Method for preventing AGV from advancing and falling

Abstract

The invention provides a method for preventing an AGV from advancing and falling, and relates to the technical field of AGV equipment, a depth camera is arranged on the AGV, so that the ground on the driving path of the AGV is comprehensively monitored, and the flatness and height change of the ground are determined; the method specifically comprises the following steps: S1, extracting depth data; s2, selecting an ROI (Region of Interest) according to the advancing direction, abandoning data outside the ROI to reduce calculation, and calculating depth gradient change in the ROI; s3, judging whether the gradient value exceeds a set threshold value or not so as to determine whether the road surface is abnormal or not in the advancing direction; and S4, after the deceleration obstacle avoidance function is triggered, whether deceleration and obstacle avoidance distances are enough is judged. The system has the beneficial effects that the problem that the risk of accidents is increased due to the fact that the AGV cannot detect abnormal conditions of some areas in time in the driving process due to the fact that a certain dead angle often exists when a traditional sensor is used for detecting the environment is solved, and the purposes of observing and covering wider areas and reducing detection blind areas are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of AGV equipment application, and in particular to a method for preventing an AGV from falling while advancing. Background Art

[0002] In the manufacturing industry, as the scale of production expands and the complexity of products increases, higher requirements are placed on the efficiency, accuracy and stability of material handling. Traditional manual handling methods are labor-intensive, error-prone, and inefficient, and cannot meet the pace of modern production, prompting companies to seek automated handling solutions. Unmanned automatic transport vehicles can achieve 24-hour uninterrupted work and greatly improve production efficiency.

[0003] For example, in the automobile manufacturing industry, unmanned automated transport vehicles can accurately transport parts from the warehouse to the production line, ensuring the continuous operation of the production line and improving production efficiency and product quality. However, existing AGVs face the following difficulties when applied: Uneven ground or potholes: If the ground on which the AGV is traveling has large height differences or potholes, the AGV may lose balance and fall during its forward movement. This risk is particularly high when traveling at high speeds or carrying heavy cargo.

[0004] Ground material problem: Some ground materials may be too smooth, such as tiles, marble, etc., or there may be oil stains, water stains, etc. on the ground, which will reduce the friction between the AGV wheels and the ground, making the AGV easy to slip out of control and fall.

[0005] Obstacle interference: Obstacles that suddenly appear on the driving path, such as fallen objects, temporarily stacked goods, etc., may hit the obstacles and fall if the AGV fails to detect and avoid them in time.

[0006] Sensor failure: AGVs are usually equipped with a variety of sensors to sense the surrounding environment and their own status. If a sensor fails, such as a laser sensor that cannot accurately measure distance or a collision sensor that fails, the AGV may not be able to correctly judge the surrounding environment, resulting in a fall accident.

[0007] Drive system failure: Failure of drive components such as motors and reducers may cause the AGV to lose power or unstable power, affecting its driving control and causing it to fall. For example, if the motor suddenly stops working or the output power fluctuates abnormally, the AGV may lose balance while driving.

[0008] Control system failure: The AGV's control system is responsible for key functions such as path planning and motion control. If the control system has problems such as software errors, hardware failures, or communication interruptions, the AGV may not be able to drive normally, or even make erroneous movements and fall.

[0009] Based on this, the present invention provides a method for preventing an AGV from falling while moving forward, thereby solving the problem that a general optical sensor cannot identify whether the floor is abnormal due to blind angle illumination, causing the vehicle body to fall. Summary of the invention

[0010] The present invention overcomes the shortcomings of the prior art, provides a method for preventing AGVs from falling while moving forward, and solves the problem that traditional sensors often have certain blind spots when detecting the environment, which may cause the AGV to be unable to detect abnormal conditions in certain areas in time during driving, thereby increasing the risk of accidents. The method achieves observation coverage of a wider area and reduces the number of detection blind spots.

[0011] In order to solve the above technical problems, the present invention is achieved through the following technical solutions: A method for preventing an AGV from falling forward is to set a depth camera on the AGV to comprehensively monitor the ground along its driving path to determine the flatness and height changes of the ground; specifically, the method includes the following: S1, extract depth data; S2, select ROI according to the direction of travel, discard data outside the ROI to reduce calculation, and calculate the depth gradient change within the ROI; S3. Determine whether the gradient value exceeds the set threshold to determine whether there is any road abnormality in the direction of travel: a) If there is no abnormality on the road surface, re-capture the depth data; b) If the road surface is abnormal, the deceleration and obstacle avoidance function will be triggered; S4: After triggering the deceleration and obstacle avoidance function, determine whether the deceleration and obstacle avoidance distance are sufficient: a) If the distance is sufficient, re-capture the depth data; b) If the distance is insufficient, an emergency stop is triggered.

[0012] Furthermore, the depth cameras are arranged on the front and rear sides of the AGV to detect the moving direction of the AGV.

[0013] Furthermore, the depth camera may be equipped with a function of dynamically adjusting the detection area so as to adjust the monitoring range of the depth camera in real time according to the driving status of the AGV, task requirements, and changes in the surrounding environment.

[0014] Furthermore, the depth camera transmits a specific signal and receives a reflected signal, so as to obtain depth information of objects in the scene, thereby achieving three-dimensional perception of the surrounding environment.

[0015] Furthermore, the emitted specific signal is infrared light or structured light.

[0016] Compared with the prior art, the present invention has the following beneficial effects: It solves the problem that traditional sensors often have certain blind spots when detecting the environment, which may cause the AGV to be unable to detect abnormal conditions in certain areas in time during driving, thereby increasing the risk of accidents; the use of depth cameras can effectively reduce the blind spots of sensors; depth cameras can obtain depth information of objects in the scene by emitting specific signals and receiving reflected signals, thereby realizing three-dimensional perception of the surrounding environment; this three-dimensional perception capability enables depth cameras to cover a wider area and reduce detection blind spots. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and are used together with the embodiments of the present invention to explain the present invention, but do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a schematic diagram of the method to prevent the AGV from falling forward; Figure 2 This is a schematic diagram of the depth camera detecting the front and rear sides of the AGV from the front view direction; Figure 3 This is a schematic diagram of the depth camera detecting the front and rear sides of the AGV from a top-down perspective; Figure 4 is a general road depth data line map; h is the camera height, w is the distance between the depth data and the vehicle body, and d is the depth data; Figure 5 is the depth data route map of the bumpy road surface; h is the camera height, w is the distance between the depth data and the vehicle body, and d is the depth data; Figure 6 It is the depth data route diagram of the sunken road surface; h is the camera height, w is the distance between the depth data and the vehicle body, and d is the depth data. DETAILED DESCRIPTION

[0018] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0019] like Figures 1 to 6 As shown, the present invention provides a method for preventing an AGV from falling forward, by creatively setting a depth camera on the AGV so as to comprehensively monitor the ground on its driving path to determine the flatness and height changes of the ground; the depth camera has the following capabilities: 1. Application of Depth Camera in Plane Coverage A depth camera is a device that can obtain depth information of objects in a scene. By using a depth camera, effective monitoring of a larger plane coverage area can be achieved. Compared with traditional cameras, depth cameras can not only provide two-dimensional image information, but also accurately measure the distance between the object and the camera, thereby constructing a three-dimensional scene model.

[0020] In AGV applications, depth cameras can be installed at specific locations on the transporter, such as the bottom or front, to fully monitor the ground along its travel path. By analyzing the depth image, the flatness and height changes of the ground can be quickly determined, providing an important basis for the safe travel of the AGV.

[0021] 2. Ability to detect ground anomalies at the square centimeter level Depth cameras have high-precision measurement capabilities and can detect ground anomalies at the square centimeter level. This means that even very small ground defects, such as small potholes, cracks, and bumps, can be discovered in a timely manner. This high-resolution detection capability is crucial for the safe operation of AGVs.

[0022] For example, in some production environments that require high ground flatness, such as electronic chip manufacturing workshops, even small ground unevenness may affect the handling accuracy and stability of the AGV. Depth cameras can accurately detect these tiny anomalies, allowing the AGV to take corresponding avoidance measures in advance to avoid accidents caused by ground anomalies.

[0023] 3. Advantages of Dynamically Adjusting the Detection Area In order to further improve the efficiency and accuracy of detection, the depth camera can be equipped with the function of dynamically adjusting the detection area. Dynamically adjusting the detection area means adjusting the monitoring range of the depth camera in real time according to the driving status of the AGV, task requirements and changes in the surrounding environment.

[0024] For example, when the AGV is driving in a straight line, the detection area can be concentrated on the ground at a long distance ahead to detect potential dangers in advance. When the AGV is turning or driving in a narrow space, the detection area can be expanded to the side and rear to ensure all-round safety monitoring.

[0025] In addition, the dynamic adjustment of the detection area can also be optimized according to different ground materials and environmental conditions. For example, on smooth ground, the detection area can be appropriately reduced to reduce false alarms; on rough ground, the detection area can be expanded to improve the ability to detect potential dangers.

[0026] Combining the above functions of the depth camera, the specific operation method of installing the depth camera on the AGV is as follows: S1, extract depth data; S2, select ROI according to the direction of travel, discard data outside the ROI to reduce calculation, and calculate the depth gradient change within the ROI; S3. Determine whether the gradient value exceeds the set threshold to determine whether there is any road abnormality in the direction of travel: a) If there is no abnormality on the road surface, re-capture the depth data; b) If the road surface is abnormal, the deceleration and obstacle avoidance function will be triggered; S4: After triggering the deceleration and obstacle avoidance function, determine whether the deceleration and obstacle avoidance distance are sufficient: a) If the distance is sufficient, re-capture the depth data; b) If the distance is insufficient, an emergency stop is triggered.

[0027] like Figure 2 As shown, the depth cameras are set on the front and rear sides of the AGV to detect the direction of movement of the AGV, so as to make specific detection of the situation on the way forward.

[0028] The depth camera can be equipped with the function of dynamically adjusting the detection area to adjust the monitoring range of the depth camera in real time according to the driving status of the AGV, task requirements and changes in the surrounding environment; and the depth camera emits specific signals and receives reflected signals, so as to obtain the depth information of objects in the scene, thereby realizing three-dimensional perception of the surrounding environment; the specific signal emitted is infrared light or structured light.

[0029] Figures 4 to 6 In the equation, h is the camera height, w is the distance between the depth data and the vehicle body, and d is the depth data; Figure 4 It is a general road depth data route map. The depth data increases slowly along the illumination angle, but the change is very small, which means that the road surface is relatively flat. Figure 5 When encountering a raised road surface depth data line map, the depth data suddenly shortens and the depth gradient reverses, which means there is a raised obstacle on the road surface; Figure 6 It is the depth data route map for a sunken road surface. The depth data suddenly increases significantly; and when the gradient exceeds the set threshold, it means that a sunken road surface is encountered.

[0030] AGV refers to unmanned automated guided vehicles. Traditional sensors often have certain blind spots when detecting the environment, which may cause the AGV to be unable to detect abnormal conditions in certain areas in time during driving, thereby increasing the risk of accidents. The use of depth cameras can effectively reduce sensor blind spots. Depth cameras can obtain depth information of objects in the scene by emitting specific signals (such as infrared light, structured light, etc.) and receiving reflected signals, thereby achieving three-dimensional perception of the surrounding environment. This three-dimensional perception capability enables depth cameras to cover a wider area and reduce detection blind spots.

[0031] At the same time, the depth camera also has a high sensing resolution. It can accurately measure the distance between the object and the camera, and can distinguish small depth changes. This allows the AGV to more accurately perceive the ground conditions and promptly detect subtle ground anomalies such as small potholes, cracks, and bumps. High sensing resolution can also improve the positioning accuracy and navigation accuracy of the AGV, allowing it to travel more stably in complex environments.

[0032] The technical features of reducing sensor blind spots and improving sensing resolution have brought many improvements to the performance of AGV. First, the safety of AGV is enhanced. By more comprehensively sensing the surrounding environment, AGV can avoid abnormal areas on the ground in time to avoid equipment damage and cargo loss caused by collision or fall. Second, the work efficiency of AGV is improved. Accurate ground perception enables AGV to choose the optimal driving path, reduce unnecessary detours and pauses, and thus speed up the completion of handling tasks. In addition, high sensing resolution can also provide more abundant information for the intelligent control of AGV, enabling it to adjust the driving speed and movement according to different ground conditions, further improving the stability and reliability of operation.

[0033] The advantage of being able to modify the judgment range according to the direction of travel provides great flexibility for AGV. In different work scenarios, the direction of travel of the AGV may change constantly, and the corresponding ground anomaly detection needs will also change accordingly. For example, when the AGV is traveling in a straight line, it may need to focus on the ground area far ahead; when the AGV is turning, it needs to focus on the ground on the side of the turning direction. By modifying the judgment range according to the direction of travel, the AGV can dynamically adjust the sensor's detection range according to the actual situation, ensuring that ground anomalies related to the current direction of travel can always be accurately detected.

[0034] This flexibility can also improve the adaptability of AGVs. In complex and changing working environments, AGVs may encounter a variety of different terrains and obstacles. By flexibly adjusting the judgment range, AGVs can better adapt to different environmental conditions and improve their operational reliability in various scenarios.

[0035] The advantage of dynamically adjusting the judgment range is that it can optimize the AGV's ground anomaly detection capability in real time according to actual conditions. Dynamic adjustment can be based on a variety of factors, such as the AGV's driving speed, load conditions, ambient light conditions, etc. For example, when the AGV is driving at a higher speed, the judgment range can be appropriately expanded to detect potential ground anomalies in advance; and when the AGV is carrying heavier cargo, the judgment range can be concentrated on the ground area close to the wheels to ensure timely detection of ground anomalies that may affect driving stability.

[0036] In addition, dynamically adjusting the judgment range can also work in conjunction with other sensors and control systems. For example, when the AGV's navigation system detects an obstacle ahead, it can automatically adjust the depth camera's judgment range to strengthen the detection of the ground around the obstacle in order to better plan a detour. This collaborative work can improve the overall performance and intelligence level of the AGV, enabling it to complete various handling tasks more efficiently.

[0037] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. However, any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for preventing an AGV from falling forward, characterized in that: By setting up a depth camera on the AGV, the ground along its driving path can be fully monitored to determine the flatness and height changes of the ground; specifically, the following are included: S1, extract depth data; S2, select ROI according to the direction of travel, discard data outside the ROI to reduce calculation, and calculate the depth gradient change within the ROI; S3. Determine whether the gradient value exceeds the set threshold to determine whether there is any road abnormality in the direction of travel: a) If there is no abnormality on the road surface, re-capture the depth data; b) If the road surface is abnormal, the deceleration and obstacle avoidance function will be triggered; S4: After triggering the deceleration and obstacle avoidance function, determine whether the deceleration and obstacle avoidance distance are sufficient: a) If the distance is sufficient, re-capture the depth data; b) If the distance is insufficient, an emergency stop is triggered.

2. The method for preventing an AGV from falling forward according to claim 1, characterized in that: The depth cameras are arranged on the front and rear sides of the AGV to detect the moving direction of the AGV.

3. The method for preventing an AGV from falling forward according to claim 2, characterized in that: The depth camera can be equipped with a function of dynamically adjusting the detection area to adjust the monitoring range of the depth camera in real time according to the driving status of the AGV, task requirements and changes in the surrounding environment.

4. The method for preventing an AGV from falling forward according to claim 3, characterized in that: The depth camera transmits a specific signal and receives a reflected signal, so as to obtain the depth information of objects in the scene, thereby achieving three-dimensional perception of the surrounding environment.

5. The method for preventing an AGV from falling forward according to claim 4, characterized in that: The specific emitted signal is infrared light or structured light.

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