A semi-automatic forklift control system based on remote monitoring

Abstract

The application relates to a fork truck control technical field, in particular to a semi-automatic fork truck control system based on remote monitoring, which comprises a remote monitoring center, an environment sensing unit, a vehicle state acquisition unit, a vehicle-mounted processing unit, a vehicle-mounted control unit, a semi-automatic control unit and a communication unit. The system preprocesses the received environment data through filtering and calculation; the running state of the system is determined through the equivalent driving time and the preset threshold; the shortest distance standard is adjusted based on the determination result, and the fork alignment accuracy and the end deceleration distance are further determined according to the adjustment effect; the application realizes the unified processing and analysis performance optimization of the semi-automatic fork truck control system, effectively optimizes the equivalent driving time of the fork truck driving stage of the scheme, and improves the resource utilization rate.

Description

Technical Field

[0001] This invention relates to the field of forklift control technology, and in particular to a semi-automatic forklift control system based on remote monitoring. Background Technology

[0002] Forklifts, as key equipment in material handling, face new demands regarding their operation and intelligence, highlighting the growing problems of traditional manual forklift operation. This results in high skill requirements for operators, significant training costs, the inability of the system to optimize based on feedback, and difficulties in guaranteeing the reliability and stability of processing results. To avoid potential risks, quantify the duration of single operations for different processes, optimize engineering routes, and place higher demands on the scientific rigor and comparability of analysis results. Many improved and updated measures have been implemented, enabling timely anomaly detection and significantly improving overall operational efficiency, becoming a necessary and effective means. Therefore, traditional manual operation remains one of the important methods in current forklift control systems.

[0003] However, existing technologies mostly employ unified fixed parameters or local adjustment mechanisms, lacking overall optimization of the operation of multiple areas of the system, such as environmental perception unit, vehicle status acquisition unit, on-board processing unit, on-board control unit, execution unit, communication unit, remote monitoring center, semi-automatic control module, and safety monitoring and intervention module. Existing technologies mostly rely on manual experience diagnosis, making it difficult to achieve global optimization scheduling and efficient collaborative operation. Therefore, the operating efficiency of forklift control systems is low, and they cannot systematically capture the dynamic correlation between various data.

[0004] Meanwhile, existing systems are not adaptable enough to dynamically changing environments and on-site disturbances. Key data within the system often rely on empirically set or fixed standard values, lacking a mechanism for dynamic adjustment based on specific real-time monitoring and analysis data, thus reducing the operational efficiency and reliability of the forklift control system.

[0005] Chinese Patent Publication No. CN119604829A discloses a control method for an automated guided vehicle with forklift capabilities, including a primary sensor and a motion controller. The system adjusts the driving distance of the automated guided vehicle by monitoring the vehicle position in real time, sets an automatic guidance path according to the loading and unloading mode, and guides the movement of the vehicle based on the travel distance.

[0006] Therefore, although the proposed solution can automatically guide vehicle movement, it still has the following problems: 1. This solution only uses a single real-time monitoring method to adjust the travel distance. When other modules of the system are malfunctioning, it cannot intelligently optimize the vehicle through sensors, which leads to an inability to effectively balance the working time of each vehicle, thereby reducing the operational efficiency of the vehicle control system.

[0007] 2. This scheme uses fixed processing decisions, which can lead to correction deviations when the sensor acquisition frequency changes. This affects the subsequent operation of the module based on vehicle travel distance analysis and further reduces the operational efficiency of the vehicle control system. Summary of the Invention

[0008] To address this issue, the present invention provides a semi-automatic forklift control system based on remote monitoring, which overcomes the problem of increased operating time of forklift control systems caused by data processing deviations resulting from the inability to generate corresponding update decisions based on changes in environmental factors in the prior art.

[0009] To achieve the above objectives, the present invention provides a semi-automatic forklift control system based on remote monitoring, comprising: A remote monitoring center is used to generate the expected path based on the obstacle map; An environmental sensing unit, installed on the forklift, is used to periodically collect environmental data around the forklift, including environmental feature points around the forklift and the shortest distance between the actual position of the forklift and the expected path in each period. The vehicle status acquisition unit, which is connected to the environmental sensing unit, is used to acquire the status parameters of the forklift in real time, including driving speed, working time, buffer distance and fork pitch angle. The vehicle-mounted processing unit is connected to the environmental perception unit and the vehicle status acquisition unit to preprocess the received environmental data and status parameters. The preprocessing methods include filtering environmental feature points, calculating the density of environmental feature points, calculating the path overlap based on each shortest distance, calculating the change in driving speed, and calculating the average operation time. The vehicle control unit is connected to the vehicle processing unit and is used to determine whether to generate a corresponding processing decision based on the preprocessed data output by the vehicle processing unit, and to determine whether to update the processing decision based on the preprocessed data re-acquired after executing the processing decision. A semi-automatic control unit, which is connected to the vehicle control unit, is used to generate corresponding adjustment decisions based on the processing decisions output by the vehicle control unit in order to adjust the operating parameters of the corresponding unit to the corresponding values. A communication unit, which is connected to the remote monitoring center and the vehicle control unit, is used to transmit operational data between the vehicle control unit and the remote monitoring center.

[0010] Furthermore, based on the data acquisition results from the vehicle status acquisition unit, the on-board control unit determines whether the control for the forklift's driving phase meets the standard by comparing the calculated equivalent driving time of the forklift with the preset equivalent driving time. If the control fails to meet the standard, the control unit determines the reason for the failure based on the forklift's average driving speed. The equivalent driving time of the forklift is the product of the proportion of forklift turns and the difference between the time consumed during the forklift's driving phase and the preset time. The proportion of turns is the ratio of the number of directional changes in the forklift's driving phase where the turning angle exceeds the preset angle to the total number of turns.

[0011] Furthermore, when the vehicle control unit determines that the control for the forklift's travel phase does not meet the standard, it determines the reason for the non-compliance based on a comparison between the actual average travel speed of the forklift and the pre-stored preset average travel speed. Based on the determined reason, it generates a corresponding processing decision, including: issuing a decision to adjust the path overlap if the cause is a deviation in the travel path control strategy, or issuing a decision to adjust the fork alignment accuracy if the cause is excessively long operation time; wherein, the path overlap is the average of the shortest distance from the actual position point of the forklift to the planned path in each cycle during the travel phase; the fork alignment accuracy is obtained by the shortest distance between the fork and the target loading position and the fork pitch angle deviation.

[0012] Furthermore, when the vehicle control unit determines that there is a deviation in the driving path control strategy, it reduces the minimum distance standard between the forklift and obstacles at each turn based on the comparison result of the difference between the actual driving speed and the preset driving speed and the preset difference. The reduction of the minimum standard distance is positively correlated with the driving speed difference, and the expected path is regenerated based on the adjusted standard. The minimum distance standard is the difference between the preset minimum forklift distance and the speed difference.

[0013] Furthermore, after adjusting the path overlap, the vehicle control unit also corrects the adjusted shortest distance standard based on the comparison between the forklift's safe buffer distance and the preset safe buffer distance, and the reduction in path overlap is positively correlated with the safe buffer distance; wherein, the safe buffer distance is the spatial distance from the center point directly in front of the forklift surface to the nearest obstacle.

[0014] Furthermore, in response to the first repeated detection condition, the vehicle control unit determines that the reason for not meeting the standard is that the system positioning and operation process takes too long, and determines the reason for not meeting the standard based on the average fork alignment time; wherein, the average fork alignment time is the average of the difference between the timing start and timing end points during each loading or unloading action of the forklift in a single delivery operation. The first repeated detection condition is that after the vehicle control unit completes the correction of the shortest distance standard, it re-determines that the control for the forklift travel phase still does not meet the standard.

[0015] Furthermore, the vehicle control unit increases the fork alignment accuracy based on the comparison between the average fork alignment time and the preset average fork alignment time, and the increase in fork alignment accuracy is positively correlated with the average fork alignment time.

[0016] Furthermore, the vehicle control unit increases the end deceleration distance based on the comparison between the distance between the two forks and the preset distance between the two forks, and the increase in the end deceleration distance is positively correlated with the distance between the two forks; wherein, the distance between the two forks is the horizontal distance between the center lines of the two forks; the end deceleration distance is the shortest distance for the forklift to decelerate to the maximum allowable alignment speed, wherein the maximum allowable alignment speed is the corresponding speed obtained by looking up a table for the fork alignment accuracy.

[0017] Furthermore, the vehicle control unit responds to the second repeated detection condition and determines that the reason for not meeting the standard is the performance fluctuation of the environmental perception unit. It reduces the obstacle confirmation delay based on the feature point density of the forklift's environmental perception unit, and the reduction in obstacle confirmation delay is negatively correlated with the feature point density. The feature point density is the ratio of the effective feature points obtained after preprocessing by the vehicle-mounted processing unit to the volume of the effective detection area. The obstacle confirmation delay is obtained by the perception confidence coefficient, which is the ratio of the feature point density to the preset feature point density. The second repeat detection condition is that after the vehicle control unit completes the adjustment of the end deceleration distance, it re-determines that the control for the forklift's driving phase still does not meet the standard.

[0018] Furthermore, the vehicle control unit is also provided with a negative correlation function for the perception execution coefficient and the preset obstacle confirmation delay. The vehicle control unit is also used to substitute the perception confidence coefficient into the negative correlation function to obtain the obstacle confirmation delay.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: by setting up an on-board control unit, which analyzes the equivalent travel time of the forklift during each travel process, the present invention can effectively determine whether there is an execution deviation or preprocessing deviation in the forklift control system. At the same time, the on-board control unit can also output the corresponding processing method according to the determined actual situation, thereby effectively eliminating the deviation caused by abnormal data during data processing. While effectively improving the processing method for different travel processes, it effectively avoids the influence of the shortest distance standard on the equivalent travel time, thereby effectively reducing the equivalent travel time of the forklift travel phase of the solution described in the present invention.

[0020] Furthermore, the vehicle control unit of the present invention is used to determine whether the control for the forklift travel phase meets the standard based on the data acquisition results of the vehicle status acquisition unit and the comparison result of the calculated equivalent travel time of the forklift with the preset equivalent travel time. If it is determined that the control does not meet the standard, the reason for the non-compliance is determined based on the average travel speed of the forklift. This further makes the determination result of compliance more scenario-based and intelligent, thereby effectively reducing the equivalent travel time of the forklift travel phase in the solution of the present invention.

[0021] Furthermore, the vehicle control unit of the present invention is also used to determine the reason for non-compliance when it is determined that the control for the forklift travel phase does not meet the standard, based on the comparison result of the actual average travel speed of the forklift and the preset average travel speed, and to generate a corresponding processing decision based on the determined reason. This makes the judgment result more complete and refined, effectively avoiding misjudgment and omission of the average travel speed by the vehicle control unit under a single fixed threshold, thereby further effectively reducing the equivalent travel time of the forklift travel phase of the present invention.

[0022] Furthermore, the vehicle control unit of the present invention is also used to reduce the shortest distance standard between the forklift and obstacles at each turn based on the comparison result of the difference between the actual driving speed and the preset driving speed and the preset difference when it is determined that there is a deviation in the driving path control strategy. It can intuitively determine the relationship of excessive, appropriate or insufficient data processing in the current data processing process. While further improving the agility of the vehicle control unit, it further avoids resource waste, thereby further effectively reducing the equivalent driving time of the forklift driving stage of the present invention.

[0023] Furthermore, the vehicle control unit of the present invention is also used to, after completing the adjustment of the path overlap, correct the adjusted shortest distance standard according to the comparison result of the forklift safety buffer distance and the preset safety buffer distance, thereby effectively outputting the corresponding processing decision. While further improving the accuracy of the path overlap, it further avoids the influence of the safety buffer distance on the shortest distance standard, thereby further effectively reducing the equivalent travel time of the forklift travel phase of the present invention.

[0024] Furthermore, the vehicle control unit of the present invention is also used to respond to the first repeated detection condition and determine that the reason for non-compliance is that the system positioning and operation process takes too long. The reason for non-compliance is determined based on the average alignment time of the forks, thereby effectively outputting the corresponding processing decision. While further improving the data processing within the cycle, it further avoids resource waste, thereby further effectively reducing the equivalent travel time of the forklift travel phase of the solution of the present invention.

[0025] Furthermore, the vehicle control unit of the present invention is also used to increase the fork alignment accuracy based on the comparison result of the average fork alignment time and the preset average fork alignment time, which can effectively improve the accuracy of truck alignment and thus effectively avoid the occurrence of comparison result deviation, thereby further effectively reducing the equivalent travel time of the forklift travel phase of the present invention.

[0026] Furthermore, the vehicle control unit of the present invention is also used to increase the end deceleration distance based on the comparison result of the distance between the two forks and the preset distance between the two forks, which can specifically improve the agility of the forklift during the driving stage, further refine the adjustment range, and thus further effectively reduce the equivalent driving time of the forklift during the driving stage of the present invention.

[0027] Furthermore, the vehicle control unit of the present invention is also used to respond to the second repeated detection condition and determine that the reason for not meeting the standard is the performance fluctuation of the environmental perception unit. The obstacle confirmation delay is reduced according to the feature point density of the forklift environmental perception unit, and multiple preset values ​​of adjustment range are pre-stored. Thus, the obstacle confirmation delay adjusted by the adjustment coefficient ensures a more accurate processing result, thereby further effectively reducing the equivalent travel time of the forklift travel phase of the solution of the present invention.

[0028] Furthermore, the vehicle control unit of the present invention is also provided with a negative correlation function for the perception execution coefficient and the preset obstacle confirmation delay. The vehicle control unit is also used to substitute the perception confidence coefficient into the negative correlation function to obtain the obstacle confirmation delay. By constructing the correlation function, the adjustment of the obstacle delay is made more logical and precise. At the same time, multiple function models are pre-stored to ensure that the collected data can be substituted into the calculation, thereby effectively improving the accuracy of processing decisions and further effectively reducing the equivalent travel time of the forklift travel phase of the present invention. Attached Figure Description

[0029] Figure 1 This is a structural block diagram of the semi-automatic forklift control system based on remote monitoring described in this invention; Figure 2 This is a flowchart illustrating the system of the present invention that determines whether the control for the forklift travel phase conforms to the standard based on the equivalent travel time. Figure 3 This is a flowchart illustrating the control and optimization process of the system's travel path as described in this invention. Figure 4 This is an optimized flowchart of the positioning and operation process of the system described in this invention. Detailed Implementation

[0030] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0031] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0032] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0033] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" 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.

[0034] It should be noted that the data in this embodiment are all derived from a comprehensive analysis and evaluation of historical test data and corresponding historical test results from the system described in this invention over the three months prior to this test. Before this test, the system described in this invention comprehensively determines the preset values ​​stored in the database based on the analysis results of 25,863 cumulative tests over the previous three months and the processing results after handling 19,584 specific cases. Those skilled in the art will understand that the system described in this invention can determine the above-mentioned parameters for a single item by selecting the value with the highest proportion based on the data distribution as the preset standard parameter, using weighted summation to obtain the value as the preset standard parameter, substituting each historical data point into a specific formula and using the value obtained by the formula as the preset standard parameter, or other selection methods, as long as the system described in this invention can clearly define different specific situations in the single-item judgment process through the obtained values.

[0035] Please see Figure 1The diagram shown is a structural block diagram of the semi-automatic forklift control system based on remote monitoring according to the present invention. The semi-automatic forklift control system based on remote monitoring according to the present invention includes a remote monitoring center, an environmental sensing unit, a vehicle status acquisition unit, an on-board processing unit, an on-board control unit, a semi-automatic control unit, and a communication unit. The remote monitoring center is used to generate the expected path based on the obstacle map; The environmental sensing unit is installed on the forklift to periodically collect environmental data around the forklift, including environmental feature points around the forklift and the shortest distance between the actual position of the forklift and the expected path in each period. The vehicle status acquisition unit is connected to the environmental perception unit and is used to collect the status parameters of the forklift in real time, including driving speed, working time, buffer distance and fork pitch angle. The on-board processing unit is connected to the environmental perception unit and the vehicle status acquisition unit to preprocess the received environmental data and status parameters. The preprocessing methods include filtering environmental feature points, calculating the density of environmental feature points, calculating the path overlap based on each shortest distance, calculating the change in driving speed, and calculating the average operation time. The vehicle control unit is connected to the vehicle processing unit and is used to determine whether to generate a corresponding processing decision based on the preprocessed data output by the vehicle processing unit, and to determine whether to update the processing decision based on the preprocessed data re-acquired after executing the processing decision. The semi-automatic control unit is connected to the vehicle control unit and is used to generate corresponding adjustment decisions based on the processing decisions output by the vehicle control unit in order to adjust the operating parameters of the corresponding unit to the corresponding values. The communication unit is connected to the remote monitoring center and the vehicle control unit to transmit operational data between the vehicle control unit and the remote monitoring center.

[0036] Specifically, during operation, the remote monitoring center plans the path in real time based on the forklift information output by the communication unit. The environmental perception unit inputs environmental information into the vehicle status acquisition unit for data preprocessing. The on-board control unit combines the preprocessed data to start the corresponding semi-automatic operation mode and compares the preprocessed data with preset parameters to determine whether the control for the current forklift driving stage meets the standard. If the standard is not met, a corresponding processing decision is generated based on the determined reason. An alarm is issued when the system detects complex situations, potential risks, or when the semi-automatic mode cannot complete the task. The system also determines whether intervention is needed based on the displayed information. The semi-automatic control unit outputs the results based on the received processing decision.

[0037] It is understood that the environmental perception unit is equipped with a camera and a lidar device to collect environmental information in real time; the vehicle status acquisition unit is equipped with a speed sensor, a position sensor and an angle sensor to measure the forklift speed, forklift and fork position information and fork pitch angle in real time. Specifically, the system described in this invention stores and manages the processing results of received environmental and forklift information, and constructs a continuously updated database.

[0038] Please see Figure 2 As shown, this is a flowchart illustrating the system of the present invention determining whether the control for the forklift travel phase meets the standard based on the equivalent travel time. The process of determining whether the control for the forklift travel phase meets the standard based on the comparison result of the equivalent travel time includes: Specifically, the vehicle control unit described in this embodiment of the invention is used to determine whether the control for the forklift's driving phase meets the standard based on the data acquisition results of the vehicle status acquisition unit and the comparison result of the calculated equivalent driving time of the forklift with the preset equivalent driving time. If the control fails to meet the standard, the reason for non-compliance is determined based on the average driving speed of the forklift. The equivalent driving time of the forklift is the product of the proportion of forklift turns and the difference between the time consumed during the forklift's driving phase and the preset time. The proportion of turns is the ratio of the number of directional changes in the forklift's driving phase where the turning angle exceeds the preset angle to the total number of turns. In this embodiment, the preset equivalent driving time T0 = 61s.

[0039] If the equivalent driving time T is less than or equal to the preset equivalent driving time T0, the vehicle control unit determines that the control for the forklift driving phase meets the standard. If the equivalent driving time T is greater than the preset equivalent driving time T0, the vehicle control unit determines that the control for the forklift driving phase does not meet the standard, and the vehicle control unit determines the cause based on the average driving speed. It is understood that the database pre-stores the minimum allowable equivalent driving time threshold for different types of data. Therefore, the above-mentioned assignment of the preset equivalent driving time is only a preferred embodiment of the system of the present invention. The present invention does not impose specific restrictions on the value of the preset equivalent driving time, as long as the comparison result between the obtained equivalent driving time and the preset equivalent driving time can directly characterize the analysis of the vehicle control unit.

[0040] Specifically, the vehicle control unit described in this embodiment of the invention is further configured to determine the cause of non-compliance when the control for the forklift's driving phase is deemed non-compliant based on a comparison between the actual average forklift speed and a pre-stored preset average speed. It also generates corresponding processing decisions based on the determined cause, including: issuing a decision to adjust the path overlap when the cause is determined to be a deviation in the driving path control strategy, or issuing a decision to adjust the fork alignment accuracy when the cause is determined to be excessively long operation time; wherein the path overlap is the average of the shortest distance from the actual position point of the forklift to the planned path in each cycle during the driving phase; the fork alignment accuracy is obtained by the shortest distance between the forklift and the target loading position and the forklift pitch angle deviation; in this embodiment, the preset average driving speed v0 = 1.2 m / s. If the average driving speed is greater than the preset average driving speed, the vehicle control unit determines that the cause is a deviation in the forklift's driving path and issues an adjustment strategy based on the shortest distance standard. If the average driving speed is less than or equal to the preset average driving speed, the vehicle control unit determines that the reason is that the operation process takes too long and issues an adjustment decision for the fork alignment accuracy. It is understood that the fork alignment accuracy is obtained by weighted summation of the shortest distance between the forks and the target position and the pitch angle deviation.

[0041] Please see Figure 3 As shown, it is a flowchart of the control optimization process for the driving path of the system described in this invention, and the process includes: Specifically, the vehicle control unit described in this embodiment of the invention is further used to reduce the minimum distance standard L between the forklift and obstacles at each turn based on a comparison between the difference between the actual driving speed and the preset driving speed and the preset difference, when a deviation in the driving path control strategy is determined. The reduction in the minimum standard distance is positively correlated with the driving speed difference, and the expected path is regenerated based on the adjusted standard. The minimum distance standard is the difference between the preset minimum forklift distance and the speed difference. In this embodiment, the first preset average driving speed difference... =1.4m / s, second preset average driving speed difference =1.0m / s, corresponding to the first distance adjustment coefficient k1=0.5, the second distance adjustment coefficient k2=0.7, and the third distance adjustment coefficient k3=0.9; If the average driving speed difference Greater than the second preset average driving speed difference The vehicle control unit determines to adjust the shortest distance standard L using a third distance adjustment coefficient k3; If the average driving speed difference Less than or equal to the second preset average driving speed difference And greater than the first preset average driving speed difference The vehicle control unit determines to adjust the shortest distance standard L using the second distance adjustment coefficient k2; If the average driving speed difference Less than or equal to the first preset average driving speed difference The vehicle control unit determines to adjust the shortest distance standard L using a first distance adjustment coefficient k1; When the vehicle control unit uses the j-th distance adjustment coefficient kj to adjust the shortest distance standard between the forklift and the obstacle at each turn, j=1, 2, 3, the adjusted shortest distance standard L'=L×kj is set.

[0042] Specifically, the vehicle control unit described in this embodiment of the invention is further configured to, after adjusting the path overlap, correct the adjusted shortest distance standard based on a comparison between the forklift's safe buffer distance and the preset safe buffer distance, wherein the reduction in path overlap is positively correlated with the safe buffer distance; wherein the safe buffer distance is the spatial distance from the center point directly in front of the forklift's surface to the nearest obstacle; in this embodiment, the first preset safe buffer distance H1 = 1.15m, the second preset safe buffer distance H2 = 1.65m, and the corresponding first distance correction coefficient f1 = 0.95, the second distance correction coefficient f2 = 0.97, and the third distance correction coefficient f3 = 0.98; If the safety buffer distance H is greater than the second preset safety buffer distance H2, the vehicle control unit determines to use the third distance correction coefficient f3 to adjust the adjusted shortest distance standard L'. If the safety buffer distance H is less than or equal to the second preset safety buffer distance H2 and greater than the first preset safety buffer distance H1, the vehicle control unit determines to use the second distance correction coefficient f2 to adjust the adjusted shortest distance standard L'. If the safety buffer distance H is less than or equal to the first preset safety buffer distance H1, the vehicle control unit determines to adjust the adjusted shortest distance standard L' using the first distance correction coefficient f1. When the vehicle control unit uses the x-th distance correction coefficient fx to correct the adjusted shortest distance standard, x=1, 2, 3, the corrected adjusted shortest distance standard is set to "=L'×fx".

[0043] It is understood that the database described in this embodiment of the invention is based on the monitored safe buffer distance, and compares the safe buffer distance obtained through real-time calculation with it to achieve accurate evaluation and graded response of parameter adjustment status. The higher the average driving speed, the larger the required safe buffer distance and the larger the required adjustment range. Therefore, a corresponding adjustment coefficient needs to be selected to ensure that the safe buffer distance is proportional to the corrected shortest distance standard. Thus, the correction coefficient is proportional to the shortest distance standard.

[0044] Specifically, the vehicle control unit described in this embodiment of the invention is also used to respond to the first repeated detection condition and determine that the reason for not meeting the standard is that the system positioning and operation process takes too long. The reason for not meeting the standard is determined based on the average fork alignment time. The average fork alignment time is the average of the difference between the timing start and timing end points during each loading or unloading action of the forklift in a single delivery operation. The first repeated detection condition is that after the vehicle control unit completes the correction of the shortest distance standard, it re-determines that the control for the forklift travel phase still does not meet the standard.

[0045] Please see Figure 4 As shown, it is an optimized flowchart of the system positioning and operation process of the present invention, the process of which includes: Specifically, the vehicle control unit described in this embodiment of the invention is further used to increase the fork alignment accuracy z based on the comparison result of the average fork alignment time and the preset average fork alignment time, and the increase in fork alignment accuracy is positively correlated with the average fork alignment time; in this embodiment, the first preset average fork alignment time u1 = 4.0s; the second preset average fork alignment time u2 = 5.2s; and the corresponding first accuracy adjustment coefficient =1.4, second precision adjustment coefficient =1.6, third precision adjustment coefficient =1.8; If the average fork alignment time u is greater than the second preset average fork alignment time u2, the vehicle control unit determines to use the third precision adjustment coefficient. Adjust the fork alignment accuracy z; If the average fork alignment time u is less than or equal to the second preset average fork alignment time u2 and greater than the first preset average fork alignment time u1, the vehicle control unit determines to use the second precision adjustment coefficient. Adjust the fork alignment accuracy z; If the average fork alignment time u is less than or equal to the first preset average fork alignment time u1, the vehicle control unit determines to use the first precision adjustment coefficient. Adjust the fork alignment accuracy z; When the vehicle control unit uses the p-th precision adjustment coefficient When adjusting the fork alignment accuracy z, p=1,2,3, and the adjusted fork alignment accuracy z'=z× .

[0046] Specifically, the vehicle control unit described in this embodiment of the invention is further used to increase the end deceleration distance d based on the comparison result between the distance between the two forks and the preset distance between the two forks, and the increase in the end deceleration distance is positively correlated with the distance between the two forks; wherein, the distance between the two forks is the horizontal distance between the center lines of the two forks; the end deceleration distance is the shortest distance for the forklift to decelerate to the maximum allowable alignment speed, wherein the maximum allowable alignment speed is the corresponding speed obtained by looking up a table for fork alignment accuracy; in this embodiment, the first preset distance between the two forks b1 = 25mm; the second preset distance between the two forks b2 = 50mm; and the corresponding first distance adjustment coefficient. =1.3, second spacing adjustment coefficient =1.5, third spacing adjustment coefficient =1.7; If the distance between the two forks, b, is greater than the second preset distance between the two forks, b2, the vehicle control unit determines to use the third distance adjustment coefficient. Adjust the end deceleration distance d; If the distance between the two forks, b, is less than or equal to the second preset distance between the two forks, b2, and greater than the first preset distance between the two forks, b1, the vehicle control unit determines to use the second distance adjustment coefficient. Adjust the end deceleration distance d; If the distance between the two forks b is less than or equal to the first preset distance between the two forks b1, the vehicle control unit determines to use the first distance adjustment coefficient. Adjust the end deceleration distance d; When the vehicle control unit uses the r-th spacing adjustment coefficient When adjusting the end deceleration distance d, p=1,2,3, and set the adjusted end deceleration distance. .

[0047] It is understandable that the greater the distance between the two forks, the greater the required end deceleration distance. Therefore, it is necessary to select a corresponding adjustment coefficient to increase the end deceleration distance. Hence, the adjustment coefficient is directly proportional to the end deceleration distance.

[0048] Specifically, the vehicle control unit described in this embodiment of the invention is also used to respond to the second repeated detection condition and determine that the reason for not meeting the standard is the performance fluctuation of the environmental perception unit. The obstacle confirmation delay y is reduced according to the feature point density of the forklift environmental perception unit, and the reduction of the obstacle confirmation delay is negatively correlated with the feature point density. The feature point density is the ratio of the effective feature points obtained after preprocessing by the vehicle-mounted processing unit to the volume of the effective detection area. The obstacle confirmation delay is obtained by the perception confidence coefficient, which is the ratio of the feature point density to the preset feature point density. The second repeat detection condition is that after the vehicle control unit completes the adjustment of the end deceleration distance, it re-determines that the control for the forklift's driving phase still does not meet the standard.

[0049] In this embodiment, the first preset feature point density =600 points / m 3 Second preset feature point density =800 points / m 3 The corresponding first density adjustment coefficient =0.85, second density adjustment coefficient =0.65, third density adjustment coefficient =0.55; If the feature point density Greater than the second preset feature point density The vehicle control unit determines that the obstacle confirmation delay y is adjusted using a third density adjustment coefficient Ω3; If the feature point density less than or equal to the second preset feature point density And greater than the first preset feature point density The vehicle control unit determines to use the second density adjustment coefficient. Adjust the obstacle confirmation delay y; If the feature point density less than or equal to the first preset feature point density The vehicle control unit determines to use the first density adjustment coefficient. Adjust the obstacle confirmation delay y; When the vehicle control unit adjusts the obstacle confirmation delay y using the nth density adjustment coefficient Ωn, n=1,2,3, the adjusted obstacle confirmation delay is set. .

[0050] It is understood that the system obtains the obstacle confirmation delay through a negative correlation function and replans the preset path based on the adjusted obstacle confirmation delay.

[0051] Specifically, the vehicle control unit described in this embodiment of the invention is further provided with a negative correlation function for the perception execution coefficient and the preset obstacle confirmation delay. The vehicle control unit is also used to substitute the perception confidence coefficient into the negative correlation function to obtain the obstacle confirmation delay.

[0052] It is understood that the embodiments of the present invention have a negative correlation function y=y0×f(c), where f(c) is a monotonically decreasing function of the confidence coefficient. As the confidence coefficient decreases, f(c) decreases accordingly. Therefore, the required obstacle confirmation delay y also decreases accordingly. Hence, the density adjustment coefficient is inversely proportional to the obstacle confirmation delay.

[0053] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0054] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A semi-automatic forklift control system based on remote monitoring, characterized in that, include: A remote monitoring center is used to generate the expected path based on the obstacle map; An environmental sensing unit, installed on the forklift, is used to periodically collect environmental data around the forklift, including environmental feature points around the forklift and the shortest distance between the actual position of the forklift and the expected path in each period. The vehicle status acquisition unit, which is connected to the environmental perception unit, is used to collect the status parameters of the forklift in real time, including driving speed, working time, buffer distance and fork pitch angle. The vehicle-mounted processing unit is connected to the environmental perception unit and the vehicle status acquisition unit to preprocess the received environmental data and status parameters. The preprocessing methods include filtering environmental feature points, calculating the density of environmental feature points, calculating the path overlap based on each shortest distance, calculating the change in driving speed, and calculating the average operation time. The vehicle control unit is connected to the vehicle processing unit and is used to determine whether to generate a corresponding processing decision based on the preprocessed data output by the vehicle processing unit, and to determine whether to update the processing decision based on the preprocessed data re-acquired after executing the processing decision. A semi-automatic control unit, which is connected to the vehicle control unit, is used to generate corresponding adjustment decisions based on the processing decisions output by the vehicle control unit in order to adjust the operating parameters of the corresponding unit to the corresponding values. A communication unit, which is connected to the remote monitoring center and the vehicle control unit, is used to transmit operational data between the vehicle control unit and the remote monitoring center.

2. The semi-automatic forklift control system based on remote monitoring according to claim 1, characterized in that, The vehicle control unit is used to determine whether the control of the forklift's driving phase meets the standard based on the data acquisition results of the vehicle status acquisition unit and the comparison result of the calculated equivalent driving time of the forklift with the preset equivalent driving time. If it is determined that the control does not meet the standard, the reason for the non-compliance is determined based on the average driving speed of the forklift. The equivalent driving time of the forklift is the product of the proportion of forklift turns and the difference between the time spent in the forklift driving phase and the preset time. The proportion of turns is the ratio of the number of directional changes in which the forklift's turning angle exceeds the preset angle to the total number of turns.

3. The semi-automatic forklift control system based on remote monitoring according to claim 2, characterized in that, The vehicle control unit is also used to determine the cause of non-compliance when the control for the forklift's travel phase is deemed non-compliant based on a comparison of the actual average travel speed of the forklift with a pre-stored preset average travel speed. Furthermore, it generates corresponding processing decisions based on the determined cause, including: issuing a decision to adjust the path overlap if the cause is a deviation in the travel path control strategy, or issuing a decision to adjust the fork alignment accuracy if the cause is excessively long operation time; wherein the path overlap is the average of the shortest distance from the actual position point of the forklift to the planned path in each cycle during the travel phase; and the fork alignment accuracy is obtained by the shortest distance between the forklift and the target loading position and the forklift pitch angle deviation.

4. The semi-automatic forklift control system based on remote monitoring according to claim 3, characterized in that, The vehicle control unit is also used to reduce the minimum distance standard between the forklift and obstacles at each turn based on the comparison between the difference between the actual driving speed and the preset driving speed and the preset difference when it is determined that there is a deviation in the driving path control strategy. The reduction of the minimum standard distance is positively correlated with the driving speed difference, and the expected path is regenerated based on the adjusted standard. The minimum distance standard is the difference between the preset minimum forklift distance and the speed difference.

5. The semi-automatic forklift control system based on remote monitoring according to claim 4, characterized in that, The vehicle control unit is also used to adjust the path overlap after completing the adjustment, and to correct the adjusted shortest distance standard according to the comparison result of the forklift safety buffer distance and the preset safety buffer distance. The reduction in path overlap is positively correlated with the safety buffer distance. The safety buffer distance is the spatial distance from the center point directly in front of the forklift surface to the nearest obstacle.

6. The semi-automatic forklift control system based on remote monitoring according to claim 5, characterized in that, The vehicle control unit is also used to respond to the first repeated detection condition and determine that the reason for non-compliance is that the system positioning and operation process takes too long. The reason for non-compliance is determined based on the average fork alignment time. The average fork alignment time is the average difference between the timing start and timing end of each loading or unloading action of the forklift in a single delivery operation. The first repeated detection condition is that after the vehicle control unit completes the correction of the shortest distance standard, it re-determines that the control for the forklift travel phase still does not meet the standard.

7. The semi-automatic forklift control system based on remote monitoring according to claim 6, characterized in that, The vehicle control unit is also used to increase the fork alignment accuracy based on the comparison result of the average fork alignment time and the preset average fork alignment time, and the increase in fork alignment accuracy is positively correlated with the average fork alignment time.

8. The semi-automatic forklift control system based on remote monitoring according to claim 7, characterized in that, The vehicle control unit is also used to increase the end deceleration distance based on the comparison result between the distance between the two forks and the preset distance between the two forks, and the increase in the end deceleration distance is positively correlated with the distance between the two forks; wherein, the distance between the two forks is the horizontal distance between the center lines of the two forks; the end deceleration distance is the shortest distance for the forklift to decelerate to the maximum allowable alignment speed, wherein the maximum allowable alignment speed is the corresponding speed obtained by looking up a table for the fork alignment accuracy.

9. The semi-automatic forklift control system based on remote monitoring according to claim 8, characterized in that, The vehicle control unit is also used to respond to the second repeated detection condition and determine that the reason for not meeting the standard is the performance fluctuation of the environmental perception unit. The obstacle confirmation delay is reduced according to the feature point density of the forklift environmental perception unit, and the reduction in obstacle confirmation delay is negatively correlated with the feature point density. The feature point density is the ratio of the effective feature points obtained after preprocessing by the vehicle-mounted processing unit to the volume of the effective detection area. The obstacle confirmation delay is obtained by the perception confidence coefficient, which is the ratio of the feature point density to the preset feature point density. The second repeat detection condition is that after the vehicle control unit completes the adjustment of the end deceleration distance, it re-determines that the control for the forklift's driving phase still does not meet the standard.

10. The semi-automatic forklift control system based on remote monitoring according to claim 9, characterized in that, The vehicle control unit also has a negative correlation function for the perception execution coefficient and the preset obstacle confirmation delay. The vehicle control unit also substitutes the perception confidence coefficient into the negative correlation function to obtain the obstacle confirmation delay.

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