CN115271118A - Garbage recycling method and system for unmanned sweeper - Google Patents
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Abstract
The invention relates to a garbage recycling method and system for an unmanned sweeper. This system includes unmanned motor sweeper, cloud scheduling platform, unmanned motor sweeper include: the system comprises a dustbin capacity sensor, a whole VCU, an automatic driving controller, a vehicle-mounted OBU, a sensing camera, a laser radar, a combined navigation system, a cleaning mechanism, a traveling mechanism, a vehicle body framework and an exterior assembly; the unmanned sweeper is connected with the cloud scheduling platform through an Ethernet. The invention realizes the scheduling work of the unmanned sweeper in the park, improves the sweeping efficiency, exerts the working energy efficiency of the unmanned sweeper to the maximum level, improves the utilization rate of the unmanned sweeper, reduces the operation cost of the park and realizes the maximization of the yield and the benefit.
Description
Technical Field
The invention relates to the technical field of unmanned sweeper, in particular to a garbage recycling method and system of an unmanned sweeper.
Background
At present, after the cleaning work of an unmanned sweeper in the market in a designated area is finished, when a vehicle returns to a station, sanitation personnel at the station clean garbage in a dust box of the sweeper, and after the garbage is dumped, the sanitation personnel issue an instruction again and assign the unmanned sweeper to the corresponding area for cleaning.
The garbage cleaning vehicle is characterized in that corresponding garbage stations are arranged in a large park and a scenic spot, after the unmanned sweeper finishes sweeping work in a designated area, the unmanned sweeper returns to the garbage stations, corresponding sanitation workers clean garbage, if the garbage sweeper in the surrounding districts cleans the garbage sweeper and returns to the stations, the garbage sweeper needs to wait, and after the sanitation workers clean the garbage, the next cleaning operation is carried out.
The prior art has the following disadvantages: 1. the plurality of unmanned cleaning vehicles cannot be planned, so that the unmanned cleaning vehicles wait after returning to a garbage recovery station after cleaning is finished, and wait for sanitation personnel to clean garbage; 2. after the vehicle is cleaned, the vehicle returns to a garbage cleaning point, and a new cleaning task cannot be performed before the vehicle is cleaned, so that the cleaning efficiency is influenced.
Disclosure of Invention
In view of the defects of the prior art, the invention provides a garbage recycling method and system for an unmanned sweeper, which not only realize the scheduling work of the unmanned sweeper in a park, improve the sweeping efficiency, bring the work energy efficiency of the unmanned sweeper to the maximum level, but also improve the utilization rate of the unmanned sweeper, reduce the operation cost of the park and realize the maximization of the yield and the benefit.
In order to achieve the above objects and other related objects, the present invention provides technical solutions as follows;
the method for recycling the garbage of the unmanned sweeper is characterized by comprising the following steps of:
step S1: based on the garden map information, the cloud scheduling platform divides the garden into N1-nIndividual area, garbage collection site a1Obstacles, obstaclesM；
Step S2: the garbage is recovered to the station a by avoiding the barrier M1And N1-nThree points to be fitted are respectively arranged between the end points of the regions, and the three point sets are represented as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) Setting a cleaning planning path;
and step S3: based on N areas of the park, the cloud scheduling platform sends out cleaning instructions, and a plurality of unmanned cleaning vehicles recover the site a from the rubbish1Starting, running to N areas according to a planned path, and cleaning each appointed area;
and step S4: the method comprises the following steps that an unmanned sweeper runs on the basis of a planned path, a sensing camera of the unmanned sweeper identifies and processes garbage in a cleaning area, meanwhile, identified garbage information is uploaded to a cloud scheduling platform through an Ethernet, the cloud scheduling platform distinguishes and processes the received garbage information, if the garbage amount in a specified area exceeds the single-vehicle cleaning capacity, the cloud scheduling platform schedules idle vehicles from the nearest specified area for supplementary cleaning, if the garbage amount in the current cleaning area is less, the cloud platform issues a scheduling instruction after the current cleaning work is finished, and the unmanned sweeper is scheduled to go to a corresponding busy area;
step S5: the automatic driving controller judges a garbage capacity signal transmitted by the garbage can capacity sensor, and if the garbage can capacity exceeds a set value, a garbage dumping instruction is sent back to the cloud scheduling platform;
step S6: the cloud scheduling platform calculates and recycles the site a according to the position of the unmanned sweeper1Avoiding the barrier M, and recovering the garbage to the station a1And N1-nThree points to be fitted are respectively arranged between the end points of the regions, and the three point sets are represented as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) Setting a path for the unmanned sweeper to return to the garage;
step S7: the unmanned sweeper returns the garbage to the warehouse according to the warehouse returning path, the cloud scheduling platform issues a new cleaning instruction to the unmanned sweeper again, and the unmanned sweeper continues to execute a new cleaning task.
Further, in step S2, the setting of the cleaning planned path includes the following steps:
step S21, based on cubic function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n, three point sets denoted as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) To N, to1End of area (S)1,S2) And (S)2,S3) Fitting is performed to obtain the following function:
y1=ax1 3+bx1 2+cx1+ d and y3=jx3 3+kx3 2+mx3+n，
Since the function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n all pass through point S2We can get:
y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n；
step S22, for y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2The first derivative is obtained by + n: 3ax2 2+2bx2+c=3jx2 2+2kx2+ m, then for function y1And function y3Second order derivation is performed separately, with the following functions: 6ax1+2b =0 and 6jx3+2k =0, polynomial coefficients (a, b, c, d, j, k, m, n) calculated by the above algebraic equation and determining the set of points to determine two segments of cubic splines;
step S23, using the same algorithm to carry out comparison on N2-nAnd solving the regional end point to obtain an optimal planned route, and finally respectively issuing the optimal route to the corresponding unmanned cleaning.
Further, in step S6, the setting of the route for the unmanned sweeping vehicle to return to the garage includes the following steps:
s61, the cloud scheduling platform calculates waiting time T according to the number of the garbage-cleaning vehicles fed back by the garbage recovery station1；
Step S62, based on the cubic function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n, three point sets denoted as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) To N, to1End of area (S)1,S2) And (S)2,S3) Fitting was performed, taking the following function:
y1=ax1 3+bx1 2+cx1+ d and y3=jx3 3+kx3 2+mx3+n，
Since the function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n all pass through point S2We can get:
y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n；
step S63, to ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n=y2And calculating a first derivative, respectively performing second derivative on the functions y1 and y3 in order to ensure the optimization of the path between the S1 point and the S3 point, and making the obtained second derivative be zero so as to obtain the following functions: 6ax1+2b =0 and 6jx3+2k =0, calculated by the above equation and given set of points to determine the polynomial coefficients (a, b, c, d, j, k, m, n) of the two-segment cubic spline;
step S64, using the same algorithm to carry out comparison on N2-nSolving the regional terminal to obtain an optimal planned route, and finally respectively issuing the optimal warehouse returning paths to the corresponding unmanned sweeper;
step (ii) ofS65, the cloud scheduling platform calculates a database returning distance L according to the optimal database returning path1；
S66, the cloud scheduling platform returns the warehouse distance L1Need waiting time T1Planning the vehicle speed, and calculating the optimal speed V of the vehicle returning to the garage according to the formula V = L/T1；
And S67, the cloud scheduling platform issues the optimal speed to the vehicle end VCU through the Ethernet, the vehicle end VCU adjusts the speed according to the received speed, and the unmanned sweeper returns to the warehouse for cleaning according to the adjusted speed.
The invention has the following positive effects:
the invention realizes the dispatching work of the unmanned sweeper in the park, improves the sweeping efficiency, exerts the working energy efficiency of the unmanned sweeper to the maximum level, improves the utilization rate of the unmanned sweeper, reduces the operation cost of the park and realizes the maximization of the yield and the benefit.
Drawings
FIG. 1 is a schematic structural diagram of an unmanned patrol vehicle according to the present invention;
FIG. 2 is a schematic diagram of the optimal speed algorithm of the present invention;
FIG. 3 is a schematic diagram of an optimal path algorithm according to the present invention;
FIG. 4 is a flow chart of the garbage recycling method of the present invention;
FIG. 5 is a schematic diagram of the optimal path of the present invention.
Element number name: the system comprises an automatic driving controller 1, a display 2, a sensing camera 3, an ash bin 4, an ash bin feeding port 41, a dustbin capacity sensor 5, an air suction port 51 of a suction fan, an air exhaust port 52 of the suction fan, a cleaning mechanism 6, a traveling mechanism 7, an on-board OBU 8, a laser radar 9 and a vehicle VCU 10.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Example (b): referring to fig. 1, a garbage recycling system of an unmanned sweeper comprises an unmanned sweeper and a cloud scheduling platform, wherein the unmanned sweeper comprises: the system comprises a dustbin capacity sensor, a whole VCU, an automatic driving controller, a vehicle-mounted OBU, a sensing camera, a laser radar, a combined navigation system, a cleaning mechanism, a traveling mechanism, a vehicle body framework and an exterior assembly; the unmanned sweeper is connected with the cloud scheduling platform through an Ethernet.
In an embodiment of the present invention, the cloud scheduling platform receives feedback information of the unmanned sweeping vehicle in real time, and adjusts and controls operation of the unmanned sweeping vehicle.
The invention also provides a garbage recycling method of the unmanned sweeper, referring to fig. 2 or 4, comprising the following steps of:
step S1: based on the garden map information, the cloud scheduling platform divides the garden into N1-nIndividual area, garbage collection site a1An obstacle M;
step S2: the garbage is recovered to the station a by avoiding the barrier M1And N1-nThree points to be fitted are respectively arranged between the end points of the regions, and the three point sets are represented as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) Setting a cleaning planning path;
and step S3: based on N areas of the park, the cloud scheduling platform sends out cleaning instructions, and a plurality of unmanned cleaning vehicles recover the site a from the rubbish1Starting, running to N areas according to a planned path, and cleaning each appointed area;
and step S4: the method comprises the following steps that an unmanned sweeper runs on the basis of a planned path, a sensing camera of the unmanned sweeper identifies and processes garbage in a cleaning area, meanwhile, identified garbage information is uploaded to a cloud scheduling platform through an Ethernet, the cloud scheduling platform distinguishes and processes the received garbage information, if the garbage amount in a specified area exceeds the single-vehicle cleaning capacity, the cloud scheduling platform schedules idle vehicles from the nearest specified area for supplementary cleaning, if the garbage amount in the current cleaning area is less, the cloud platform issues a scheduling instruction after the current cleaning work is finished, and the unmanned sweeper is scheduled to go to a corresponding busy area;
step S5: the automatic driving controller judges a garbage capacity signal transmitted by the garbage can capacity sensor, and if the garbage can capacity exceeds a set value, a garbage dumping instruction is sent back to the cloud scheduling platform;
step S6: the cloud scheduling platform calculates and recycles the site a according to the position of the unmanned sweeper1Avoiding the barrier M, and recovering the garbage to the station a1And N1-nThree points to be fitted are respectively arranged between the end points of the regions, and the three point sets are represented as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) Setting a path for the unmanned sweeper to return to the garage;
step S7: the unmanned sweeper returns the garbage to the warehouse according to the warehouse returning path, the cloud scheduling platform issues a new cleaning instruction to the unmanned sweeper again, and the unmanned sweeper continues to execute a new cleaning task.
Further, in step S2, the setting of the cleaning planned path includes the following steps:
step S21, based on cubic function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n, three point sets denoted as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) To N, to1End of area (S)1,S2) And (S)2,S3) Fitting was performed, taking the following function:
y1=ax1 3+bx1 2+cx1+ d and y3=jx3 3+kx3 2+mx3+n；
Since the function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n all pass through point S2We can get:
y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n；
step S22, for y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2The first derivative is obtained by + n: 3ax2 2+2bx2+c=3jx2 2+2kx2+ m, in order to guarantee the optimization of the path between the point S1 and the point S3, the functions y1 and y3 are respectively subjected to second derivative, and the obtained second derivative is made to be zero, so as to obtain the final product
With the following function: 6ax1+2b =0 and 6jx3+2k =0, polynomial coefficients (a, b, c, d, j, k, m, n) calculated by the above equation and given set of points to determine two segments of cubic splines;
step S23, using the same algorithm to carry out comparison on N2-nAnd solving the regional end point to obtain an optimal planned route, and finally respectively issuing the optimal route to the corresponding unmanned cleaning.
Specifically, as shown in fig. 5, the unmanned sweeping vehicle recognizes three points S of the obstacle based on the sensing camera1、S2、S3And analyzing and identifying the image data based on the identification module of the unmanned sweeper to obtain an optimal path so that the unmanned patrol car reaches the target park N1When the garbage capacity is judged by the garbage capacity sensor and the garbage capacity is fully loaded, the unmanned patrol car returns to the recovery site a along the same path1And dumping the garbage.
Further, as shown in fig. 2 or 4, in step S6, the setting of the unmanned sweeping vehicle to return to the garage includes the following steps:
s61, the cloud scheduling platform calculates waiting time T according to the number of the garbage-cleaning vehicles fed back by the garbage recovery station1；
Step S62, based on the cubic function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n; to N1End of area (S)1,S2) And (S)2,S3) Fitting was performed, taking the following function:
y1=ax1 3+bx1 2+cx1+ d and y3=jx3 3+kx3 2+mx3+n；
y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n；
Step S63, for y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+ n the second derivative as a function: 6ax1+2b =0 and 6jx3+2k =0, calculated by algebraic equations to determine the polynomial coefficients (a, b, c, d, j, k, m, n) of the two segments of cubic splines;
step S64, using the same algorithm to carry out comparison on N2-nSolving the regional terminal to obtain an optimal planned route, and finally respectively issuing the optimal warehouse returning paths to the corresponding unmanned sweeper;
s65, the cloud scheduling platform calculates a database returning distance L according to the optimal database returning path1(ii) a S66, the cloud scheduling platform returns the warehouse distance L1Need waiting time T1Planning the vehicle speed, and calculating the optimal speed V of the vehicle returning to the garage according to a formula V = L/T1；
And S67, the cloud scheduling platform issues the optimal speed to the vehicle end VCU through the Ethernet, the vehicle end VCU adjusts the speed according to the received speed, and the unmanned sweeper returns to the warehouse for cleaning according to the adjusted speed.
In conclusion, the scheduling work of the unmanned sweeper in the park is realized, the sweeping efficiency is improved, the working energy efficiency of the unmanned sweeper is exerted to the maximum level, the utilization rate of the unmanned sweeper is improved, the park operation cost is reduced, and the maximum yield and benefit is realized.
The above-described embodiments are merely illustrative of the principles of the present invention and are not to be construed as limiting the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (3)
1. The method for recycling the garbage of the unmanned sweeper is characterized by comprising the following steps of:
step S1: based on the garden map information, the cloud scheduling platform divides the garden into N1-nIndividual area, garbage collection site a1An obstacle M;
step S2: the garbage is recovered to the station a by avoiding the barrier M1And N1-nThree points to be fitted are respectively arranged between the end points of the regions, and the three point sets are represented as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) Setting a cleaning planning path;
and step S3: based on N areas of the park, the cloud scheduling platform sends out cleaning instructions, and a plurality of unmanned cleaning vehicles recover the site a from the rubbish1Starting, running to N areas according to a planned path, and cleaning each appointed area;
and step S4: the method comprises the following steps that an unmanned sweeper runs on the basis of a planned path, a sensing camera of the unmanned sweeper identifies and processes garbage in a cleaning area, meanwhile, identified garbage information is uploaded to a cloud scheduling platform through an Ethernet, the cloud scheduling platform distinguishes and processes the received garbage information, if the garbage amount in a specified area exceeds the single-vehicle cleaning capacity, the cloud scheduling platform schedules idle vehicles from the nearest specified area for supplementary cleaning, if the garbage amount in the current cleaning area is less, the cloud platform issues a scheduling instruction after the current cleaning work is finished, and the unmanned sweeper is scheduled to go to a corresponding busy area;
step S5: the automatic driving controller judges a garbage capacity signal transmitted by the garbage can capacity sensor, and if the garbage can capacity exceeds a set value, a garbage dumping instruction is sent back to the cloud scheduling platform;
step S6: the cloud scheduling platform calculates and recovers the station a according to the position of the unmanned sweeper1Avoiding the barrier M, and recovering the garbage to the station a1And N1-nThree points to be fitted are respectively arranged between the end points of the regions, and the three point sets are represented as S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) Setting a path for the unmanned sweeper to return to the garage;
step S7: the unmanned sweeper returns the garbage to the warehouse according to the warehouse returning path, the cloud scheduling platform issues a new cleaning instruction to the unmanned sweeper again, and the unmanned sweeper continues to execute a new cleaning task.
2. The method for recycling garbage of an unmanned sweeping vehicle according to claim 1, comprising: in step S2, the setting of the cleaning planned path includes the steps of:
step S21: based on a cubic function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + N, for N1End of area (S)1，S2) And (S)2，S3) Fitting was performed, taking the following function:
y1=ax1 3+bx1 2+cx1+d,y3=jx3 3+kx3 2+mx3+n，
y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n；
step S22, for y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+ n is the first derivative to obtain：3ax2 2+2bx2+c=3jx2 2+2kx2+m；
Step S23 of respectively pairing the functions y1And y3Performing a second derivative, and making the obtained second derivative zero to obtain the following function: 6ax1+2b =0 and 6jx3+2k=0；
Step S24: calculating by combining the functions obtained in steps S21-S23 with the coordinates of the three points to determine polynomial coefficients (a, b, c, d, j, k, m, n) of two segments of cubic splines;
step S25: using the same algorithm for N2-nAnd solving the regional terminal to obtain an optimal planned route, and finally respectively issuing the optimal route to the corresponding unmanned sweeper.
3. The method for recycling garbage from an unmanned sweeping vehicle according to claim 1, wherein: in step S6, the setting of the route for the unmanned sweeping vehicle to return to the garage includes the following steps:
step S61: the cloud scheduling platform calculates waiting time T according to the number of garbage-cleaning vehicles fed back by the garbage recovery station1；
Step S62: based on a cubic function y = ax3+bx2+ cx + d and y = jx3+kx2+mx+n，S1=（x1，y1），S2=（x2，y2），S3=（x3，y3) To N, to1End of area (S)1，S2) And (S)2，S3) Fitting was performed, taking the following function:
y1=ax1 3+bx1 2+cx1+ d and y3=jx3 3+kx3 2+mx3+n，
Since the function y = ax3+bx2+ cx + d and y = jx3+kx2+ mx + n all pass through point S2We can get:
y2=ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n；
step S63: to ax2 3+bx2 2+cx2+d=jx2 3+kx2 2+mx2+n=y2The first derivative is calculated, and: 3ax2 2+2bx2+c=3jx2 2+2kx2+ m, second derivative is performed on the functions y1 and y3, respectively, and the obtained second derivative is zero, so as to obtain the following functions: 6ax1+2b =0 and 6jx3+2k =0, polynomial coefficients (a, b, c, d, j, k, m, n) calculated by the above equation and given set of points to determine two segments of cubic splines;
step S64: using the same algorithm for N2-nSolving the regional terminal to obtain an optimal planned route, and finally respectively issuing the optimal warehouse returning paths to the corresponding unmanned sweeper;
step S65: the cloud scheduling platform calculates a database returning distance L according to the optimal database returning path1；
Step S66: the cloud scheduling platform returns the warehouse according to the distance L1Need waiting time T1Planning the vehicle speed, and calculating the optimal speed V of the vehicle returning to the garage according to the formula V = L/T1；
Step S67: the cloud scheduling platform issues the optimal speed to the vehicle end VCU through the Ethernet, the vehicle end VCU adjusts the vehicle speed according to the received speed, and the unmanned sweeper returns to the garage for cleaning according to the adjusted speed.
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| CN116451890A (en) * | 2023-02-14 | 2023-07-18 | 广州景瑞达工程咨询有限公司 | Smart city management method and system based on cloud computing |
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| CN116451890A (en) * | 2023-02-14 | 2023-07-18 | 广州景瑞达工程咨询有限公司 | Smart city management method and system based on cloud computing |
| CN116451890B (en) * | 2023-02-14 | 2023-12-12 | 上海勘测设计研究院有限公司 | Smart city management method and system based on cloud computing |
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