3) is also provided with a micro switch for determining whether the fork is folded or unfolded into place.
3. The control method for a box-opening robot according to claim 2, characterized in that, Includes the following steps: Step S1: Data is acquired through navigation laser (21), blind spot laser (40), and obstacle avoidance laser (5). The multi-laser SLAM data is summarized and sent to the industrial control computer. The industrial control computer organizes and summarizes the data and sends it to the upper control system of the unloading truck. The upper control system models the environment, obtains the stacking order of the goods, and initializes the state of the stacking area. Step S2, the upper control system calculates and judges the range of the passage area, and judges whether the vehicle (1) can move to the front of the goods to be stacked. If the passage requirements are met, it moves directly to the front of the goods to be stacked. If the passage area is insufficient, the upper software controls the oil pump and solenoid valve of the fork (3), and controls the extension and retraction of the folding cylinder (31) of the fork (1) through hydraulic oil to realize the folding and unfolding of the fork (3). When the micro switch on the fork (3) is triggered, it will feed back the positioning signal to the upper control system. The upper control system controls the fork to be fully folded, thereby reducing the turning radius and adjusting the body posture in a narrow space. As needed, the upper control system queries the data of the top surround view camera (41) and the side surround view camera (42) of the vehicle body (1) to determine the size of the space around the vehicle body (1) and avoid collisions when adjusting the body posture. Depending on the complexity of the narrow space, the body posture is adjusted once or multiple times. Finally, after moving to the front of the goods to be stacked, the upper control system controls the fork (3) to unfold to the horizontal. In step S3, the upper control system activates the bottom recognition laser (22) of the fork (3) to identify the goods to be stacked in front of the fork (3), and controls the fork (3) to rise and move to the side to align with the pallet to pick up the goods. After the goods are picked up, the detection plate of the fork (3) is in the triggered state throughout the loading process. At the same time, the upper control system activates the fork end surround view camera at the bottom of the fork (3) to determine whether the goods have fallen during transportation. If the goods fall, the system immediately stops and notifies the remote end. If the goods do not fall, the goods are transported to the designated location normally.
4. The control method for a box-opening robot according to claim 3, characterized in that, The specific process of environmental modeling in step S1 is as follows: Step S11 constructs a map of the passable area around the robot based on the navigation laser (21), blind spot laser (40), and obstacle avoidance laser (5) data, which is usually represented by a grid map or geometric features; Step S12: Determine the target point: Based on the position of the goods to be stacked, calculate the target point that the robot needs to reach, which is usually a certain distance in front of the goods. Step S13 Path Search: Attempt to search for a collision-free path from the current location to the target point in the environment map. If a path can be found, it means that the passable area is sufficient. Step S14: Path Feasibility Verification: Verify whether the searched path can be executed by the robot. If the path exists and is feasible, it is determined that the passage area is sufficient, and the robot can move along the path; otherwise, it is determined that the passage area is insufficient. If the passage area is sufficient, move to the front of the goods according to the normal route.
5. The control method for a box-opening robot according to claim 3, characterized in that, The top surround view camera (41) and the side surround view camera (42) are activated when the vehicle body (1) turns or reverses. The multiple cameras provide multiple image data. The upper control system stitches and merges the multiple image data, and then constructs an environmental map and locates itself based on visual SLAM. The upper control system then controls the movement of the vehicle body through the lower control system to ensure high-precision movement of the vehicle body in a narrow environment.
6. The control method for a box-opening robot according to claim 3, characterized in that, The control process for folding and unfolding the forks (3) is as follows:
1. In the fork folding control software, the initial position of the fork (3) is the horizontal unfolded position. The folding angle is set to 0, and the initial 0 position is inserted in the upper control system.
2. After the navigation laser (21) completes the mapping, the upper control system calculates that the fork needs to be folded at this time, and then controls the folding cylinder (31) on the fork (3) to retract; after the fork (3) is folded, the folding limit micro switch is triggered, the signal is transmitted to the IO module, the upper control system reads the folding signal at this time, controls the folding cylinder (31) to stop retracting, and sets the folding angle at this time to 1; 3. The upper control system calculates the need to unfold the forks. The upper control system controls the extension of the folding cylinder (31). The unfolding of the forks (3) triggers the unfolding limit micro switch. The signal is transmitted to the IO module. The upper control system reads the unfolding signal at this time and controls the folding cylinder (31) to stop extending. The folding angle returns to the horizontal unfolding position.
7. The control method for a box-opening robot according to claim 3, characterized in that, The calculation process of the obstacle avoidance distance value of the obstacle avoidance radar (5) of the vehicle body (1) during the forward movement is as follows: Warning / deceleration distance; Slow stopping distance; Emergency stopping distance; in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
8. The control method for a box-opening robot according to claim 3, characterized in that, The calculation process of the obstacle avoidance distance value of the obstacle avoidance radar (5) of the vehicle body (1) during the reversing process is as follows: Warning / deceleration distance; Slow stopping distance; Emergency stopping distance; in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.
9. The control method for a box-opening robot according to claim 3, characterized in that, The calculation process of the obstacle avoidance distance value of the obstacle avoidance radar (5) of the vehicle body (1) when it is about to reach the destination is as follows: Warning / deceleration distance; Slow stopping distance; Emergency stopping distance; in, This is the current linear velocity; To control the delay time; To reduce speed to avoid obstacles; This is the stopping distance parameter.