CN111582556B - Intelligent parcel sorting system path planning method based on RRT algorithm - Google Patents
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Abstract
The invention provides an intelligent parcel sorting system path planning method based on an RRT algorithm, which comprises the following specific steps: step 1, extracting a plan view of a parcel sorting system, and acquiring position information of an inlet, an outlet and an obstacle of a parcel in the plan view; step 2, taking the entrance position as the current position, and adopting an RRT algorithm to perform path planning to preliminarily obtain a package transmission path; the artificial potential field gravitation component is introduced, a growth function in the direction of resultant force of a random growth function and the gravitation function is introduced in the node expansion process, step length is set, and the position of one step length in the direction of the growth function is the position point of the next step; and step 3, performing further smooth path processing on the primarily obtained parcel conveying path by utilizing a Bezier curve to obtain a final parcel conveying path. The invention solves the problems of strong randomness of path generation and long and roundabout path in the prior art.
Description
Technical Field
The invention belongs to the technical field of path planning methods, and relates to an intelligent parcel sorting system path planning method based on an RRT algorithm.
Background
Along with the rapid development of electronic commerce, the number of express packages is rapidly increased, the traditional manual sorting can not meet the requirements, the automatic sorting system can effectively solve the problems caused by manual sorting, and the system has the characteristics of continuous and large-batch sorting operation, extremely low sorting error rate and basically realizing unmanned sorting sites, so that the system is widely applied to the field of modern logistics. At present, the conveyor belt in the market is mainly divided into a transfer robot, an AGV trolley and a ball modularized conveyor belt. But the carrying robot has the characteristics of large occupied area, high maintenance cost and the like; the AGV trolley has specific requirements on the size and weight of the express packages; compared with the traditional unidirectional transmission conveyor belt, the ball modularized conveyor belt has the characteristics of convenience in maintenance, long service life and the like, but the package can only travel in a specific direction, and has the characteristic of inflexibility in steering. Thus, there is a need to develop intelligent modular conveyor belts. An automatic express package sorting system based on an intelligent conveyor belt relates to two important components of package sorting and path planning.
The research scholars at home and abroad make many improvements to the RRT algorithm. The RRT algorithm has the advantages that modeling is not needed on a map, the calculation complexity is not changed obviously along with the increase of barriers or threats, a feasible solution of path planning can be found in a complex environment, but in most cases, the path planned by the RRT algorithm is not an optimal path, the latest position point is generated along the direction of a selected sub-target point, so that the formed path has a large number of turning points, and the other disadvantage is that for the position point entering an obstacle region, the position point needs to be regenerated, multiple iterations can exist, and the quality of position point generation is affected. And the planned path needs to be further smoothed to meet the actual requirements.
Disclosure of Invention
The invention aims to provide an intelligent parcel sorting system path planning method based on an RRT algorithm, which solves the problems of strong randomness of path generation and long and roundabout path in the prior art.
The technical proposal adopted by the invention is that,
the intelligent parcel sorting system path planning method based on the RRT algorithm comprises the following specific steps:
step 1, extracting a plan view of a parcel sorting system, and acquiring position information of an inlet, an outlet and an obstacle of a parcel in the plan view;
step 2, taking the entrance position as the current position, and adopting an RRT algorithm to perform path planning to preliminarily obtain a package transmission path; the artificial potential field gravitation component is introduced, a growth function in the direction of resultant force of a random growth function and the gravitation function is introduced in the node expansion process, step length is set, and the position of one step length in the direction of the growth function is the position point of the next step;
and step 3, performing further smooth path processing on the primarily obtained parcel conveying path by utilizing a Bezier curve to obtain a final parcel conveying path.
The present invention is also characterized in that,
the step 2 is specifically as follows:
step 2.1, setting the position of an inlet as the current position of a package;
step 2.2, obtaining a random value q,0< q <1 in the plane graph area; if the random value is smaller than the set probability value of 0.6, selecting the exit position point as the current sub-target point, and if the random value is larger than the set probability value, randomly generating a coordinate point in the plane graph area as the current sub-target point;
judging whether the current sub-target point is in an obstacle area, and if so, re-executing the step 2.2, namely re-acquiring the sub-target point; otherwise, executing the step 2.3;
step 2.3, selecting a coordinate point closest to the current sub-target point and the exit position as a current position point, introducing a growth function F (n) in the direction of resultant force of the random growth function and the gravitation function, setting a step length, and setting the position of one step length in the direction of F (n) as a next position point;
step 2.4, taking the current position point to the next position point as an initial vector, judging whether the initial vector enters an obstacle area, if so, taking the initial vector as a vector to be selected and carrying out step 2.5, otherwise, entering step 2.6;
step 2.5, respectively expanding 5 vectors in the anticlockwise direction and the clockwise direction of the vector to be selected at an angle of pi/9, and reserving the vector which does not enter the barrier area as an optional vector; taking the lengths of all the selectable vectors as heuristic functions, and selecting the endpoint corresponding to the vector with the smallest heuristic function as the next position point;
step 2.6, taking the next position point as the current position point, judging whether the current position of the package is in the package outlet area, if so, carrying out step 2.7, otherwise, turning to step 2.2;
step 2.7, all the current position points from the entrance position to the exit area in the steps 2.1 to 2.6 are the primary obtained package conveying paths.
In step 2.2, the method for judging whether the current sub-target point is in the obstacle area is as follows: setting an obstacle safety distance, and judging whether the distance between the current sub-target point position of the package and the center point of the obstacle is greater than the safety distance of the obstacle; if yes, the current sub-target point is not considered to be in the obstacle area, otherwise, the current sub-target point is considered to be in the obstacle area.
In the step 2.3, the calculation mode of the growth function F (n) is as follows:
F(n)＝R(n)+G(n) (1)
wherein R (n) is a random growth function in the direction from the current position point to the current sub-target point, and the formula is as follows:
R(n)＝||q target -q near || (2)
wherein q is target For the position coordinates of the current sub-target point, q near The position coordinates of the current position point;
the gravitational potential field function U of the exit position point to the current position point is:
wherein q is goal A coordinate point k which is an exit position point p The gravitation coefficient of the exit position to the current position point of the package; g (n) is the gravitation function from the current position point to the exit position point, namely the negative gradient corresponding to the gravitational field function U, and the formula is as follows:
G(n)＝k p ||q goal -q near || (4)
the method can be obtained by combining formulas (1) - (4):
F(n)＝||q target -q near ||+k p ×||q goal -q near || (5)
in summary, the calculation formula of the next position point is:
q new ＝q near +q_ dist ×(||q target -q near ||+k p ×||q goal -q near ||) (6)
wherein q is new For the next position point, q/u dist In steps.
In step 2.4, the method for judging whether the initial vector enters the obstacle region is as follows: selecting 0.5cm interval coordinate position points on the initial vector, setting obstacle safety distance, comparing whether the distance from the interval coordinate position points to the center of an obstacle area is larger than the safety distance, and if so, considering that the initial vector does not enter the obstacle area; otherwise the initial vector is considered to enter the obstacle region.
The specific method of the step 3 is as follows:
step 3.1, let all location points in the initially obtained parcel delivery path be { X } i I=1, 2Λn, starting from i=1, determiningIf in the obstacle region, if i=i+1, continuing to judge +.>Whether or not in the obstacle region, otherwise delete X i+1 Let i=i+2, continue to judge +.>Whether or not in the obstacle region; stopping operation until i is more than i+2, and obtaining a new optimized path;
and 3.2, selecting a first-order Bezier curve to further smooth the new optimized path, and obtaining a final parcel delivery path.
The step 3.2 specifically comprises the following steps: assuming that the number of the new optimized path nodes is n, sequentially taking intermediate nodes between two nodes, taking n-1 nodes, judging whether a line segment between connected nodes is in an obstacle area or not, and if the line segment is not in the obstacle area, replacing the nodes at two ends with the intermediate nodes; if the path is in the obstacle area, the original nodes are reserved, and the method is analogically performed until the last node, wherein the updated path formed by all nodes is the final package transmission path.
The invention has the beneficial effects that
1. Introducing artificial potential field gravitation components on the basis of an RRT algorithm, introducing a growth function in the direction of resultant force of a random growth function and the gravitation function in the node expansion process, setting step length, and taking the position of one step length in the direction of the growth function as the position point of the next step; the action of the gravity component can limit the generation range of the node, and secondly, the generation quality of the path is improved in the range, so that the path track difference after each simulation is finished is not large, and the speed of the algorithm is improved to a certain extent;
2. adding an obstacle avoidance process in the obstacle avoidance process, generating a sector area, adding a heuristic function, selecting an optimal vector iteration initial vector from a plurality of vectors to be selected, and further optimizing a path to obtain a nearest obstacle avoidance vector;
3. and after the primary package conveying path is obtained, further smoothing processing is carried out, so that the path flexibility is improved, the planned path is shorter, and the transmission efficiency is faster.
Drawings
FIG. 1 is a flow chart of an intelligent parcel sorting system path planning method based on the RRT algorithm of the invention;
fig. 2 is a plan view obtained by an embodiment 1 of the path planning method of the intelligent parcel sorting system based on the RRT algorithm of the present invention;
fig. 3 is a preliminary parcel delivery path diagram obtained by the intelligent parcel sorting system path planning method embodiment 1 based on the RRT algorithm of the present invention;
fig. 4 is a final parcel delivery path diagram obtained by the intelligent parcel sorting system path planning method embodiment 1 based on RRT algorithm of the present invention;
fig. 5 is a diagram of a parcel delivery path using a conventional RRT algorithm;
fig. 6 is a diagram of a parcel delivery path obtained using the rrt+artificial potential field method.
Detailed Description
The invention will be described in detail below with reference to the drawings and the detailed description.
The invention discloses an intelligent parcel sorting system path planning method based on an RRT algorithm, which is shown in figure 1 and comprises the following specific steps:
step 1, extracting a plan view of a parcel sorting system, and acquiring position information of an inlet, an outlet and an obstacle of a parcel in the plan view;
step 2, taking the entrance position as the current position, and adopting an RRT algorithm to carry out path planning to obtain a preliminary package transmission path; the artificial potential field gravitation component is introduced, a growth function in the direction of resultant force of a random growth function and the gravitation function is introduced in the node expansion process, step length is set, and the position of one step length in the direction of the growth function is the position point of the next step;
and step 3, performing further smooth path processing on the primarily obtained parcel conveying path by utilizing a Bezier curve to obtain a final parcel conveying path.
The step 2 specifically comprises the following steps:
step 2.1, setting the position of an inlet as the current position of a package;
step 2.2, obtaining a random value q,0< q <1 in the plane graph area; if the random value is smaller than the set probability value of 0.6, selecting the exit position point as the current sub-target point, and if the random value is larger than the set probability value, randomly generating a coordinate point in the plane graph area as the current sub-target point of the package;
judging whether the current sub-target point is in an obstacle area, and if so, re-executing the step 2.2, namely re-acquiring the sub-target point; otherwise, executing the step 2.3;
the method for judging whether the current sub-target point is in the obstacle area comprises the following steps: setting an obstacle safety distance, and judging whether the distance between the current sub-target point position of the package and the center point of the obstacle is greater than the safety distance of the obstacle; if yes, the current sub-target point is not considered to be in the obstacle area, otherwise, the current sub-target point is considered to be in the obstacle area.
Step 2.3, selecting a coordinate point closest to the current sub-target point and the exit position as a current position point, introducing a growth function F (n) in the direction of resultant force of the random growth function and the gravitation function, setting a step length, and setting the position of one step length in the direction of F (n) as a next position point;
the growth function F (n) is calculated by:
F(n)＝R(n)+G(n) (1)
wherein R (n) is a random growth function in the direction from the current position point to the current sub-target point, and the formula is as follows:
R(n)＝||q target -q near || (2)
wherein q is target For the position coordinates of the current sub-target point, q near The position coordinates of the current position point;
the attraction potential field function U of the package exit position point to the current position point is:
wherein q is goal A coordinate point k which is an exit position point p The gravitation coefficient of the exit position to the current position point; g (n) is the gravitation function from the current position point to the exit position point, namely the negative gradient corresponding to the gravitational field function U, and the formula is as follows:
G(n)＝k p ||q goal -q near || (4)
the method can be obtained by combining formulas (1) - (4):
F(n)＝||q target -q near ||+k p ×||q goal -q near || (5)
in summary, the calculation formula of the next position point is:
q new ＝q near +q_ dist ×(||q target -q near ||+k p ×||q goal -q near ||) (6)
wherein q is new For the next position point, q/u dist In steps.
Step 2.4, taking the current position point to the next position point as an initial vector, judging whether the initial vector enters an obstacle area, if so, taking the initial vector as a vector to be selected and carrying out step 2.5, otherwise, entering step 2.6;
the method for judging whether the initial vector enters the obstacle area comprises the following steps: selecting 0.5cm interval coordinate position points on the initial vector, setting obstacle safety distance, comparing whether the distance from the interval coordinate position points to the center of an obstacle area is larger than the safety distance, and if so, considering that the initial vector does not enter the obstacle area; otherwise the initial vector is considered to enter the obstacle region.
Step 2.5, respectively expanding 5 vectors in the anticlockwise direction and the clockwise direction of the vector to be selected at an angle of pi/9, and reserving the vector which does not enter the barrier area as an optional vector; taking the lengths of all the selectable vectors as heuristic functions, and selecting the endpoint corresponding to the vector with the smallest heuristic function as the next position point;
step 2.4 to step 2.6 are local obstacle avoidance methods, an obstacle avoidance process is added in the obstacle avoidance process, a sector area is generated, a heuristic function is added, an optimal vector iteration initial vector is selected from a plurality of vectors to be selected, and the path is further optimized.
Step 2.6, taking the next position point as the current position point, judging whether the current position of the package is in the package outlet area, if so, carrying out step 2.7, otherwise, turning to step 2.2;
the method for judging whether the current position of the package is in the package outlet area comprises the following steps: setting a threshold e, if the distance between the exit position of the package and the current position point of the package is smaller than the threshold e, judging that the package reaches the exit position, otherwise, continuing to carry out path planning.
And 2.7, wherein all the current position points from the entrance position to the exit area in the steps 2.1 to 2.6 are the primary package conveying paths.
The specific method of the step 3 is as follows:
step 3.1, let all location points in the preliminary parcel delivery path be { X } i I=1, 2Λn }, starting from i=1JudgingIf in the obstacle region, if i=i+1, continuing to judge +.>Whether or not in the obstacle region, otherwise delete X i+1 Let i=i+2, continue to judge +.>Whether or not in the obstacle region; stopping operation until i is more than i+2, and obtaining a new optimized path;
step 3.2, selecting a first-order Bezier curve to carry out further smoothing treatment on the new optimized path to obtain a final parcel delivery path; specifically, assuming that the number of new optimized path nodes is n, sequentially taking intermediate nodes between two nodes, n-1 nodes can be taken, judging whether a line segment between connected nodes is in an obstacle region or not, if not, replacing the nodes at two ends with the intermediate nodes; if the path is in the obstacle area, the original nodes are reserved, and the method is analogically performed until the last node, wherein the updated path formed by all nodes is the final package transmission path.
Example 1
Executing the step 1, wherein the obtained plan view is shown in fig. 2, the diamond at the upper right corner is an outlet position point, the diamond at the lower left corner is an inlet position point, and the black is an obstacle;
performing step 2, and obtaining a package conveying path preliminarily, as shown in fig. 3; the local area obstacle avoidance strategy is adopted on the basis of adding the gravitation component, so that the package is sensitive to the information of the environmental obstacle, and the direction can be quickly changed to bypass the obstacle to walk when the package encounters the obstacle.
Step 3 is executed to obtain a final package transmission path, as shown in fig. 4, a secondary smoothing strategy is adopted to reduce the number of nodes generated by the RRT algorithm, and a smoother path is obtained. The strategy has a good smoothing effect on nodes with sharp included angles, so that the package steering accords with the package steering in actual conditions.
For the same package sorting system plan, the conventional RRT algorithm is adopted, the obtained path is as shown in fig. 5, the node expansion mode is random, and the node expansion mode is insensitive to environmental information perception. And backtracking phenomenon can occur; the path obtained by adopting the RRT+artificial potential field method is shown in fig. 6, the RRT+artificial potential field method is that on the basis of the traditional RRT, the next position point is determined by adopting the artificial potential field method for the point entering the obstacle region, as can be seen from the figure, the method can also obtain a good path, but as for the simulation result, as shown in the table 1, the simulation time is longer, the path length is longer, in addition, the artificial potential field method needs to be set manually and reasonably to meet the steering requirement, and the human factors increase the difficulty of obtaining the optimal path.
Table 1 comparison of simulation results
In conclusion, the intelligent parcel sorting system path planning method based on the RRT algorithm has the advantages that no backtracking phenomenon exists in the path, the path steering is more flexible, the path is shorter, and the transmission efficiency is faster.
Claims (2)
1. The intelligent parcel sorting system path planning method based on the RRT algorithm is characterized by comprising the following specific steps:
step 1, extracting a plan view of a parcel sorting system, and acquiring position information of an inlet, an outlet and an obstacle of a parcel in the plan view;
step 2, taking the entrance position as the current position, and adopting an RRT algorithm to perform path planning to preliminarily obtain a package transmission path; the artificial potential field gravitation component is introduced, a growth function in the direction of resultant force of a random growth function and the gravitation function is introduced in the node expansion process, step length is set, and the position of one step length in the direction of the growth function is the position point of the next step;
the step 2 is specifically as follows:
step 2.1, setting the position of an inlet as the current position of a package;
step 2.2, obtaining a random value q,0< q <1 in the plane graph area; if the random value is smaller than the set probability value of 0.6, selecting the exit position point as the current sub-target point, and if the random value is larger than the set probability value, randomly generating a coordinate point in the plane graph area as the current sub-target point;
judging whether the current sub-target point is in an obstacle area, and if so, re-executing the step 2.2, namely re-acquiring the sub-target point; otherwise, executing the step 2.3;
the method for judging whether the current sub-target point is in the obstacle area comprises the following steps: setting an obstacle safety distance, and judging whether the distance between the current sub-target point position of the package and the center point of the obstacle is greater than the safety distance of the obstacle; if yes, the current sub-target point is not considered to be in the obstacle area, otherwise, the current sub-target point is considered to be in the obstacle area;
step 2.3, selecting a coordinate point closest to the current sub-target point and the exit position as a current position point, introducing a growth function F (n) in the direction of resultant force of the random growth function and the gravitation function, setting a step length, and setting the position of one step length in the direction of F (n) as a next position point;
the growth function F (n) is calculated by:
F(n)＝R(n)+G(n) (1)
wherein R (n) is a random growth function in the direction from the current position point to the current sub-target point, and the formula is as follows:
R(n)＝||q target -q near || (2)
wherein q is target For the position coordinates of the current sub-target point, q near The position coordinates of the current position point;
the gravitational potential field function U of the exit position point to the current position point is:
wherein q is goal A coordinate point k which is an exit position point p Indexing the current location point of the package for the exit locationA force coefficient; g (n) is the gravitation function from the current position point to the exit position point, namely the negative gradient corresponding to the gravitational field function U, and the formula is as follows:
G(n)＝k p ||q goal -q near || (4)
the method can be obtained by combining formulas (1) - (4):
F(n)＝||q target -q near ||+k p ×||q goal -q near || (5)
in summary, the calculation formula of the next position point is:
q new ＝q near +q _dist ×(||q target -q near ||+k p ×||q goal -q near ||) (6)
wherein q is new For the next position point, q _dist Is the step length;
step 2.4, taking the current position point to the next position point as an initial vector, judging whether the initial vector enters an obstacle area, if so, taking the initial vector as a vector to be selected and carrying out step 2.5, otherwise, entering step 2.6;
in step 2.4, the method for judging whether the initial vector enters the obstacle region is as follows: selecting 0.5cm interval coordinate position points on the initial vector, setting obstacle safety distance, comparing whether the distance from the interval coordinate position points to the center of an obstacle area is larger than the safety distance, and if so, considering that the initial vector does not enter the obstacle area; otherwise, the initial vector is considered to enter the obstacle region;
step 2.5, respectively expanding 5 vectors in the anticlockwise direction and the clockwise direction of the vector to be selected at an angle of pi/9, and reserving the vector which does not enter the barrier area as an optional vector; taking the lengths of all the selectable vectors as heuristic functions, and selecting the endpoint corresponding to the vector with the smallest heuristic function as the next position point;
step 2.6, taking the next position point as the current position point, judging whether the current position of the package is in the package outlet area, if so, carrying out step 2.7, otherwise, turning to step 2.2;
step 2.7, namely, initially obtaining a package conveying path from all the current position points in the exit area from the entrance position in the steps 2.1 to 2.6;
step 3, performing further smooth path processing on the primarily obtained parcel conveying path by utilizing a Bezier curve to obtain a final parcel conveying path;
the specific method of the step 3 is as follows:
step 3.1, let all location points in the initially obtained parcel delivery path be { X } i I=1, 2 … n }, and starting from i=1, judgment is madeIf in the obstacle region, if i=i+1, continuing to judge +.>Whether or not in the obstacle region, otherwise delete X i+1 Let i=i+2, continue to judge +.>Whether or not in the obstacle region; stopping operation until i is more than i+2, and obtaining a new optimized path;
and 3.2, selecting a first-order Bezier curve to further smooth the new optimized path, and obtaining a final parcel delivery path.
2. The RRT algorithm-based intelligent parcel sorting system path planning method of claim 1, wherein step 3.2 is specifically: assuming that the number of the new optimized path nodes is n, sequentially taking intermediate nodes between two nodes, taking n-1 nodes, judging whether a line segment between connected nodes is in an obstacle area or not, and if the line segment is not in the obstacle area, replacing the nodes at two ends with the intermediate nodes; if the path is in the obstacle area, the original nodes are reserved, and the method is analogically performed until the last node, wherein the updated path formed by all nodes is the final package transmission path.
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