A cargo state perception and anti-collision system and method based on radar wave detection

Abstract

This invention relates to the field of radio detection technology, and in particular to a cargo status perception and collision avoidance system and method based on radar wave detection. The system includes a radar detection module that uses millimeter-wave radar to acquire external distance information between the containerized cargo and the hatch, as well as information on the distribution status of the cargo inside the container. A control module, connected to the radar detection module, is configured to determine the degree of off-center loading risk based on the distribution status information of the cargo inside the container. This allows the system to move beyond simply relying on external distance for fixed-threshold collision avoidance decisions. Instead, it first identifies the degree of off-center loading risk inside the cargo, then calculates the basic collision risk by combining external distance information and real-time motion parameters. An off-center loading correction factor is used to correct the safety distance threshold, the permissible transmission speed threshold, or the collision risk coefficient, enabling the off-center loading state to directly participate in collision avoidance decisions. This allows for increased control intervention when the off-center loading risk is high, reducing the risk of collision, slippage, or overturning.

Description

Technical Field

[0001] This invention relates to the field of radio detection technology, and in particular to a cargo status perception and collision avoidance system and method based on radar wave detection. Background Technology

[0002] Civil aviation container cargo loaders (hereinafter referred to as "loaders") are key ground equipment used at airports to transfer cargo from pallets or containers to the aircraft cargo hold. During loading operations, operators control the lifting and transporting of the loader's bridge platform to smoothly deliver the container cargo into the aircraft hold.

[0003] Existing collision avoidance systems for civil aviation container cargo loaders typically only detect the distance between the cargo's outer contour and the hatch using laser or vision sensors. They cannot obtain the distribution of cargo inside the container, thus failing to identify off-center loading risks. Their collision avoidance decisions often rely on fixed distance thresholds, failing to combine real-time cargo motion parameters to calculate collision risks or dynamically adjust collision avoidance sensitivity based on internal off-center loading conditions. This results in insufficient protection under off-center loading conditions or frequent false stops under normal conditions. Furthermore, the lack of a tiered control strategy makes it difficult to balance safety and efficiency.

[0004] Therefore, a cargo state perception and collision avoidance system and method based on radar wave detection is proposed. Summary of the Invention

[0005] In this section, as well as in the abstract and title of this application, some simplifications or omissions may be made to avoid obscuring the purpose of this section, the abstract, and the title of this application, and such simplifications or omissions shall not be used to limit the scope of the invention.

[0006] To address the shortcomings of existing technologies, one objective of this invention is to provide a cargo status perception and collision avoidance system based on radar wave detection.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: a cargo status perception and collision avoidance system based on radar wave detection, comprising a radar detection module, which acquires external distance information between the containerized cargo and the hatch, and distribution status information of the cargo inside the containerized cargo, respectively, through millimeter-wave radar; a control module, connected to the radar detection module, configured to: determine the degree of off-center loading risk based on the distribution status information of the cargo inside; calculate the basic collision risk based on the external distance information and the real-time motion parameters of the cargo; when the degree of off-center loading risk is greater than a preset off-center loading threshold, generate an off-center loading correction factor based on the degree of off-center loading risk, and use the off-center loading correction factor to correct at least one of the safety distance threshold, the allowable transmission speed threshold, or the collision risk coefficient in the basic collision risk, so as to obtain a corrected collision risk level; output a graded control command (202) based on the corrected collision risk level, and send the graded control command to the transmission motor controller of the loader to adjust the transmission speed of the cargo or perform braking.

[0008] As a preferred embodiment of the cargo status perception and collision avoidance system based on radar wave detection described in this invention, the millimeter-wave radar is configured to switch working modes, acquiring external distance information in external ranging mode and acquiring the distribution status information of internal cargo in penetrating imaging mode; wherein the signal frequency of the penetrating imaging mode is configured to be able to penetrate the non-metallic container wall.

[0009] As a preferred embodiment of the radar wave detection-based cargo status perception and collision avoidance system of the present invention, the control module is configured to generate a three-dimensional distribution image of the container cargo based on the penetrating echo signal received by the millimeter-wave radar, and identify off-center loading risks based on the positional offset, center of gravity offset, or distribution symmetry of the cargo.

[0010] As a preferred embodiment of the radar wave detection-based cargo status perception and collision avoidance system of the present invention, the control module is configured to generate an off-center load correction factor according to the degree of off-center load risk, and to use the off-center load correction factor to correct the basic collision risk in at least one of the following ways: when correcting the safety distance threshold, the corrected safety distance threshold increases with the increase of the degree of off-center load risk; when correcting the permissible transmission speed threshold, the corrected permissible transmission speed threshold decreases with the increase of the degree of off-center load risk; when correcting the collision risk coefficient, the off-center load correction factor is introduced as a multiplicative factor or an additive weighting term into the calculation of the collision risk coefficient, so that the corrected collision risk coefficient increases with the increase of the degree of off-center load risk.

[0011] As a preferred embodiment of the radar wave detection-based cargo status perception and collision avoidance system of the present invention, the graded control commands include: a first-level command: normal transmission, corresponding to a corrected collision risk level lower than a first threshold; a second-level command: decelerating to a first safe speed range and issuing a warning, corresponding to a corrected collision risk level between the first and second thresholds; a third-level command: decelerating to a second safe speed range and issuing an audible and visual alarm, corresponding to a corrected collision risk level between the second and third thresholds, wherein the upper limit of the second safe speed range is lower than the lower limit of the first safe speed range; and a fourth-level command: immediately stopping transmission and issuing an emergency alarm, corresponding to a corrected collision risk level higher than the third threshold.

[0012] As a preferred embodiment of the radar wave detection-based cargo state perception and collision avoidance system of the present invention, the real-time motion parameters include the instantaneous velocity of the cargo; the control module is configured to calculate the basic inertial sliding distance S1 under the current motion state based on the instantaneous velocity v of the cargo, the friction coefficient μ between the transmission surface and the cargo, and the gravitational acceleration g; wherein, S1 = v² / (2μg); the control module calculates the basic collision risk based on the comparison result of the basic inertial sliding distance S1 and the external distance information d; when the off-center load risk level is greater than the preset off-center load threshold, the control module uses the off-center load risk level as the off-center load variable L, and calculates the corrected inertial sliding distance S2 according to S2 = S1 × (1 + α·L); wherein, α is a preset redundancy correction coefficient; the control module determines the corrected collision risk level based on the comparison result of the corrected inertial sliding distance S2 and the external distance information d.

[0013] As a preferred embodiment of the radar wave detection-based cargo status perception and collision avoidance system of the present invention, wherein: the radar detection module further includes an environmental sensor group, the environmental sensor group including at least one of a light sensor, a rain sensor, and an electromagnetic interference detection module; when the radar detection module includes a lidar for distance detection, the control module is configured to, based on the detection result of the light sensor, reduce the weight of the lidar in distance detection and increase the weight of the millimeter-wave radar in distance detection when the light intensity exceeds a preset value; the control module is further configured to, based on the detection result of the rain sensor, increase the weight of the millimeter-wave radar in distance detection when rainfall or humidity exceeds a preset value; the control module is further configured to, based on the detection result of the electromagnetic interference detection module, trigger the millimeter-wave radar to switch from a first operating frequency to a second operating frequency when abnormal electromagnetic interference is detected.

[0014] As a preferred embodiment of the radar wave detection-based cargo status perception and collision avoidance system of the present invention, the control module is further configured to: record external distance information, internal cargo distribution status information, real-time motion parameters, off-center load risk judgment results, collision risk calculation results, and the final output hierarchical control commands during each transmission process; update the friction coefficient μ, redundancy correction coefficient α, or risk threshold in the collision risk calculation model according to the recorded data; when multiple false alarms or missed alarms occur consecutively in the same loading scenario, automatically trigger the recalibration of the model parameters, so that the system enters the calibration mode, controls the loader to transmit standard mass cargo at a preset speed, measures the actual sliding distance, and performs stepwise correction on the friction coefficient μ, redundancy correction coefficient α, or risk threshold according to the deviation between the actual sliding distance and the ideal inertial sliding distance.

[0015] As a preferred embodiment of the radar wave detection-based cargo status perception and collision avoidance system of the present invention, the control module is further configured to: predict the movement trajectory of the cargo within a future time window by continuously detecting the external distance information acquired by the radar detection module; when the deviation between the predicted movement trajectory and the preset safe transmission path exceeds a threshold, output a deceleration or stop command in advance before the cargo actually reaches the dangerous position.

[0016] The beneficial effects of the radar-based cargo status perception and collision avoidance system of the present invention are as follows: By simultaneously acquiring external distance information between the containerized cargo and the hatch, as well as the distribution status information of the cargo inside the containerized cargo, through millimeter-wave radar, the system no longer relies solely on fixed threshold collision avoidance judgments based on external distance. Instead, it can quantify the positional deviation, center of gravity deviation, or asymmetrical distribution of the internal cargo into the degree of off-center loading risk, and further incorporate this degree of off-center loading risk into the basic collision risk calculation. In particular, after calculating the basic inertial sliding distance, the control module converts the off-center loading risk into a control correction amount in the corrected inertial sliding distance, safety distance threshold, allowable transmission speed threshold, or collision risk coefficient through an off-center loading correction factor. This creates a linkage between the internal off-center loading state and external distance, instantaneous speed, and braking response. The system can proactively increase the degree of control intervention for potential sideslip, deflection, or inertial delay that may occur during braking of off-center cargo, rather than simply issuing a separate alarm after detecting off-center loading. At the same time, it reduces unnecessary deceleration or emergency stops when the off-center loading risk is low, and achieves a step-by-step response of normal transmission, deceleration, alarm, or stop through hierarchical control commands, thereby balancing the safety and continuity of loading operations.

[0017] To address the shortcomings of existing technologies, another objective of this invention is to provide a cargo status perception and collision avoidance method based on radar wave detection.

[0018] To achieve the above objectives, the present invention adopts the following technical solution: a cargo state perception and collision avoidance method based on radar wave detection, employing the aforementioned cargo state perception and collision avoidance system based on radar wave detection, and operating according to the following steps: acquiring external distance information between the containerized cargo and the hatch, and the distribution state information of the cargo inside the containerized cargo using millimeter-wave radar; determining the degree of off-center loading risk based on the distribution state information of the internal cargo; calculating the basic collision risk based on the external distance information and the real-time motion parameters of the cargo; when the degree of off-center loading risk is greater than a preset off-center loading threshold, generating an off-center loading correction factor based on the degree of off-center loading risk, and using the off-center loading correction factor to correct at least one of the safety distance threshold, the allowable transmission speed threshold, or the collision risk coefficient in the basic collision risk, to obtain a corrected collision risk level; and outputting a graded control command based on the corrected collision risk level.

[0019] The beneficial effects of the cargo status perception and collision avoidance method based on radar wave detection of the present invention are the same as those of the cargo status perception and collision avoidance system based on radar wave detection, and will not be repeated here. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a partial schematic diagram of the system of the present invention.

[0022] Figure 2 This is a flowchart of the overall system of the present invention.

[0023] Figure 3 This is a schematic diagram illustrating the relationship between the degree of off-center load risk and the correction of inertial sliding distance in this invention.

[0024] In the diagram: 100, Radar detection module; 101, Millimeter-wave radar; 102, Environmental sensor group; 200, Control module; 201, Off-center load correction factor; 202, Hierarchical control command. Detailed Implementation

[0025] To make the objectives, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0026] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0027] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0028] Reference Figure 1 This embodiment provides a cargo status perception and collision avoidance system based on radar wave detection, including: a radar detection module 100 acquiring external distance information between the containerized cargo and the hatch via a millimeter-wave radar 101, and acquiring information on the distribution status of the cargo inside the containerized cargo. The external distance information is used to reflect the proximity of the containerized cargo to the hatch, and the information on the distribution status of the cargo inside the containerized cargo is used to reflect whether there are conditions such as uneven loading, tilting, concentrated gaps, or uneven distribution inside the containerized cargo.

[0029] The control module 200 is connected to the radar detection module 100 and is used to receive external distance information and internal cargo distribution status information. The control module 200 determines the degree of off-center loading risk based on the internal cargo distribution status information and calculates the basic collision risk based on the external distance information and the real-time motion parameters of the cargo. The real-time motion parameters may include at least one of the cargo's speed, acceleration, mass, or transport status.

[0030] When the off-center load risk level exceeds the preset off-center load threshold, the control module 200 does not treat the off-center load risk as an independent alarm condition. Instead, it generates an off-center load correction factor 201 based on the off-center load risk level and uses this correction factor 201 as correction information in the collision risk calculation. Specifically, the control module 200 uses the off-center load correction factor 201 to correct at least one of the following in the basic collision risk calculation: the safe distance threshold, the allowable transmission speed threshold, or the collision risk coefficient. This ensures that, under the same external distance and the same real-time motion parameters, a higher off-center load risk level results in a higher corrected collision risk level.

[0031] The control module 200 outputs a graded control command 202 based on the revised collision risk level. The graded control command 202 may include at least one of normal transmission, reduced transmission speed, early warning alarm, or stop transmission.

[0032] Therefore, the system can increase the intervention level of collision avoidance control in advance when there is a risk of off-center loading inside the cargo, and reduce unnecessary stops when there is no off-center loading or the risk of off-center loading is low, thus taking into account both loading safety and operational continuity.

[0033] With the above settings, this embodiment does not simply make a fixed threshold collision avoidance judgment based on the external distance between the containerized cargo and the hatch, but further combines the distribution state of the cargo inside the containerized cargo, so that the off-center load risk is included in the collision risk calculation. As a result, the control module can adjust the collision risk level according to the internal off-center load state when the external distance is the same, and realize the step-by-step control of normal transmission, reduced speed transmission and stopped transmission through graded control commands.

[0034] Furthermore, the radar detection module 100 includes a millimeter-wave radar 101, which is configured to switch operating modes: acquiring external distance information in an external ranging mode and acquiring internal cargo distribution information in a penetration imaging mode. The signal frequency of the penetration imaging mode is configured to penetrate the non-metallic container wall. Specifically, the operating modes are as follows: External ranging mode: The radar transmits signals with normal power and waveform. By measuring the time difference (or frequency difference, such as in FMCW system) between the transmitted and received echoes, the precise distance between the front of the cargo and the radar is calculated. This mode is mainly used to acquire external distance information.

[0035] Penetration Imaging Mode: The radar switches to signal parameters with stronger penetration capabilities, such as increasing transmission power and selecting a center frequency more suitable for penetrating non-metallic materials (e.g., 77GHz or 140GHz). In this mode, millimeter-wave signals can penetrate common container wall materials such as cardboard, plastic, and composite panels, illuminating the surface of the internal cargo and generating echoes. The radar receives the penetration echoes and reconstructs a three-dimensional structural image of the cargo's interior using imaging algorithms (e.g., synthetic aperture radar SAR imaging, inverse projection imaging, etc.), thereby obtaining information on the distribution of the internal cargo.

[0036] The two modes are switched in a time-division manner. Specifically, when the cargo is far from the hatch and has not yet entered the close-range collision avoidance control zone, the millimeter-wave radar 101 increases the workload of the penetration imaging mode within a detection cycle to obtain information on the distribution of cargo inside the container and to determine the degree of off-center loading risk. When the cargo approaches the hatch and enters the close-range collision avoidance control zone, the millimeter-wave radar 101 increases the workload of the external ranging mode, and pauses the penetration imaging mode if necessary to increase the refresh frequency of external distance information. The close-range collision avoidance control zone can be preset according to the loader model, transmission speed, and braking response time.

[0037] By switching between external ranging mode and penetration imaging mode using the same millimeter-wave radar 101, the installation space required for separately arranging ranging sensors and penetration detection sensors can be reduced, and the complexity of synchronous processing between the two types of detection data can be decreased. Simultaneously, the penetration imaging mode can be used to acquire the internal cargo distribution status behind the non-metallic container walls, supplementing the limitations of optical sensors in obtaining internal state information.

[0038] Among them, the millimeter-wave radar 101 is a radar that uses the millimeter-wave frequency band (usually 30GHz~300GHz) for detection. Compared with lidar, millimeter waves have the ability to penetrate fog, smoke and dust, and have a certain degree of penetration into non-metallic materials.

[0039] Reference Figures 1-3 The control module 200 is configured to generate a three-dimensional distribution image of the container cargo based on the penetration echo signal received by the millimeter-wave radar 101, and identify off-center loading risks based on the positional offset, center of gravity offset, or distribution symmetry of the cargo.

[0040] The control module 200 performs imaging processing on the penetration echo signal. Specifically, in penetration imaging mode, the millimeter-wave radar 101 typically needs to move along the scanning direction (e.g., as the loader bridge platform moves forward, the radar moves relative to the cargo). Azimuth resolution is obtained through synthetic aperture technology. The control module 200 collects echo data from multiple locations and reconstructs a three-dimensional image of the cargo's interior using back projection algorithm (BPA), range-Doppler algorithm (RDA), or compressed sensing algorithm. Each voxel (three-dimensional pixel) in this image corresponds to a dielectric constant value. Because different materials (cargo, air, packaging materials) have different dielectric constants, the image can distinguish the boundaries between cargo and voids, and between cargo of different densities.

[0041] Secondly, the control module 200 extracts off-center related features from the 3D image: Position offset: Calculate the position of the overall center of gravity of the cargo relative to the geometric center of the container. If the center of gravity deviates from the center by more than a preset threshold (e.g., more than 10% offset along the transmission direction, or more than 5% lateral offset), it is judged as an off-center load risk.

[0042] Center of gravity shift: The position of the cargo's center of gravity in the vertical and horizontal directions is calculated using the density distribution in the 3D image. If the center of gravity is too high (making it easy to tip over) or the lateral shift is too large, it is considered a risk.

[0043] Distribution symmetry: Divide the 3D image into left and right halves or front and back halves, and compare the volume, density integral, or mass estimates of the two halves. If the asymmetry exceeds a threshold (e.g., one side has 20% more mass than the other side), it is considered to be at risk of off-center loading.

[0044] The control module 200 ultimately outputs a value indicating the degree of off-center load risk (such as 0~100% or a grade label) for subsequent adjustment of collision sensitivity.

[0045] By performing three-dimensional imaging on the transmitted echo signal and further extracting features such as position offset, center of gravity offset, and distribution symmetry, the control module 200 can convert the internal cargo distribution state into an off-center load risk level that can be used for subsequent risk calculation, thereby providing quantitative input for the correction of the safe distance threshold, the allowable transmission speed threshold, or the collision risk coefficient.

[0046] Reference Figure 1 and Figure 2 The control module 200 generates an off-center load correction factor 201 based on the degree of off-center load risk, and uses the off-center load correction factor 201 to correct the basic collision risk. The off-center load correction factor 201 can be used to correct at least one of the following: a safe distance threshold, a permissible transmission speed threshold, or a collision risk coefficient.

[0047] In one implementation, the off-center load correction factor 201 is used to correct the safety distance threshold. The safety distance threshold refers to the distance boundary at which the system determines that the cargo is approaching a dangerous area and triggers an alarm, deceleration, or stop control. For example, when the off-center load risk level does not exceed the preset off-center load threshold, the basic safety distance threshold corresponding to the stop control can be set to 30cm. When the off-center load risk level is 50%, the control module 200 can increase the corrected safety distance threshold to 40cm, and when the off-center load risk level is 80%, the control module 200 can increase the corrected safety distance threshold to 50cm. The correspondence between the safety distance threshold and the off-center load risk level can be determined using a linear function, a piecewise function, or a lookup table. By increasing the corrected safety distance threshold as the off-center load risk level increases, the system can trigger deceleration or stop control earlier at a position where the cargo is farther from the hatch, thereby reserving a larger safety margin for the off-center cargo that may slip, deflect, or overturn during braking.

[0048] In another implementation, the off-center load correction factor 201 is used to correct the permissible transfer speed threshold. When the off-center load risk level does not exceed the preset off-center load threshold, the system allows the loader to transfer goods at a higher speed; when the off-center load risk level is greater than the preset off-center load threshold, the control module 200 reduces the permissible transfer speed threshold according to the off-center load risk level and limits the maximum speed of the transfer motor. For example, the basic permissible transfer speed threshold can be 0.5 m / s, and when the off-center load risk level increases, the corrected permissible transfer speed threshold can be reduced to 0.2 m / s. By making the corrected permissible transfer speed threshold decrease with the increase of the off-center load risk level, the inertial impact of off-center loaded goods during emergency braking can be reduced, and a longer reaction time can be provided for the operator.

[0049] In another implementation, the off-center load correction factor 201 is used to correct the collision risk coefficient. The control module 200 can introduce the off-center load correction factor 201 as a multiplicative factor or an additive weighting term in the calculation of the basic collision risk coefficient. For example, the basic collision risk coefficient can be expressed as R1=f(d, v, a, m, μ), where d is the external distance information, v is the instantaneous velocity, a is the instantaneous acceleration, m is the cargo mass, and μ is the friction coefficient. The corrected collision risk coefficient can be expressed as R2=R1×(1+k·L), where R1 is the basic collision risk coefficient, R2 is the corrected collision risk coefficient, L is the degree of off-center load risk, and k is a preset amplification factor. The degree of off-center load risk L can be expressed as a percentage from 0 to 100%, or it can be normalized to a value between 0 and 1. When L is expressed as a percentage, the control module 200 converts it to a normalized value before calculation. The preset amplification factor k can be pre-calibrated according to the loader's braking response time, the friction state of the transmission surface, and the cargo type.

[0050] Therefore, under the same external distance and the same real-time motion parameters, the higher the degree of off-center load risk, the greater the corrected collision risk coefficient, and the sooner the control module 200 will raise the collision risk level to the level corresponding to deceleration control or stop control.

[0051] With the above settings, off-center load risk is no longer just an independent alarm condition, but is specifically applied to the safe distance threshold, the allowable transmission speed threshold, or the collision risk coefficient through the off-center load correction factor 201, so that how off-center load risk affects collision avoidance decision has a clear calculation path; at the same time, the higher the degree of off-center load risk, the earlier the system's control intervention, the lower the allowable speed, or the higher the collision risk level, thereby solving the problem of needing different response strengths under different degrees of off-center load and achieving more refined collision avoidance control.

[0052] Furthermore, the hierarchical control instruction 202 includes: Level 1 Instruction: When the collision risk is below the first threshold (e.g., R < 0.3), the system considers the current state safe and does not intervene. The loader continues to transmit normally at the speed set by the operator. At this time, the cab does not issue an alarm, but only displays status information.

[0053] Level 2 instruction: When the collision risk is between the first and second thresholds (e.g., 0.3≤R<0.6), the system determines that there is a medium risk. The control module 200 sends a speed reduction instruction to the transmission motor controller to limit the transmission speed to the first safe speed range (e.g., 0.2~0.4m / s). At the same time, the cab issues a warning signal to remind the operator to pay attention.

[0054] Level 3 instruction: When the corrected collision risk level is between the second and third thresholds (e.g., 0.6≤R<0.8), the system judges the risk to be high, and the control module 200 further reduces the transmission speed to the second safe speed range. The upper limit of the second safe speed range is lower than the lower limit of the first safe speed range, and at the same time, an audible and visual alarm is issued.

[0055] Level 4 instruction: When the corrected collision risk level is higher than the third threshold (e.g., R≥0.8), the system judges the collision risk to be high, and the control module 200 immediately cuts off the power to the transmission motor or sends an emergency braking signal to stop the movement of the goods. At the same time, an emergency alarm is issued and the event log is recorded.

[0056] It should be noted that the first threshold, the second threshold, and the third threshold are dynamically adjustable and can be offset according to the off-center load risk.

[0057] By employing a tiered strategy of first slowing down and then stopping, the impact of sudden stops on goods and equipment is avoided. In low-risk situations, the operation can continue even with only a slowdown, avoiding unnecessary work interruptions. Tiered alarms allow operators to be fully prepared psychologically and operationally.

[0058] Furthermore, the real-time motion parameters include the instantaneous velocity v, instantaneous acceleration a, and mass m of the cargo. The instantaneous velocity v can be obtained through the encoder of the transmission motor or a separate speed sensor. The instantaneous acceleration a can be obtained through velocity differential or accelerometer. The mass m of the cargo can be measured in real time through a weighing module integrated on the transmission platform, or estimated through the cargo volume and standard density.

[0059] Secondly, the control module 200 calculates the inertial sliding distance S1. The inertial sliding distance refers to the distance that the cargo will continue to slide forward due to inertia if the transmission is stopped immediately from the current moment (i.e., power is cut off and the cargo is naturally decelerated to 0 by friction). In the simplified model, S1 = v² / (2μg), where μ is the friction coefficient between the transmission surface and the bottom of the container plate, and g is the acceleration due to gravity. A more accurate model can consider the acceleration a (if the cargo is currently accelerating, the inertia is greater; if the cargo is currently decelerating, the inertia is smaller), as well as the influence of mass m on friction. Then, the control module 200 compares the inertial gliding distance S1 with the current distance d between the front end of the cargo and the hatch. If S1 ≥ d, the control module 200 determines that the basic inertial gliding distance is not less than the current external distance information, and outputs a higher level of collision risk accordingly. When S1 is less than d, the control module 200 can determine the basic collision risk coefficient based on the ratio of S1 to d, for example, R = min(1, S1 / d).

[0060] Finally, when the off-center load risk level exceeds the preset off-center load threshold, the control module 200 uses the off-center load correction factor 201 to perform a safety redundancy correction on the basic inertial sliding distance. Since the cargo may rotate, sideslip, or partially tilt during braking under off-center load conditions, the actual sliding distance may be greater than the ideal sliding distance. Therefore, the basic inertial sliding distance S1 can be corrected to a corrected inertial sliding distance S2. The correction method can be: S2 = S1 × (1 + α·L), where S1 is the basic inertial sliding distance, S2 is the corrected inertial sliding distance, L is the off-center load risk level, and α is the preset redundancy correction coefficient. The control module 200 determines the corrected collision risk level based on the comparison between the corrected inertial sliding distance S2 and the current distance d from the front end of the cargo to the hatch. When S2 is close to or greater than d, the control module 200 increases the collision risk level and outputs a deceleration or stop command. The preset redundancy correction coefficient α can be pre-calibrated based on the loader's braking response time, the friction coefficient of the transmission surface, and historical sliding distance test results.

[0061] Therefore, collision risk can be quantitatively calculated based on inertial sliding distance, and the impact of off-center loading can be quantified into the corrected inertial sliding distance.

[0062] Reference Figure 1 and Figure 2 The radar detection module 100 also includes an environmental sensor group 102, which includes at least one of a light sensor, a rain sensor, and an electromagnetic interference detection module. The control module 200 dynamically adjusts the sensor fusion strategy or radar operating parameters based on the output of these sensors. To address light interference: Under strong sunlight, the infrared component of sunlight may enter the receiver of the lidar, generating noise or false echoes. The light sensor detects the ambient illuminance, and when the illuminance exceeds a preset value (e.g., 10,000 lux, equivalent to strong sunlight), the control module 200 reduces the weight of the lidar in distance measurement. If a millimeter-wave radar 101 is also present in the system, its weight is increased; if only a lidar is present, an alarm is triggered to alert the operator to potential light interference.

[0063] For rainy and foggy weather: The millimeter-wave radar 101 has strong penetration ability in rain and fog, but the laser and optical sensors will be severely attenuated. When the rain sensor (such as an optical rain sensor or a capacitive rain sensor) detects rainfall or humidity exceeding the threshold, the control module 200 increases the weight of the millimeter-wave radar 101 in distance measurement, and can even temporarily turn off the lidar to save energy or avoid erroneous data.

[0064] Regarding electromagnetic interference: Airport aprons contain various sources of electromagnetic interference (such as navigation radar, communication equipment, and radar from other vehicles). The electromagnetic interference detection module can be a spectrum monitoring circuit or it can determine the presence of abnormal interference by analyzing the noise floor level of the signal received by the millimeter-wave radar 101. When strong electromagnetic interference is detected, the control module 200 triggers the frequency switching function of the millimeter-wave radar 101. For example, if the radar is originally operating at 77GHz, it will automatically switch to the 79GHz or 24GHz band after being interfered with (hardware support for frequency agility is required). After the frequency switch, if the interference intensity at the second operating frequency is lower than the preset interference threshold, the control module 200 will continue to use the detection results of the switched millimeter-wave radar for distance detection or internal status detection.

[0065] This solution addresses the issues of lidar failure or false alarms under strong sunlight, unreliable optical sensors in rainy or foggy weather, and electromagnetic interference causing millimeter-wave radar 101 to fail to detect.

[0066] Furthermore, the control module 200 has a built-in non-volatile memory that continuously records the following data during each transfer operation: Record the external distance information, internal cargo distribution status information (or key features), real-time motion parameters (speed, acceleration, mass), off-center load risk judgment results (degree value), collision risk calculation results (risk coefficient, inertial sliding distance, etc.) during each transmission process, and finally output the graded control command 202 (normal / deceleration / stop). The collision risk calculation model includes multiple parameters, such as the friction coefficient μ, safety distance threshold, off-center load correction coefficient α, and risk thresholds at various levels in the inertial skid distance formula. The control module 200 updates the parameters in the collision risk calculation model using recorded historical data. The parameters include at least one of the friction coefficient μ, safety distance threshold, redundancy correction coefficient α, and risk thresholds at various levels. Specifically, when multiple false alarms or missed alarms occur consecutively in the same loading scenario, the control module 200 enters calibration mode, controls the loader to transport standard mass cargo at a preset speed, measures the actual skid distance of the cargo after braking, and compares the actual skid distance with the ideal inertial skid distance calculated according to S1=v² / (2μg). When the actual skid distance is greater than the ideal inertial skid distance, the control module 200 increases the friction coefficient correction, redundancy correction coefficient α, or safety distance threshold by a preset step size. When the actual skid distance is less than the ideal inertial skid distance and there is a false stop, the control module 200 decreases the corresponding parameter by a preset step size to achieve step-by-step closed-loop calibration.

[0067] The system monitors for false alarms and missed alarms. A false alarm is defined as: the model outputs a high risk and triggers a speed reduction / stop, but there is actually no collision risk (e.g., the operator continues the operation after confirming it is safe and no collision occurs). A missed alarm is defined as: the model outputs a low risk, but a collision or dangerous situation actually occurs (requires manual marking). When multiple false alarms or missed alarms occur consecutively (e.g., 3 times) in the same loading scenario (e.g., a specific aircraft model or a specific cargo type), the system automatically triggers recalibration, i.e., suspends normal operation and enters calibration mode. Calibration mode includes: automatically running a set of standard tests (e.g., transporting standard weight cargo at different speeds and measuring the actual sliding distance), or prompting the operator to enter correction values.

[0068] By recording historical operation data and performing calibration procedures when false alarms or omissions occur consecutively, the control module 200 can correct the friction coefficient, redundancy correction coefficient, or risk threshold based on the actual skidding distance, so as to reduce the impact of different loader states, changes in transmission surface friction, or differences in cargo type on the accuracy of collision risk calculation.

[0069] Furthermore, the control module 200 is also configured as follows: The control module 200 continuously records the time series of external distance information, for example, recording the distance d(t) between the cargo and the hatch every 0.1 seconds. By analyzing the changes in d(t), the instantaneous velocity v(t) = Δd / Δt and the acceleration a(t) = Δv / Δt of the cargo can be calculated. Assuming that the motion pattern (uniform speed, uniform acceleration, variable acceleration) of the cargo remains unchanged within a short time window (e.g., the next second), the future distance can be predicted using the kinematic equation: d(t+Δt) = d(t) - v(t)·Δt - 0.5·a(t)·Δt². More complex predictions can be made using Kalman filtering or neural networks to model possible jitter and serpentine movements of the cargo. The preset safe transport path refers to the optimal straight-line trajectory of the cargo from the front end of the loader's bridge platform to the hatch. Ideally, the cargo should move in a straight line along the centerline of the bridge platform without deflection. Path deviation can be measured by the lateral offset of the cargo's front center point from the ideal trajectory centerline, or by analyzing whether multiple measuring points of the distance sensor (such as the left, center, and right measuring points) change synchronously to determine whether the cargo has deviated.

[0070] When the predicted trajectory indicates that the cargo will collide with the hatch at some point in the future (e.g., 0.5 seconds later) (i.e., the predicted distance is ≤0), or the trajectory deviation exceeds a threshold (e.g., lateral offset exceeds 5cm), the system does not need to wait until the cargo actually reaches the dangerous position before triggering control. Instead, it outputs a deceleration or stop command in advance. By outputting the deceleration or stop command in advance, the transmission speed can be reduced before the cargo deflection or approach speed increases further, thereby reducing the probability of a collision or reducing the impact energy when a collision may occur.

[0071] By continuously detecting external distance information and predicting motion trajectory, the control module 200 can output deceleration or stop commands before the cargo reaches a dangerous position, thereby reducing the risk of response lag caused by relying solely on near-distance threshold triggering control and improving the ability to identify abnormal motion states such as cargo deflection and lateral deviation in advance.

[0072] Reference Figure 1 and Figure 2 Furthermore, a cargo status perception and collision avoidance method based on radar wave detection is provided, including the following steps: S1. Environmental and Cargo Status Acquisition: The millimeter-wave radar 101 operates in a time-division switching mode, acquiring real-time external distance information between the containerized cargo and the aircraft door in external ranging mode, and acquiring information on the stacking position, density distribution, and center of gravity position of the cargo inside the non-metallic container in penetration imaging mode.

[0073] S2. Determination of Off-center Loading Risk: Based on the three-dimensional distribution image of the internal cargo, calculate the cargo's center of gravity offset, weight distribution asymmetry, and center of gravity height to determine the degree of off-center loading risk. The degree of off-center loading risk can be expressed as a continuous numerical value, percentage, or graded label.

[0074] S3. Basic Collision Risk Calculation: Based on external distance information, instantaneous velocity of the cargo, instantaneous acceleration, and cargo mass, calculate the basic inertial sliding distance under the current motion state, and compare the basic inertial sliding distance with the external distance information to obtain the basic collision risk.

[0075] S4. Off-center load correction: When the off-center load risk level is greater than the preset off-center load threshold, an off-center load correction factor 201 is generated according to the off-center load risk level, and the off-center load correction factor 201 is used to correct at least one of the safety distance threshold, allowable transmission speed threshold or collision risk coefficient in the basic collision risk to obtain the corrected collision risk level.

[0076] S5. Graded control output: Based on the corrected collision risk level, output graded control commands 202 in sequence, such as normal transmission, graded speed reduction warning, graded audible and visual alarm, or emergency stop.

[0077] S6. Parameter Calibration: Record the distance data, off-center loading status, motion parameters, risk calculation results and control commands for this operation; when false alarms or omissions occur continuously, the control module 200 enters the calibration mode, controls the loader to transfer standard mass of goods at a preset speed, measures the actual sliding distance, and performs stepwise corrections on the friction coefficient, redundancy correction coefficient or risk threshold based on the deviation between the actual sliding distance and the ideal inertial sliding distance.

[0078] By simultaneously acquiring external distance and internal cargo distribution status using millimeter-wave radar 101, the level of off-center loading risk is determined in real time. When the off-center loading risk level exceeds the preset off-center loading threshold, an off-center loading correction factor 201 is generated based on the off-center loading risk level. This off-center loading correction factor 201 is used to correct the safety distance threshold, the allowable transmission speed threshold, or the collision risk coefficient, so that the collision avoidance decision is linked with the off-center loading status of the cargo. At the same time, the basic collision risk is calculated by combining real-time motion parameters, and a graded control command 202 is output according to the corrected collision risk level. This avoids false alarms or protection lag caused by fixed thresholds, reduces unnecessary emergency stops while ensuring safety, and improves the continuity and environmental adaptability of loading operations.

[0079] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A cargo status perception and collision avoidance system based on radar wave detection, applied to civil aviation container cargo loaders, characterized in that, include: The radar detection module (100) acquires information on the external distance between the containerized cargo and the hatch, as well as information on the distribution status of the cargo inside the containerized cargo, through millimeter-wave radar (101). The control module (200), connected to the radar detection module (100), is configured as follows: The degree of off-center loading risk is determined based on the distribution information of the internal goods; The basic collision risk is calculated based on the external distance information and the real-time movement parameters of the cargo; When the degree of off-center load risk is greater than the preset off-center load threshold, an off-center load correction factor (201) is generated according to the degree of off-center load risk, and the off-center load correction factor (201) is used to correct at least one of the safety distance threshold, the allowable transmission speed threshold or the collision risk coefficient in the basic collision risk, so as to obtain the corrected collision risk level. The graded control command (202) is output according to the modified collision risk level, and the graded control command (202) is sent to the loader's transmission motor controller to adjust the transmission speed of the cargo or perform braking. The millimeter-wave radar (101) is configured to switch working modes, acquire the external distance information in the external ranging mode, and acquire the distribution status information of the internal cargo in the penetration imaging mode. The signal frequency of the penetration imaging mode is configured to penetrate the non-metallic container wall. The control module (200) is configured to generate a three-dimensional distribution image of the container cargo based on the penetration echo signal received by the millimeter-wave radar (101), and identify off-center loading risks based on the positional offset, center of gravity offset, or distribution symmetry of the cargo. The hierarchical control command (202) includes: Level 1 instruction: Normal transmission, corresponding to the corrected collision risk level being lower than the first threshold; Level 2 instruction: Reduce speed to the first safe speed range and issue a warning, corresponding to the modified collision risk level being between the first threshold and the second threshold; Level 3 instruction: Reduce speed to the second safe speed range and issue an audible and visual alarm, corresponding to the corrected collision risk level being between the second threshold and the third threshold, where the upper limit of the second safe speed range is lower than the lower limit of the first safe speed range; Level 4 instruction: Immediately stop transmission and issue an emergency alarm, corresponding to a revised collision risk level that is higher than the third threshold; The real-time motion parameters include the instantaneous speed of the cargo; The control module (200) is configured to calculate the basic inertial sliding distance S1 under the current motion state based on the instantaneous velocity v of the cargo, the friction coefficient μ between the transmission surface and the cargo, and the gravitational acceleration g. Wherein, S1 = v² / (2μg); The control module (200) calculates the basic collision risk based on the comparison between the basic inertial gliding distance S1 and the external distance information d; The control module (200) uses the degree of off-center load risk as the off-center load variable L, and calculates the corrected inertial sliding distance S2 according to S2=S1×(1+α·L); Where α is the preset redundancy correction coefficient; The control module (200) determines the corrected collision risk level based on the comparison result between the corrected inertial gliding distance S2 and the external distance information d.

2. The cargo status perception and collision avoidance system based on radar wave detection as described in claim 1, characterized in that: The control module (200) is configured to generate an off-center load correction factor (201) based on the degree of off-center load risk, and to use the off-center load correction factor (201) to correct the basic collision risk in at least one of the following ways: When the safety distance threshold is corrected, the basic safety distance threshold is corrected to the off-center safety distance threshold according to a preset mapping relationship. The preset mapping relationship is a linear function, a piecewise function, or a lookup table relationship. When the allowed transmission speed threshold is modified, the basic allowed transmission speed threshold is modified to the off-center allowed transmission speed threshold according to the preset mapping relationship; When the collision risk coefficient is corrected, the degree of off-center load risk is used as the off-center load variable L, and the basic collision risk coefficient R1 is corrected to the corrected collision risk coefficient R2. Where R2 = R1 × (1 + k·L), or R2 = R1 + k·L, k is the preset amplification factor.

3. The cargo status perception and collision avoidance system based on radar wave detection as described in claim 2, characterized in that: The radar detection module (100) further includes an environmental sensor group (102), which includes at least one of a light sensor, a rain sensor, and an electromagnetic interference detection module; When the radar detection module (100) includes a lidar for distance detection, the control module (200) is configured to reduce the weight of the lidar in distance detection and increase the weight of the millimeter-wave radar (101) in distance detection when the light intensity exceeds a preset value, based on the detection result of the light sensor. The control module (200) is also configured to increase the weight of the millimeter-wave radar (101) in distance detection when rainfall or humidity exceeds a preset value, based on the detection results of the rain sensor. The control module (200) is further configured to trigger the millimeter-wave radar (101) to switch from a first operating frequency to a second operating frequency when abnormal electromagnetic interference is detected, based on the detection result of the electromagnetic interference detection module.

4. The cargo status perception and collision avoidance system based on radar wave detection as described in claim 3, characterized in that: The control module (200) is also configured to: Record the external distance information, internal cargo distribution status information, real-time motion parameters, off-center load risk judgment results, collision risk calculation results, and the final output hierarchical control instructions (202) during each transmission process. The friction coefficient μ, redundancy correction coefficient α, or risk threshold in the collision risk calculation model are updated based on the recorded data. When multiple false alarms or missed alarms occur consecutively in the same loading scenario, the model parameters are automatically recalibrated, causing the system to enter calibration mode. The system controls the loader to transport standard-weight cargo at a preset speed, measures the actual sliding distance, and performs stepwise corrections on the friction coefficient μ, redundancy correction coefficient α, or risk threshold based on the deviation between the actual sliding distance and the ideal inertial sliding distance.

5. The cargo status perception and collision avoidance system based on radar wave detection as described in claim 4, characterized in that: The control module (200) is also configured to: By continuously detecting the external distance information acquired by the radar detection module (100), the movement trajectory of the goods within a future time window is predicted; When the predicted trajectory deviates from the preset safe transmission path by more than a threshold, a deceleration or stop command is output in advance before the goods actually reach the dangerous location.

6. A cargo status perception and collision avoidance method based on radar wave detection, applied to the cargo status perception and collision avoidance system based on radar wave detection as described in any one of claims 1 to 5, characterized in that, Includes the following steps: The millimeter-wave radar (101) acquires information on the external distance between the containerized cargo and the hatch, as well as information on the distribution of cargo inside the containerized cargo. The degree of off-center loading risk is determined based on the distribution information of the internal goods; The basic collision risk is calculated based on the external distance information and the real-time movement parameters of the cargo; When the degree of off-center load risk is greater than the preset off-center load threshold, an off-center load correction factor (201) is generated according to the degree of off-center load risk, and the off-center load correction factor (201) is used to correct at least one of the safety distance threshold, the allowable transmission speed threshold or the collision risk coefficient in the basic collision risk, so as to obtain the corrected collision risk level. The graded control command (202) is output according to the modified collision risk level, and the graded control command (202) is sent to the transmission motor controller of the loader to adjust the transmission speed of the cargo or perform braking.

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