CN118068841B - An intelligent obstacle avoidance system for logistics AGV based on multi-sensor technology - Google Patents
An intelligent obstacle avoidance system for logistics AGV based on multi-sensor technology Download PDFInfo
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Abstract
The invention relates to the technical field of obstacle avoidance of a logistics AGV, in particular to an intelligent obstacle avoidance system of the logistics AGV based on a multi-sensor technology, which comprises an obstacle avoidance management platform, an information acquisition unit, a response blocking unit, an obstacle avoidance performance monitoring unit, a vehicle self evaluation unit, an obstacle avoidance blocking analysis unit, a route monitoring unit and an execution response unit; according to the invention, on the premise that the obstacle avoidance efficiency of the logistics AGV is qualified, analysis is carried out from two points of potential obstacle regulation and control and the movement of the logistics AGV, so that the obstacle avoidance risk situation of the AGV is known, namely, the movement state parameters are subjected to self-movement supervision feedback evaluation analysis, so that the influence degree of the logistics AGV on the obstacle avoidance is reduced, the influence of interference factors is reduced by analyzing in a face mode and combining with the potential obstacle regulation and control, and on the premise that the overall obstacle avoidance of the logistics AGV is normal, the obstacle avoidance risk prediction supervision analysis is carried out on the running risk data, so that the obstacle avoidance efficiency of the logistics AGV is predicted, optimized and adjusted in advance.
Description
Technical Field
The invention relates to the technical field of obstacle avoidance of logistics AGVs, in particular to an intelligent obstacle avoidance system of a logistics AGV based on a multi-sensor technology.
Background
Logistics system technology is an important component in advanced manufacturing technology, and can be seen from the broad meaning analysis of the logistics system technology, the logistics system technology has been developed from the prior simple material handling to the comprehensive technology integrating mechanical design, computer science, management and automatic control technology into a whole today;
The AGV is short for automatic guided transport vehicle, belongs to modern intelligent logistics equipment, is mainly used for carrying unmanned goods, is widely applied to an automatic logistics system along with the gradual progress of logistics technology, but in terms of the prior art, the AGV is blocked by an obstacle in the advancing process, can not timely and effectively avoid safety, further influences the operation safety and the working efficiency of the AGV, and can not analyze the safety efficiency of the current execution strategy of the AGV, further can not timely optimize the treatment, increase the collision risk of the AGV, and can not monitor the AGV, thereby influencing the obstacle avoidance efficiency and the obstacle avoidance stability of the AGV;
In view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an intelligent obstacle avoidance system for a logistics AGV based on a multi-sensor technology, which is used for solving the technical defect that the technical defect is proposed, analyzing from two points of potential obstacle regulation and control and movement of the logistics AGV on the premise that the obstacle avoidance efficiency of the logistics AGV is qualified, so as to know the obstacle avoidance risk situation of the AGV, namely, carrying out self-movement supervision feedback evaluation analysis on movement state parameters, so as to judge whether the movement of the logistics AGV is interfering with the obstacle avoidance, reducing the obstacle avoidance reaction of the logistics AGV and the influence degree of the regulation on the obstacle avoidance, and analyzing in an information fusion mode, namely, analyzing by a surface mode and combining the potential obstacle regulation so as to judge whether the overall obstacle avoidance risk of the logistics AGV is too high, so as to reasonably optimize the logistics AGV, avoid collision of logistics AGVs, reduce the influence of interference factors, and carrying out obstacle avoidance risk prediction supervision analysis on the travelling risk data on the premise that the logistics AGV is normally avoiding the obstacle, so as to predict, optimize and regulate the obstacle avoidance efficiency and the obstacle avoidance stability of logistics AGV in advance.
Preferably, the object of the present invention can be achieved by the following technical solutions: a logistics AGV intelligent obstacle avoidance system based on a multi-sensor technology comprises an obstacle avoidance management platform, an information acquisition unit, a response blocking unit, an obstacle avoidance performance monitoring unit, a vehicle self evaluation unit, an obstacle avoidance blocking analysis unit, a route monitoring unit and an execution response unit;
When the obstacle avoidance management platform generates an operation instruction, the operation instruction is sent to an information acquisition unit and a response blocking unit, the information acquisition unit immediately acquires response risk data and motion state parameters of the logistics AGV after receiving the operation instruction, the response risk data comprises an obstacle avoidance risk value and a response representation value, the motion state parameters comprise a steering deviation value and a state response value, the response risk data and the motion state parameters are respectively sent to an obstacle avoidance performance monitoring unit and a vehicle self-assessment unit, the obstacle avoidance performance monitoring unit immediately carries out obstacle avoidance response delay risk assessment analysis on the response risk data after receiving the response risk data, and sends an obtained qualified signal to the vehicle self-assessment unit and an obtained unqualified signal to an execution response unit;
The response blocking unit immediately acquires blocking regulation data of the logistics AGV after receiving the pipe conveying instruction, wherein the blocking regulation data comprises a response representation value and a short touch risk rate, carries out regulation and interference supervision feedback analysis on the blocking regulation data, and sends an obtained delay risk assessment coefficient B to the obstacle avoidance analysis unit;
the vehicle self-evaluation unit immediately performs self-motion supervision feedback evaluation analysis on the motion state parameters after receiving the qualified signals, sends the obtained safety signals to the obstacle avoidance and obstruction analysis unit, and sends the obtained risk signals to the execution response unit;
The obstacle avoidance and obstruction analysis unit immediately enters information fusion evaluation analysis after receiving the delay risk evaluation coefficient B and the safety signal, sends an obtained normal signal to the route supervision unit, and sends an obtained alarm signal to the execution response unit;
The route supervision unit receives the normal signals, immediately collects running risk data, wherein the running risk data comprises a safety early warning value and a safety avoiding value, carries out obstacle avoidance risk prediction supervision analysis on the running risk data, and sends the obtained early warning signals to the execution response unit.
Preferably, the obstacle avoidance response delay risk assessment analysis process of the obstacle avoidance performance supervision unit is as follows:
Setting a monitoring period, setting the monitoring period as a time threshold, acquiring a barrier avoiding risk value of the logistics AGV in a history m time thresholds, wherein m is a natural number larger than zero, the barrier avoiding risk value represents a ratio of the number of barrier avoiding failures in the history barrier avoiding times, then setting the ratio to a product value obtained after data normalization processing of the barrier avoiding delay early warning times, wherein the distance between the logistics AGV and the barrier is smaller than the number corresponding to a preset threshold when the barrier avoiding starts to early warning, setting an orthogonal coordinate system with the number as an X axis, setting a barrier avoiding risk value as a Y axis, drawing a barrier avoiding risk value curve in a description mode, further acquiring a ratio of the length of a line segment above the barrier avoiding risk value curve to the length of a line segment below the preset barrier avoiding risk value curve, setting the ratio to a barrier avoiding efficiency risk rate, and comparing the barrier avoiding efficiency risk rate with a preset barrier efficiency rate threshold stored in the barrier avoiding efficiency rate by the internal record of the barrier efficiency rate.
If the ratio between the obstacle avoidance efficiency risk rate and the preset obstacle avoidance efficiency risk rate threshold is smaller than 1, generating a qualified signal;
if the ratio of the obstacle avoidance efficiency risk rate to the preset obstacle avoidance efficiency risk rate threshold is greater than or equal to 1, generating a disqualified signal.
Preferably, the regulatory interference supervision feedback analysis process of the response blocking unit is as follows:
S1: obtaining a response representation value of the logistic AGV in the time threshold, wherein the response representation value represents the ratio of the number of sensors corresponding to the preset threshold to the total number of sensors, which is obtained by carrying out data normalization processing on the part of the maximum operation temperature value of each sensor in the historical logistic AGV exceeding the initial operation temperature value and the duration;
s2: acquiring the total collision times of the logistics AGVs in a time threshold, acquiring a product value obtained by carrying out data normalization processing on the oxidation area and the contact minimum area of the internal circuit ports of the logistics AGVs in the time threshold, setting the product value as an interruption risk value, setting the product value obtained by carrying out data normalization processing on the total collision times and the interruption risk value as a short-touch risk rate, and respectively marking a response representation value and the short-touch risk rate as XB and DC;
S3: according to the formula Obtaining a delay risk assessment coefficient, wherein a1 and a2 are preset scale factor coefficients of a response representation value and a short touch risk rate respectively, a1 and a2 are both larger than zero, a3 is a preset correction factor coefficient, the value is 2.191, and B is the delay risk assessment coefficient.
Preferably, the self-motion supervision feedback evaluation analysis process of the vehicle self-evaluation unit is as follows:
T1: acquiring an actual steering maximum angle of the logistics AGV in a time threshold, setting a part of the actual steering maximum angle which is lower than a preset steering angle threshold as a steering error value, acquiring a part of the rotational friction force of a rotating shaft of the logistics AGV in the time threshold which exceeds the preset threshold, setting the part as a friction resistance value, and setting a product value obtained by carrying out data normalization processing on the steering error value and the friction resistance value as a steering deviation value;
t2: acquiring a state reaction value of the logistics AGV in a time threshold, wherein the state reaction value represents a product value obtained by carrying out data normalization processing on the fluctuation times of the operation voltage of the logistics AGV and a reactive power average value, and then carrying out data normalization processing on the product value and an over-temperature operation value, and the over-temperature operation value represents a ratio of times that the operation temperature exceeds a preset operation temperature by a time length longer than a preset time length in the total historical operation times of the logistics AGV;
T3: comparing the steering deviation value and the state response value with a preset steering deviation value threshold value and a preset state response value threshold value which are recorded and stored in the steering deviation value and the state response value:
if the steering deviation value is smaller than a preset steering deviation value threshold value and the state response value is smaller than a preset state response value threshold value, generating a safety signal;
and if the steering deviation value is greater than or equal to a preset steering deviation value threshold value or the state response value is greater than or equal to a preset state response value threshold value, generating a risk signal.
Preferably, the information fusion evaluation analysis process of the obstacle avoidance and blocking analysis unit is as follows:
acquiring a steering deviation value and a state response value in a time threshold, and acquiring an optimization demand evaluation coefficient B in the time threshold, wherein the steering deviation value and the state response value are respectively marked as ZP and ZF;
according to the formula Obtaining a potential risk assessment coefficient, wherein f1, f2 and f3 are respectively preset weight factor coefficients of a steering deviation value, a state reaction value and an optimization demand assessment coefficient, f4 is a preset fault tolerance factor coefficient, f1, f2, f3 and f4 are all larger than zero, R is a potential risk assessment coefficient, and the potential risk assessment coefficient R is compared with a preset potential risk assessment coefficient threshold value recorded and stored in the potential risk assessment coefficient R:
if the ratio between the potential risk assessment coefficient R and the preset potential risk assessment coefficient threshold is smaller than 1, generating a normal signal;
And if the ratio between the potential risk assessment coefficient R and the preset potential risk assessment coefficient threshold value is more than or equal to 1, generating an alarm signal.
Preferably, the route supervision unit predicts the obstacle avoidance risk and supervises the analysis process as follows:
Acquiring a running time period of the logistics AGV in a time threshold, marking the running time period as analysis time period, acquiring obstacle avoidance times of the logistics AGV in the analysis time period, acquiring obstacle avoidance parameters of each obstacle avoidance time in the analysis time period, wherein the obstacle avoidance parameters comprise an early warning risk distance and an obstacle avoidance safety distance, the early warning risk distance represents a running path distance between the logistics AGV and an obstacle at the obstacle avoidance early warning moment of the logistics AGV, the obstacle avoidance safety distance represents a minimum straight line distance between the logistics AGV and the obstacle, the obstacle avoidance time is taken as an X axis, a rectangular coordinate system is established by taking the early warning risk distance and the obstacle avoidance safety distance as Y axes respectively, an early warning risk distance curve and an obstacle avoidance safety distance curve are drawn respectively in a dot drawing mode, and further an area surrounded by the early warning risk distance curve and the X axis and an area surrounded by the obstacle avoidance safety distance curve and are respectively set as a safety early warning value and a safety avoidance value;
Comparing the safety early warning value and the safety avoidance value with a preset safety early warning value threshold value and a preset safety avoidance value threshold value which are recorded and stored in the safety early warning value and the safety avoidance value, and analyzing the safety early warning value and the safety avoidance value:
If the safety early warning value is greater than or equal to a preset safety early warning value threshold or the safety avoidance value is greater than or equal to a preset safety avoidance value threshold, no signal is generated;
if the safety early warning value is smaller than the preset safety early warning value threshold value and the safety avoidance value is smaller than the preset safety avoidance value threshold value, generating an early warning signal.
The beneficial effects of the invention are as follows:
(1) According to the invention, the obstacle avoidance risk of the logistics AGV is analyzed in a point-to-surface mode, so that the obstacle avoidance efficiency of the logistics AGV is improved, and the obstacle avoidance efficiency is analyzed from the point of the logistics AGV, namely, obstacle avoidance response delay risk assessment analysis is performed on response risk data, so as to judge whether the obstacle avoidance risk of the logistics AGV is too high or not, so that reasonable optimization processing is performed according to information feedback conditions, the obstacle avoidance response performance of the logistics AGV is improved, and meanwhile, the optimization adjustment of an obstacle avoidance decision of the logistics AGV is facilitated in time;
(2) According to the invention, on the premise that the obstacle avoidance efficiency of the logistics AGV is qualified, analysis is carried out from two points of potential obstacle regulation and control and the movement of the logistics AGV, so that the obstacle avoidance risk situation of the AGV is known, namely, the movement state parameter is subjected to self-movement supervision feedback evaluation analysis, so that the obstacle avoidance response of the logistics AGV and the influence degree of the regulation on the obstacle avoidance are reduced, and analysis is carried out in an information fusion mode, namely, the analysis is carried out in a face mode and combined with the potential obstacle avoidance regulation, so that whether the overall obstacle avoidance risk of the logistics AGV is too high is judged, the logistics AGV is subjected to reasonable optimization treatment, the collision of the logistics AGV is avoided, the influence of interference factors is reduced, and on the premise that the overall obstacle avoidance of the logistics AGV is normal, obstacle avoidance risk prediction supervision analysis is carried out on the driving risk data so as to judge the obstacle avoidance risk trend, so that the obstacle avoidance efficiency and the obstacle avoidance stability of the logistics AGV are predicted, optimized and adjusted in advance.
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The invention is further described below with reference to the accompanying drawings;
FIG. 1 is a flow chart of the system of the present invention;
fig. 2 is a partial reference diagram of an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: referring to fig. 1 to 2, the present invention is a logistics AGV intelligent obstacle avoidance system based on a multi-sensor technology, which includes an obstacle avoidance management platform, an information acquisition unit, a response blocking unit, an obstacle avoidance performance monitoring unit, a vehicle self-evaluation unit, an obstacle avoidance blocking analysis unit, a route monitoring unit, and an execution response unit, wherein the obstacle avoidance management platform is in unidirectional communication connection with the information acquisition unit and the response blocking unit, the information acquisition unit is in unidirectional communication connection with the obstacle avoidance performance monitoring unit and the vehicle self-evaluation unit, the obstacle avoidance performance monitoring unit is in unidirectional communication connection with the execution response unit and the vehicle self-evaluation unit, the vehicle self-evaluation unit is in unidirectional communication connection with the obstacle avoidance blocking analysis unit, the obstacle avoidance blocking analysis unit is in unidirectional communication connection with the route monitoring unit and the execution response unit, and the route monitoring unit is in unidirectional communication connection with the execution response unit;
When the obstacle avoidance management platform generates an operation instruction, the operation instruction is sent to the information acquisition unit and the response blocking unit, the information acquisition unit immediately acquires response risk data and motion state parameters of the logistics AGV after receiving the operation instruction, the response risk data comprises an obstacle avoidance risk value and a response representation value, the motion state parameters comprise a steering deviation value and a state response value, the response risk data and the motion state parameters are respectively sent to the obstacle avoidance performance monitoring unit and the vehicle self evaluation unit, the obstacle avoidance performance monitoring unit immediately carries out obstacle avoidance response delay risk evaluation analysis on the response risk data after receiving the response risk data so as to judge whether the obstacle avoidance risk of the logistics AGV is too high or not, so that reasonable optimization processing is carried out according to information feedback conditions to improve the obstacle avoidance performance of the logistics AGV, and the specific obstacle avoidance response delay risk evaluation analysis process is as follows:
Setting a monitoring period, setting the monitoring period as a time threshold, acquiring a barrier avoiding risk value of the logistics AGV in a history m time thresholds, wherein m is a natural number larger than zero, the barrier avoiding risk value represents a ratio of the number of barrier avoiding failures in the history barrier avoiding times, then setting the ratio to a product value obtained after data normalization processing of the barrier avoiding delay early warning times, wherein the distance between the logistics AGV and the barrier is smaller than the number corresponding to a preset threshold when the barrier avoiding starts to early warning, setting an orthogonal coordinate system with the number as an X axis, setting a barrier avoiding risk value as a Y axis, drawing a barrier avoiding risk value curve in a description mode, further acquiring a ratio of the length of a line segment above the barrier avoiding risk value curve to the length of a line segment below the preset barrier avoiding risk value curve, setting the ratio to a barrier avoiding efficiency risk rate, and comparing the barrier avoiding efficiency risk rate with a preset barrier efficiency rate threshold stored in the barrier avoiding efficiency rate by the internal record of the barrier efficiency rate.
If the ratio between the obstacle avoidance efficiency risk rate and the preset obstacle avoidance efficiency risk rate threshold is smaller than 1, generating a qualified signal, and sending the qualified signal to a vehicle self-evaluation unit;
if the ratio between the obstacle avoidance efficiency risk rate and the preset obstacle avoidance efficiency risk rate threshold is greater than or equal to 1, generating an unqualified signal, sending the unqualified signal to an execution response unit, and immediately making preset early warning operation corresponding to the unqualified signal after the execution response unit receives the unqualified signal, so as to optimize and adjust an obstacle avoidance decision of the logistics AGV in time, and improve the obstacle avoidance efficiency of the logistics AGV;
The response blocking unit immediately collects blocking regulation and control data of the logistics AGV after receiving the pipe conveying instruction, the blocking regulation and control data comprise response representation values and short touch risk rates, and the blocking regulation and control data are subjected to regulation and control interference supervision feedback analysis so as to know the influence condition of blocking regulation and control factors on obstacle avoidance of the logistics AGV, so that data support is provided for subsequent management, and the specific regulation and control interference supervision feedback analysis process is as follows:
Obtaining a response representation value of the logistic AGV in the time threshold, wherein the response representation value represents the ratio of the number of sensors corresponding to the preset threshold to the total number of sensors obtained by carrying out data normalization processing on the product value of the part of the maximum operation temperature value of each sensor in the historical logistic AGV exceeding the initial operation temperature value and the duration, and the larger the value of the response representation value is, the larger the obstacle avoidance delay risk of the logistic AGV is;
Acquiring the total collision times of the logistics AGVs in a time threshold, simultaneously acquiring a product value obtained by carrying out data normalization processing on the oxidation area and the contact minimum area of the internal circuit ports of the logistics AGVs in the time threshold, setting the product value as an interruption risk value, setting the product value obtained by carrying out data normalization processing on the total collision times and the interruption risk value as a short-touch risk rate, and indicating that the larger the value of the short-touch risk rate is, the larger the obstacle avoidance delay risk of the logistics AGVs is, and respectively marking the response representation value and the short-touch risk rate as XB and DC;
according to the formula Obtaining a delay risk assessment coefficient, wherein a1 and a2 are preset scale factor coefficients of a response representation value and a short touch risk rate respectively, the scale factor coefficients are used for correcting deviation of various parameters in a formula calculation process, so that a calculation result is more accurate, a1 and a2 are both larger than zero, a3 is a preset correction factor coefficient, the value is 2.191, B is the delay risk assessment coefficient, and the delay risk assessment coefficient B is sent to an obstacle avoidance analysis unit.
Embodiment two: the vehicle self-assessment unit immediately carries out self-motion supervision feedback assessment analysis on the motion state parameters after receiving the qualified signals so as to judge whether the self motion of the logistics AGV causes interference on obstacle avoidance or not, so that timely early warning feedback management is carried out, the collision risk of the logistics AGV is reduced, the transportation safety of the logistics AGV is improved, and the specific self-motion supervision feedback assessment analysis process is as follows:
The method comprises the steps of obtaining an actual steering maximum angle of a logistics AGV in a time threshold, setting a part of the actual steering maximum angle lower than a preset steering angle threshold as a steering error value, obtaining a part of the rotating friction force of a logistics AGV rotating shaft in the time threshold exceeding the preset threshold, setting the part as a friction obstruction value, and setting a product value obtained by carrying out data normalization processing on the steering error value and the friction obstruction value as a steering deviation value, wherein the larger the value of the steering deviation value is, the higher the obstacle avoidance risk of the logistics AGV in self motion is;
Acquiring a state reaction value of the logistics AGV in a time threshold, wherein the state reaction value represents a product value obtained by carrying out data normalization processing on the fluctuation times of the running voltage of the logistics AGV and a reactive power average value, and then carrying out data normalization processing on the product value and an over-temperature running value, the over-temperature running value represents a ratio of times that the running temperature exceeds the preset running temperature by a time period longer than the preset time period in the total historical running times of the logistics AGV, and the larger the value of the state reaction value is, the higher the obstacle avoidance risk of the logistics AGV is;
Comparing the steering deviation value and the state response value with a preset steering deviation value threshold value and a preset state response value threshold value which are recorded and stored in the steering deviation value and the state response value:
if the steering deviation value is smaller than a preset steering deviation value threshold value and the state reaction value is smaller than a preset state reaction value threshold value, generating a safety signal, and sending the safety signal to an obstacle avoidance and resistance analysis unit;
If the steering deviation value is greater than or equal to a preset steering deviation value threshold value or the state reaction value is greater than or equal to a preset state reaction value threshold value, generating a risk signal, and sending the risk signal to an execution response unit, wherein the execution response unit immediately makes a preset early warning operation corresponding to the risk signal after receiving the risk signal, so that the logistics AGV can be maintained and managed in time, and the obstacle avoidance reaction of the logistics AGV and the influence degree of regulation on obstacle avoidance can be reduced;
After receiving the delay risk assessment coefficient B and the safety signal, the obstacle avoidance and obstruction analysis unit immediately enters information fusion assessment analysis to judge whether the overall obstacle avoidance risk of the logistics AGV is too high, so that reasonable optimization processing is carried out on the logistics AGV, and the specific information fusion assessment analysis process is as follows:
acquiring a steering deviation value and a state response value in a time threshold, and acquiring an optimization demand evaluation coefficient B in the time threshold, wherein the steering deviation value and the state response value are respectively marked as ZP and ZF;
according to the formula Obtaining a potential risk assessment coefficient, wherein f1, f2 and f3 are respectively preset weight factor coefficients of a steering deviation value, a state reaction value and an optimization demand assessment coefficient, f4 is a preset fault tolerance factor coefficient, f1, f2, f3 and f4 are all larger than zero, R is a potential risk assessment coefficient, and the potential risk assessment coefficient R is compared with a preset potential risk assessment coefficient threshold value recorded and stored in the potential risk assessment coefficient R:
If the ratio between the potential risk assessment coefficient R and the preset potential risk assessment coefficient threshold is smaller than 1, generating a normal signal, and sending the normal signal to a route supervision unit;
if the ratio between the potential risk assessment coefficient R and the preset potential risk assessment coefficient threshold is greater than or equal to 1, generating an alarm signal, sending the alarm signal to an execution response unit, and immediately making a preset early warning operation corresponding to the alarm signal after the execution response unit receives the alarm signal, so that maintenance and management are carried out on the logistics AGVs in time, the obstacle avoidance efficiency of the logistics AGVs is improved, collision of the logistics AGVs is avoided, and the influence of interference factors is reduced;
The route supervision unit receives the running risk data collected immediately after the normal signal, the running risk data comprises a safety early warning value and a safety avoiding value, and the running risk data is subjected to obstacle avoidance risk prediction supervision analysis so as to judge the obstacle avoidance risk trend of the logistics AGV, so that the logistics AGV is predicted, optimized and adjusted in advance, the obstacle avoidance efficiency and the obstacle avoidance stability of the logistics AGV are improved, and the specific obstacle avoidance risk prediction supervision analysis process is as follows:
Acquiring a running time period of the logistics AGVs in a time threshold, marking the running time period as analysis time length, acquiring the obstacle avoidance times of the logistics AGVs in the analysis time length, acquiring the obstacle avoidance parameters of each obstacle avoidance time in the analysis time length, wherein the obstacle avoidance parameters comprise an early warning risk distance and an obstacle avoidance safety distance, the early warning risk distance represents a running path distance between the logistics AGVs and an obstacle at the obstacle avoidance early warning moment, the obstacle avoidance safety distance represents a minimum straight line distance between the logistics AGVs and the obstacle, the obstacle avoidance time is taken as an X axis, a rectangular coordinate system is established by taking the early warning risk distance and the obstacle avoidance safety distance as Y axes respectively, an early warning risk distance curve and an obstacle avoidance safety distance curve are drawn respectively in a description mode, and then an area surrounded by the early warning risk distance curve and the X axis and an area surrounded by the obstacle avoidance safety distance curve and the X axis are respectively set as a safety early warning value and a safety avoidance value, and the safety avoidance value are required to be explained, and the safety early warning value and the safety avoidance value are influence parameters reflecting the logistics risk avoidance trend are beneficial to predicting the logistics AGVs in advance;
Comparing the safety early warning value and the safety avoidance value with a preset safety early warning value threshold value and a preset safety avoidance value threshold value which are recorded and stored in the safety early warning value and the safety avoidance value, and analyzing the safety early warning value and the safety avoidance value:
If the safety early warning value is greater than or equal to a preset safety early warning value threshold or the safety avoidance value is greater than or equal to a preset safety avoidance value threshold, no signal is generated;
If the safety early warning value is smaller than a preset safety early warning value threshold value and the safety avoidance value is smaller than a preset safety avoidance value threshold value, generating an early warning signal, sending the early warning signal to an execution response unit, and immediately making a preset early warning operation corresponding to the early warning signal after the execution response unit receives the early warning signal, so that the logistics AGV can be reasonably adjusted, collision of the logistics AGV in the subsequent running process is avoided, the collision risk of the logistics AGV is predicted, and further the obstacle avoidance efficiency of the logistics AGV is improved;
In summary, the invention analyzes the obstacle avoidance risk of the logistics AGV from the point-to-the-face mode, and further improves the obstacle avoidance efficiency of the logistics AGV, and analyzes the point of the obstacle avoidance efficiency of the logistics AGV from the point, namely, the obstacle avoidance response delay risk assessment analysis is carried out on response risk data, so as to judge whether the obstacle avoidance risk of the logistics AGV is too high, so that reasonable optimization processing is carried out according to information feedback conditions, the obstacle avoidance response performance of the logistics AGV is improved, meanwhile, timely optimization processing is carried out on the obstacle avoidance decision of the logistics AGV, and under the premise that the obstacle avoidance efficiency of the logistics AGV is qualified, the two points of potential obstacle avoidance regulation and control and logistics AGV self movement are analyzed, so that the situation of the obstacle avoidance risk of the AGV is known, namely, the self-movement supervision feedback assessment analysis is carried out on movement state parameters, so as to judge whether the movement of the logistics AGV self-movement is interference caused to the obstacle avoidance, so as to reduce the influence degree of the obstacle avoidance of logistics AGV self obstacle avoidance reaction and regulation and control on the obstacle avoidance, and analyze through the information fusion mode, namely, the way of carrying out on the reasonable optimization processing of the overall obstacle avoidance risk of the logistics AGV is carried out through the face mode, so that the logistics AGV is carried out on the reasonable optimization processing on the obstacle avoidance decision.
The size of the threshold is set for ease of comparison, and regarding the size of the threshold, the number of cardinalities is set for each set of sample data depending on how many sample data are and the person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected.
The above formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and coefficients in the formulas are set by a person skilled in the art according to practical situations, and the above is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art is within the technical scope of the present invention, and the technical scheme and the inventive concept according to the present invention are equivalent to or changed and are all covered in the protection scope of the present invention.
Claims (2)
1. The logistics AGV intelligent obstacle avoidance system based on the multi-sensor technology is characterized by comprising an obstacle avoidance management platform, an information acquisition unit, a response blocking unit, an obstacle avoidance performance monitoring unit, a vehicle self evaluation unit, an obstacle avoidance blocking analysis unit, a route monitoring unit and an execution response unit;
When the obstacle avoidance management platform generates an operation instruction, the operation instruction is sent to an information acquisition unit and a response blocking unit, the information acquisition unit immediately acquires response risk data and motion state parameters of the logistics AGV after receiving the operation instruction, the response risk data comprises an obstacle avoidance risk value and a response representation value, the motion state parameters comprise a steering deviation value and a state response value, the response risk data and the motion state parameters are respectively sent to an obstacle avoidance performance monitoring unit and a vehicle self-assessment unit, the obstacle avoidance performance monitoring unit immediately carries out obstacle avoidance response delay risk assessment analysis on the response risk data after receiving the response risk data, and sends an obtained qualified signal to the vehicle self-assessment unit and an obtained unqualified signal to an execution response unit;
The response blocking unit immediately acquires blocking regulation data of the logistics AGV after receiving the pipe conveying instruction, wherein the blocking regulation data comprises a response representation value and a short touch risk rate, carries out regulation and interference supervision feedback analysis on the blocking regulation data, and sends an obtained delay risk assessment coefficient B to the obstacle avoidance analysis unit;
the vehicle self-evaluation unit immediately performs self-motion supervision feedback evaluation analysis on the motion state parameters after receiving the qualified signals, sends the obtained safety signals to the obstacle avoidance and obstruction analysis unit, and sends the obtained risk signals to the execution response unit;
The obstacle avoidance and obstruction analysis unit immediately enters information fusion evaluation analysis after receiving the delay risk evaluation coefficient B and the safety signal, sends an obtained normal signal to the route supervision unit, and sends an obtained alarm signal to the execution response unit;
The route supervision unit immediately collects running risk data after receiving the normal signal, wherein the running risk data comprises a safety early warning value and a safety avoiding value, carries out obstacle avoidance risk prediction supervision analysis on the running risk data, and sends the obtained early warning signal to the execution response unit;
the obstacle avoidance response delay risk assessment and analysis process of the obstacle avoidance performance supervision unit is as follows:
Setting a monitoring period, setting the monitoring period as a time threshold, acquiring a barrier avoiding risk value of the logistics AGV in a history m time thresholds, wherein m is a natural number larger than zero, the barrier avoiding risk value represents a ratio of the number of barrier avoiding failures in the history barrier avoiding times, then setting the ratio to a product value obtained after data normalization processing of the barrier avoiding delay early warning times, wherein the distance between the logistics AGV and the barrier is smaller than the number corresponding to a preset threshold when the barrier avoiding starts to early warning, setting an orthogonal coordinate system with the number as an X axis, setting a barrier avoiding risk value as a Y axis, drawing a barrier avoiding risk value curve in a description mode, further acquiring a ratio of the length of a line segment above the barrier avoiding risk value curve to the length of a line segment below the preset barrier avoiding risk value curve, setting the ratio to a barrier avoiding efficiency risk rate, and comparing the barrier avoiding efficiency risk rate with a preset barrier efficiency rate threshold stored in the barrier avoiding efficiency rate by the internal record of the barrier efficiency rate.
If the ratio between the obstacle avoidance efficiency risk rate and the preset obstacle avoidance efficiency risk rate threshold is smaller than 1, generating a qualified signal;
If the ratio between the obstacle avoidance efficiency risk rate and the preset obstacle avoidance efficiency risk rate threshold is greater than or equal to 1, generating a disqualification signal;
The regulation and control interference supervision feedback analysis process of the response blocking unit is as follows:
S1: obtaining a response representation value of the logistic AGV in the time threshold, wherein the response representation value represents the ratio of the number of sensors corresponding to the preset threshold to the total number of sensors, which is obtained by carrying out data normalization processing on the part of the maximum operation temperature value of each sensor in the historical logistic AGV exceeding the initial operation temperature value and the duration;
s2: acquiring the total collision times of the logistics AGVs in a time threshold, acquiring a product value obtained by carrying out data normalization processing on the oxidation area and the contact minimum area of the internal circuit ports of the logistics AGVs in the time threshold, setting the product value as an interruption risk value, setting the product value obtained by carrying out data normalization processing on the total collision times and the interruption risk value as a short-touch risk rate, and respectively marking a response representation value and the short-touch risk rate as XB and DC;
S3: according to the formula Obtaining a delay risk assessment coefficient, wherein a1 and a2 are respectively a response representation value and a preset scale factor coefficient of a short touch risk rate, a1 and a2 are both larger than zero, a3 is a preset correction factor coefficient, the value is 2.191, and B is the delay risk assessment coefficient;
The self-motion supervision feedback evaluation analysis process of the vehicle self-evaluation unit is as follows:
T1: acquiring an actual steering maximum angle of the logistics AGV in a time threshold, setting a part of the actual steering maximum angle which is lower than a preset steering angle threshold as a steering error value, acquiring a part of the rotational friction force of a rotating shaft of the logistics AGV in the time threshold which exceeds the preset threshold, setting the part as a friction resistance value, and setting a product value obtained by carrying out data normalization processing on the steering error value and the friction resistance value as a steering deviation value;
t2: acquiring a state reaction value of the logistics AGV in a time threshold, wherein the state reaction value represents a product value obtained by carrying out data normalization processing on the fluctuation times of the operation voltage of the logistics AGV and a reactive power average value, and then carrying out data normalization processing on the product value and an over-temperature operation value, and the over-temperature operation value represents a ratio of times that the operation temperature exceeds a preset operation temperature by a time length longer than a preset time length in the total historical operation times of the logistics AGV;
T3: comparing the steering deviation value and the state response value with a preset steering deviation value threshold value and a preset state response value threshold value which are recorded and stored in the steering deviation value and the state response value:
if the steering deviation value is smaller than a preset steering deviation value threshold value and the state response value is smaller than a preset state response value threshold value, generating a safety signal;
if the steering deviation value is greater than or equal to a preset steering deviation value threshold value or the state response value is greater than or equal to a preset state response value threshold value, generating a risk signal;
The information fusion evaluation analysis process of the obstacle avoidance and resistance analysis unit is as follows:
acquiring a steering deviation value and a state response value in a time threshold, and acquiring an optimization demand evaluation coefficient B in the time threshold, wherein the steering deviation value and the state response value are respectively marked as ZP and ZF;
according to the formula Obtaining a potential risk assessment coefficient, wherein f1, f2 and f3 are respectively preset weight factor coefficients of a steering deviation value, a state reaction value and an optimization demand assessment coefficient, f4 is a preset fault tolerance factor coefficient, f1, f2, f3 and f4 are all larger than zero, R is a potential risk assessment coefficient, and the potential risk assessment coefficient R is compared with a preset potential risk assessment coefficient threshold value recorded and stored in the potential risk assessment coefficient R:
if the ratio between the potential risk assessment coefficient R and the preset potential risk assessment coefficient threshold is smaller than 1, generating a normal signal;
And if the ratio between the potential risk assessment coefficient R and the preset potential risk assessment coefficient threshold value is more than or equal to 1, generating an alarm signal.
2. The logistics AGV intelligent obstacle avoidance system based on the multi-sensor technology according to claim 1, wherein the obstacle avoidance risk prediction, supervision and analysis process of the route supervision unit is as follows:
Acquiring a running time period of the logistics AGV in a time threshold, marking the running time period as analysis time period, acquiring obstacle avoidance times of the logistics AGV in the analysis time period, acquiring obstacle avoidance parameters of each obstacle avoidance time in the analysis time period, wherein the obstacle avoidance parameters comprise an early warning risk distance and an obstacle avoidance safety distance, the early warning risk distance represents a running path distance between the logistics AGV and an obstacle at the obstacle avoidance early warning moment of the logistics AGV, the obstacle avoidance safety distance represents a minimum straight line distance between the logistics AGV and the obstacle, the obstacle avoidance time is taken as an X axis, a rectangular coordinate system is established by taking the early warning risk distance and the obstacle avoidance safety distance as Y axes respectively, an early warning risk distance curve and an obstacle avoidance safety distance curve are drawn respectively in a dot drawing mode, and further an area surrounded by the early warning risk distance curve and the X axis and an area surrounded by the obstacle avoidance safety distance curve and are respectively set as a safety early warning value and a safety avoidance value;
Comparing the safety early warning value and the safety avoidance value with a preset safety early warning value threshold value and a preset safety avoidance value threshold value which are recorded and stored in the safety early warning value and the safety avoidance value, and analyzing the safety early warning value and the safety avoidance value:
If the safety early warning value is greater than or equal to a preset safety early warning value threshold or the safety avoidance value is greater than or equal to a preset safety avoidance value threshold, no signal is generated;
if the safety early warning value is smaller than the preset safety early warning value threshold value and the safety avoidance value is smaller than the preset safety avoidance value threshold value, generating an early warning signal.
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