CN115454061A - Robot path obstacle avoidance method and system based on 3D technology - Google Patents
Robot path obstacle avoidance method and system based on 3D technology Download PDFInfo
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Abstract
The invention discloses a robot path obstacle avoidance method and system based on a 3D technology, which comprises the following steps: carrying out model fitting on the three-dimensional characteristics of the obstacle and the three-dimensional obstacle avoidance parameters of the robot to obtain a robot path obstacle avoidance model representing the mapping relation between the three-dimensional characteristics and the three-dimensional obstacle avoidance parameters; and monitoring the three-dimensional characteristics of the real-time obstacle on the robot traveling path, and obtaining the real-time three-dimensional obstacle avoidance parameters of the robot by using the robot path obstacle avoidance model based on the three-dimensional characteristics of the real-time obstacle. The three-dimensional characteristics of the obstacle and the three-dimensional obstacle avoidance parameters of the robot are subjected to model fitting to obtain the robot path obstacle avoidance model representing the mapping relation of the three-dimensional characteristics and the three-dimensional obstacle avoidance parameters, the robot can carry out real-time autonomous obstacle avoidance according to the real-time three-dimensional obstacle avoidance parameters, and the autonomous obstacle avoidance algorithm based on the depth model has autonomous learning capacity under an obstacle avoidance scene and avoids the problems of complicated three-dimensional reconstruction and path planning.
Description
Technical Field
The invention relates to the technical field of robot obstacle avoidance, in particular to a robot path obstacle avoidance method and system based on a 3D technology.
Background
With the continuous development of science and technology, mobile robots have been widely used in various fields, including living services, industrial production, military, entertainment, and the like. Robotics designs control, machinery, computers, and many other disciplinary techniques. The navigation and obstacle avoidance capability of the robot is an important index for reflecting the intelligence of the robot.
Khatib in the text of Real-time ObstacleAvoidance for Manipula and MobileRobots enables an obstacle and a target point to generate abstract repulsive force and attractive force on a robot in an artificial potential field, and controls the robot to avoid the obstacle together. The path planned by the artificial potential field method has the advantages of safety and smoothness, and is convenient for the actual execution control of the robot, but the artificial potential field method is easy to fall into a local extreme value, so that the problem of path oscillation is caused when the artificial potential field method approaches an obstacle or a target point. Nicolai et al, in deep convolutional neural network, estimates continuously transformed point cloud data, and further implements path planning data and obstacle avoidance for robots. Although existing sensors already provide a large amount of accurate environmental data, the positioning method is difficult to effectively analyze the large amount of data, and the obstacle avoidance algorithm is too complex.
Disclosure of Invention
The invention aims to provide a robot path obstacle avoidance method based on a 3D technology, and aims to solve the technical problem that an obstacle avoidance algorithm in the prior art is too complex.
In order to solve the technical problems, the invention specifically provides the following technical scheme:
a robot path obstacle avoidance method based on a 3D technology comprises the following steps:
the method comprises the following steps that S1, three-dimensional characteristics of an obstacle located on a traveling path of the robot are detected by using a three-dimensional radar carried by the robot, and three-dimensional obstacle avoidance parameters of the robot are optimized and analyzed according to the three-dimensional characteristics of the obstacle;
s2, performing model fitting on the three-dimensional characteristics of the obstacle and the three-dimensional obstacle avoidance parameters of the robot to obtain a robot path obstacle avoidance model representing the mapping relation of the three-dimensional characteristics and the three-dimensional obstacle avoidance parameters;
and S3, monitoring the three-dimensional characteristics of the real-time obstacle on the traveling path of the robot, and obtaining real-time three-dimensional obstacle avoidance parameters of the robot by using the robot path obstacle avoidance model based on the three-dimensional characteristics of the real-time obstacle so as to realize real-time autonomous obstacle avoidance of the robot according to the real-time three-dimensional obstacle avoidance parameters.
As one preferable aspect of the present invention, the detecting of the three-dimensional feature of the obstacle located on the robot traveling path by the three-dimensional radar mounted on the robot includes:
detecting three-dimensional coordinates of an obstacle positioned on a traveling path of the robot by using a three-dimensional radar carried by the robot, and respectively extracting coordinates of two boundaries of the obstacle, which are close to the boundaries of two paths of the traveling path;
respectively extracting three-dimensional coordinates from boundary coordinates of two paths to spaces at boundary coordinates on two sides of an obstacle on a traveling path as three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces, and respectively marking the obstacle avoidance selectable spaces as an AA 'space and a B' space, wherein A is characterized as the left boundary of the traveling path, A 'is characterized as the left boundary of the obstacle, B' is characterized as the right boundary of the traveling path, and B is characterized as the right boundary of the obstacle;
and taking the three-dimensional coordinates of the obstacle and the three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces as the three-dimensional characteristics of the obstacle.
As a preferred scheme of the present invention, the optimizing and analyzing the three-dimensional obstacle avoidance parameters of the robot according to the three-dimensional features of the obstacle includes:
calculating the three-dimensional volume of each obstacle avoidance selectable space by using the three-dimensional coordinates of each obstacle avoidance selectable space in the three-dimensional characteristics, and comparing the three-dimensional volumes of the plurality of obstacle avoidance selectable spaces with the three-dimensional volume of the robot, wherein,
if the three-dimensional volumes of the AA 'space and the B' space are both larger than or equal to the three-dimensional volume of the robot, the AA 'space and the B' space are both used as effective obstacle avoidance spaces;
if the three-dimensional volume of the AA ' space is larger than or equal to that of the robot and the three-dimensional volume of the B ' space is smaller than that of the robot, taking the AA ' space as an effective obstacle avoidance space;
if the three-dimensional volume of the B ' B space is larger than or equal to that of the robot and the three-dimensional volume of the AA ' space is smaller than that of the robot, taking the B ' B space as an effective obstacle avoidance space;
if the three-dimensional volumes of the AA 'space and the B' space are smaller than the three-dimensional volume of the robot, the AA 'space and the B' space are both used as non-effective obstacle avoidance spaces;
when at least one effective obstacle avoidance space exists, setting an optimization function of an obstacle avoidance path in each effective obstacle avoidance space according to the highest path smoothness and the shortest path length, wherein the optimization function of the obstacle avoidance path is as follows:
in the formula (I), the compound is shown in the specification,
to characterize the optimization function with the highest path smoothness for the obstacle avoidance path,
for the optimization function characterizing the shortest path length of an obstacle avoidance path, p i The three-dimensional coordinates of the ith path point in the obstacle avoidance path are obtained, N is the total number of the path points in the obstacle avoidance path, and i is a measurement constant;
setting a solution constraint condition of an optimization function of an obstacle avoidance path, wherein the solution constraint condition is as follows:
wherein, | p i A | is p i Distance to A, | p i A' | is p i Distance to A' | p i B | is p i Distance to B, | p i B' | is p i The distance to B ', O is characterized as the center point of the robot, C is the left boundary of the robot, A' isRight boundary of robot, | OC | is distance of O to C, | OC '| is distance of O to C, [ AA']Is AA 'space, [ BB']BB' space;
solving the optimization functions of the obstacle avoidance paths based on the solving constraint conditions to obtain the obstacle avoidance paths of the effective obstacle avoidance space;
and taking the effective obstacle avoidance space and the obstacle avoidance path as three-dimensional obstacle avoidance parameters of the robot.
As a preferable scheme of the invention, when no effective obstacle avoidance space exists, the robot stops in situ to perform early warning.
As a preferable aspect of the present invention, the constructing of the robot path obstacle avoidance model includes:
taking the three-dimensional characteristics of the obstacle as an input item of a CNN (neural network), taking the three-dimensional obstacle avoidance parameters of the robot as an output item of the CNN, and performing model training by using the CNN based on the input item and the output item to obtain a robot path obstacle avoidance model, wherein the model expression of the robot path obstacle avoidance model is as follows:
Out[Y]＝CNN(In[X])；
in the formula, out Y is the three-dimensional obstacle avoidance parameter of the robot, inX is the three-dimensional characteristic of the obstacle, and CNN is the CNN neural network.
As a preferred aspect of the present invention, the monitoring three-dimensional characteristics of a real-time obstacle on a robot traveling path includes:
taking an obstacle closest to a robot in a traveling direction on a traveling path as a real-time obstacle, detecting three-dimensional coordinates of the obstacle by using a three-dimensional radar carried by the robot, and respectively extracting three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces of the real-time obstacle;
and taking the three-dimensional coordinates of the real-time obstacle and the three-dimensional coordinates of the plurality of obstacle avoidance selectable spaces as the three-dimensional characteristics of the real-time obstacle.
As a preferred scheme of the present invention, the obtaining of the real-time three-dimensional obstacle avoidance parameter of the robot based on the three-dimensional characteristics of the real-time obstacle by using the robot path obstacle avoidance model includes:
inputting the three-dimensional characteristics of the real-time obstacle to the robot path obstacle avoidance model, and outputting real-time three-dimensional obstacle avoidance parameters of the robot by the robot path obstacle avoidance model, wherein the real-time three-dimensional obstacle avoidance parameters comprise a real-time effective obstacle avoidance space and a real-time obstacle avoidance path of the robot.
As a preferable aspect of the present invention, the three-dimensional feature detection distance of the obstacle of the robot is greater than the safety braking distance of the robot.
As a preferred scheme of the present invention, when the number of real-time obstacle avoidance paths is greater than 1, evaluation weights of path smoothness and path length are set, and the path smoothness and the path length are subjected to weighted summation to serve as a selection function for selecting a real-time obstacle avoidance path, where the selection function is:
where Jarge is the evaluation value of the real-time obstacle avoidance path,
for the evaluation value of the path smoothness of the real-time obstacle avoidance path,
the evaluation values are path length evaluation values of the real-time obstacle avoidance path, and W and V are evaluation weights of path smoothness and path length respectively;
and the robot carries out real-time autonomous obstacle avoidance according to the real-time obstacle avoidance path with the highest evaluation value.
As a preferable scheme of the invention, the invention provides an obstacle avoidance system according to the robot path obstacle avoidance method based on the 3D technology, which comprises a three-dimensional radar and a data processor, wherein the three-dimensional radar is in communication connection with the data processor, the three-dimensional radar is used for detecting three-dimensional characteristics of an obstacle, the data processor is used for receiving the three-dimensional characteristics of the obstacle and obtaining three-dimensional obstacle avoidance parameters of the robot based on the three-dimensional characteristics of the obstacle by using a robot path obstacle avoidance model, and the robot path obstacle avoidance model is built in the data processor.
Compared with the prior art, the invention has the following beneficial effects:
the three-dimensional characteristics of the obstacle and the three-dimensional obstacle avoidance parameters of the robot are subjected to model fitting to obtain the robot path obstacle avoidance model representing the mapping relation of the three-dimensional characteristics and the three-dimensional obstacle avoidance parameters, the robot can carry out real-time autonomous obstacle avoidance according to the real-time three-dimensional obstacle avoidance parameters, and the autonomous obstacle avoidance algorithm based on the depth model has autonomous learning capacity under an obstacle avoidance scene and avoids the problems of complicated three-dimensional reconstruction and path planning.
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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. It should be apparent that the drawings in the following description are merely exemplary and that other implementation drawings may be derived from the provided drawings by those of ordinary skill in the art without inventive effort.
Fig. 1 is a flowchart of a robot path obstacle avoidance method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a three-dimensional feature structure according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the present invention provides a robot path obstacle avoidance method based on 3D technology, including the following steps:
the method comprises the following steps that S1, three-dimensional characteristics of an obstacle located on a traveling path of the robot are detected by using a three-dimensional radar carried by the robot, and three-dimensional obstacle avoidance parameters of the robot are optimized and analyzed according to the three-dimensional characteristics of the obstacle;
the method for detecting the three-dimensional characteristics of an obstacle positioned on a robot traveling path by using a three-dimensional radar carried by the robot comprises the following steps:
as shown in fig. 2, a three-dimensional radar carried by a robot is used for detecting three-dimensional coordinates of an obstacle on a traveling path of the robot, and two boundary coordinates of the obstacle close to two path boundaries of the traveling path are respectively extracted;
respectively extracting three-dimensional coordinates from boundary coordinates of two paths to spaces at boundary coordinates on two sides of an obstacle on a traveling path as three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces, and respectively marking the obstacle avoidance selectable spaces as AA 'spaces and B' spaces, wherein A is characterized as the left boundary of the traveling path, A 'is characterized as the left boundary of the obstacle, B' is characterized as the right boundary of the traveling path, and B is characterized as the right boundary of the obstacle;
and taking the three-dimensional coordinates of the obstacle and the three-dimensional coordinates of the plurality of obstacle avoidance selectable spaces as the three-dimensional characteristics of the obstacle.
The method comprises the following steps of optimally analyzing three-dimensional obstacle avoidance parameters of the robot according to the three-dimensional characteristics of obstacles, wherein the method comprises the following steps:
calculating the three-dimensional volume of each obstacle avoidance selectable space by using the three-dimensional coordinates of each obstacle avoidance selectable space in the three-dimensional characteristics, and comparing the three-dimensional volumes of the plurality of obstacle avoidance selectable spaces with the three-dimensional volume of the robot, wherein,
if the three-dimensional volumes of the AA 'space and the B' space are both larger than or equal to the three-dimensional volume of the robot, the AA 'space and the B' space are both used as effective obstacle avoidance spaces;
if the three-dimensional volume of the AA ' space is larger than or equal to that of the robot and the three-dimensional volume of the B ' space is smaller than that of the robot, taking the AA ' space as an effective obstacle avoidance space;
if the three-dimensional volume of the B ' B space is larger than or equal to that of the robot and the three-dimensional volume of the AA ' space is smaller than that of the robot, taking the B ' B space as an effective obstacle avoidance space;
if the three-dimensional volumes of the AA 'space and the B' space are smaller than the three-dimensional volume of the robot, the AA 'space and the B' space are both used as non-effective obstacle avoidance spaces;
when at least one effective obstacle avoidance space exists, setting an optimization function of an obstacle avoidance path in each effective obstacle avoidance space according to the highest path smoothness and the shortest path length, wherein the optimization function of the obstacle avoidance path is as follows:
in the formula (I), the compound is shown in the specification,
to characterize the most smooth optimization function of the path of the obstacle avoidance path,
for the optimisation function of the shortest path length characterizing the obstacle avoidance path, p i The three-dimensional coordinates of the ith path point in the obstacle avoidance path are obtained, N is the total number of the path points in the obstacle avoidance path, and i is a measurement constant;
setting a solving constraint condition of an optimization function of the obstacle avoidance path, wherein the solving constraint condition is as follows:
wherein, | p i A | is p i Distance to A, | p i A' | is p i Distance to A' | p i B | is p i Distance to B, | p i B' | is p i Distance to B ', O is characterized as the center point of the robot, C is the left boundary of the robot, A' is the right boundary of the robot, | OC | is the distance from O to C, | OC '| is the distance from O to C, | AA']Is AA 'space, [ BB']In BB' space, i.e. p i The value range of the robot is in an AA 'space or a BB' space, the O point is a planning position point on the obstacle avoidance path of the robot, and the center point of the robot is used as the basis of the obstacle avoidance path, so that the robot is ensured not to exceed the left boundary and the right boundary or exceed the obstacle avoidance path when moving on the obstacle avoidance pathThe left boundary and the right boundary of the effective obstacle avoidance space are collided, so that the traveling safety of the robot is ensured;
solving an optimization function of multiple obstacle avoidance paths based on the solving constraint condition to obtain an obstacle avoidance path of an effective obstacle avoidance space;
and taking the effective obstacle avoidance space and the obstacle avoidance path as three-dimensional obstacle avoidance parameters of the robot.
And when no effective obstacle avoidance space exists, the robot stops in place to perform early warning.
The obstacle avoidance path is determined by utilizing the optimization method of the path smoothness and the path length, the adjustment amount of deflection movement is small by the path smoothness while the robot can be guaranteed to successfully move on the obstacle avoidance path to realize the obstacle avoidance function, so that the movement fluctuation degree of the robot is small, the stability of the robot in the obstacle avoidance process is improved, the path length is small, the robot can be enabled to have high obstacle avoidance efficiency, the obstacle avoidance is completed in the shortest stroke and the shortest time, and the three-in-one of the obstacle avoidance safety, the stability and the efficiency is realized.
S2, performing model fitting on the three-dimensional characteristics of the obstacle and the three-dimensional obstacle avoidance parameters of the robot to obtain a robot path obstacle avoidance model representing the mapping relation between the three-dimensional characteristics and the three-dimensional obstacle avoidance parameters;
the construction of the robot path obstacle avoidance model comprises the following steps:
the three-dimensional characteristics of the obstacle are used as input items of a CNN (neural network), the three-dimensional obstacle avoidance parameters of the robot are used as output items of the CNN, model training is carried out on the CNN based on the input items and the output items by utilizing the CNN to obtain a robot path obstacle avoidance model, and the model expression of the robot path obstacle avoidance model is as follows:
Out[Y]＝CNN(In[X])；
in the formula, out Y is the three-dimensional obstacle avoidance parameter of the robot, inX is the three-dimensional characteristic of the obstacle, and CNN is the CNN neural network.
The three-dimensional obstacle avoidance parameters obtained through optimization analysis and the three-dimensional characteristics of the obstacles are used for model fitting, so that the three-dimensional obstacle avoidance parameters which accord with obstacle avoidance safety, stability and efficiency can be predicted through the three-dimensional characteristics of the obstacles by using the deep learning capacity of the neural network, the three-dimensional obstacle avoidance parameters can be directly obtained through the three-dimensional characteristics only by using the robot path obstacle avoidance model subsequently, the optimization analysis process or the traditional path planning method (an artificial potential field, an A path planning method and the like) does not need to be repeated for planning the obstacle avoidance path, the obstacle avoidance path planning effect is guaranteed, and meanwhile, the obstacle avoidance path planning efficiency is improved.
And S3, monitoring the three-dimensional characteristics of the real-time obstacle on the traveling path of the robot, and obtaining real-time three-dimensional obstacle avoidance parameters of the robot by using the robot path obstacle avoidance model based on the three-dimensional characteristics of the real-time obstacle so as to realize real-time autonomous obstacle avoidance of the robot according to the real-time three-dimensional obstacle avoidance parameters.
Monitoring three-dimensional characteristics of a real-time obstacle on a robot travel path, comprising:
taking an obstacle closest to a robot in the advancing direction on a traveling path as a real-time obstacle, detecting three-dimensional coordinates of the obstacle by using a three-dimensional radar carried by the robot, and respectively extracting three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces of the real-time obstacle;
and taking the three-dimensional coordinates of the real-time obstacle and the three-dimensional coordinates of the plurality of obstacle avoidance selectable spaces as the three-dimensional characteristics of the real-time obstacle.
The method for obtaining the real-time three-dimensional obstacle avoidance parameters of the robot by utilizing the robot path obstacle avoidance model based on the three-dimensional characteristics of the real-time obstacles comprises the following steps:
the three-dimensional characteristics of the real-time obstacle are input into the robot path obstacle avoidance model, and real-time three-dimensional obstacle avoidance parameters of the robot are output by the robot path obstacle avoidance model, wherein the real-time three-dimensional obstacle avoidance parameters comprise a real-time effective obstacle avoidance space and a real-time obstacle avoidance path of the robot.
The three-dimensional feature detection distance of the obstacle of the robot is greater than the safety braking distance of the robot.
When the number of the real-time obstacle avoidance paths is more than 1, setting evaluation weights of path smoothness and path length, and performing weighted summation on the path smoothness and the path length to serve as a selection function for selecting the real-time obstacle avoidance paths, wherein the selection function is as follows:
where Jarge is the evaluation value of the real-time obstacle avoidance path,
for the evaluation value of the path smoothness of the real-time obstacle avoidance path,
for the path length evaluation value of the real-time obstacle avoidance path, W and V are evaluation weights of path smoothness and path length respectively, W + V =1, W belongs to [0,1 ]],V∈[0,1]The user can set according to the requirement, wherein the higher the W is set, the more the path smoothness of the obstacle avoidance path is emphasized, the higher the V is set, the more the path length of the obstacle avoidance path is emphasized, and the real-time obstacle avoidance path which is the highest in evaluation and better meets the requirement of the user can be selected from the multiple real-time obstacle avoidance paths;
and the robot carries out real-time autonomous obstacle avoidance according to the real-time obstacle avoidance path with the highest evaluation value.
Based on the robot path obstacle avoidance method, the invention provides an obstacle avoidance system which comprises a three-dimensional radar and a data processor, wherein the three-dimensional radar is in communication connection with the data processor, the three-dimensional radar is used for detecting three-dimensional characteristics of obstacles, the data processor is used for receiving the three-dimensional characteristics of the obstacles, three-dimensional obstacle avoidance parameters of a robot are obtained by utilizing a robot path obstacle avoidance model based on the three-dimensional characteristics of the obstacles, and the robot path obstacle avoidance model is arranged in the data processor.
The three-dimensional characteristics of the obstacle and the three-dimensional obstacle avoidance parameters of the robot are subjected to model fitting to obtain the robot path obstacle avoidance model representing the mapping relation of the three-dimensional characteristics and the three-dimensional obstacle avoidance parameters, the robot can carry out real-time autonomous obstacle avoidance according to the real-time three-dimensional obstacle avoidance parameters, and the autonomous obstacle avoidance algorithm based on the depth model has autonomous learning capacity under an obstacle avoidance scene and avoids the problems of complicated three-dimensional reconstruction and path planning.
The above embodiments are only exemplary embodiments of the present application, and are not intended to limit the present application, and the protection scope of the present application is defined by the claims. Various modifications and equivalents may be made by those skilled in the art within the spirit and scope of the present application and such modifications and equivalents should also be considered to be within the scope of the present application.
Claims (10)
1. A robot path obstacle avoidance method based on a 3D technology is characterized by comprising the following steps:
the method comprises the following steps that S1, three-dimensional characteristics of an obstacle located on a traveling path of the robot are detected by using a three-dimensional radar carried by the robot, and three-dimensional obstacle avoidance parameters of the robot are optimized and analyzed according to the three-dimensional characteristics of the obstacle;
s2, performing model fitting on the three-dimensional characteristics of the obstacle and the three-dimensional obstacle avoidance parameters of the robot to obtain a robot path obstacle avoidance model representing the mapping relation of the three-dimensional characteristics and the three-dimensional obstacle avoidance parameters;
and S3, monitoring the three-dimensional characteristics of the real-time obstacle on the traveling path of the robot, and obtaining the real-time three-dimensional obstacle avoidance parameters of the robot by using the robot path obstacle avoidance model based on the three-dimensional characteristics of the real-time obstacle so as to realize real-time autonomous obstacle avoidance of the robot according to the real-time three-dimensional obstacle avoidance parameters.
2. The robot path obstacle avoidance method based on the 3D technology as claimed in claim 1, wherein: the three-dimensional feature that utilizes the three-dimensional radar of robot carrying to detect the barrier that is located on the robot path of travel includes:
detecting three-dimensional coordinates of an obstacle positioned on a traveling path of the robot by using a three-dimensional radar carried by the robot, and respectively extracting coordinates of two boundaries of the obstacle, which are close to the boundaries of two paths of the traveling path;
respectively extracting three-dimensional coordinates from boundary coordinates of two paths to spaces at boundary coordinates on two sides of an obstacle on a traveling path as three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces, and respectively marking the obstacle avoidance selectable spaces as an AA 'space and a B' space, wherein A is characterized as the left boundary of the traveling path, A 'is characterized as the left boundary of the obstacle, B' is characterized as the right boundary of the traveling path, and B is characterized as the right boundary of the obstacle;
and taking the three-dimensional coordinates of the obstacle and the three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces as the three-dimensional characteristics of the obstacle.
3. The robot path obstacle avoidance method based on the 3D technology as claimed in claim 2, wherein: the three-dimensional obstacle avoidance parameter of the robot is analyzed according to the three-dimensional feature optimization of the obstacle, and the method comprises the following steps:
calculating the three-dimensional volume of each obstacle avoidance selectable space by using the three-dimensional coordinates of each obstacle avoidance selectable space in the three-dimensional characteristics, and comparing the three-dimensional volumes of the plurality of obstacle avoidance selectable spaces with the three-dimensional volume of the robot, wherein,
if the three-dimensional volumes of the AA 'space and the B' space are both larger than or equal to the three-dimensional volume of the robot, the AA 'space and the B' space are both used as effective obstacle avoidance spaces;
if the three-dimensional volume of the AA ' space is larger than or equal to that of the robot and the three-dimensional volume of the B ' space is smaller than that of the robot, taking the AA ' space as an effective obstacle avoidance space;
if the three-dimensional volume of the B ' B space is larger than or equal to that of the robot and the three-dimensional volume of the AA ' space is smaller than that of the robot, taking the B ' B space as an effective obstacle avoidance space;
if the three-dimensional volumes of the AA 'space and the B' space are smaller than the three-dimensional volume of the robot, the AA 'space and the B' space are both used as non-effective obstacle avoidance spaces;
when at least one effective obstacle avoidance space exists, setting an optimization function of an obstacle avoidance path in each effective obstacle avoidance space according to the highest path smoothness and the shortest path length, wherein the optimization function of the obstacle avoidance path is as follows:
in the formula (I), the compound is shown in the specification,
to characterize the optimization function with the highest path smoothness for the obstacle avoidance path,
for the optimisation function of the shortest path length characterizing the obstacle avoidance path, p i The three-dimensional coordinates of the ith path point in the obstacle avoidance path are obtained, N is the total number of the path points in the obstacle avoidance path, and i is a metering constant;
setting a solving constraint condition of an optimization function of an obstacle avoidance path, wherein the solving constraint condition is as follows:
Wherein, | p i A | is p i Distance to A, | p i A' | is p i Distance to A' | p i B | is p i Distance to B, | p i B' | is p i Distance to B ', O is characterized as the center point of the robot, C is the left boundary of the robot, A' is the right boundary of the robot, | OC | is the distance of O to C, | OC '| is the distance of O to C, | AA']Is AA 'space, [ BB']Is BB' space;
solving is carried out on the basis of the solving constraint condition and the optimization functions of the obstacle avoidance paths to obtain an obstacle avoidance path of an effective obstacle avoidance space;
and taking the effective obstacle avoidance space and the obstacle avoidance path as three-dimensional obstacle avoidance parameters of the robot.
4. The robot path obstacle avoidance method based on the 3D technology as claimed in claim 3, wherein: and when no effective obstacle avoidance space exists, the robot stops in situ to perform early warning.
5. The robot path obstacle avoidance method based on the 3D technology as claimed in claim 4, wherein: the construction of the robot path obstacle avoidance model comprises the following steps:
taking the three-dimensional characteristics of the obstacle as an input item of a CNN (neural network), taking the three-dimensional obstacle avoidance parameters of the robot as an output item of the CNN, and performing model training by using the CNN based on the input item and the output item to obtain a robot path obstacle avoidance model, wherein the model expression of the robot path obstacle avoidance model is as follows:
Out[Y]＝CNN(In[X])；
in the formula, out Y is the three-dimensional obstacle avoidance parameter of the robot, inX is the three-dimensional characteristic of the obstacle, and CNN is the CNN neural network.
6. The robot path obstacle avoidance method based on the 3D technology as claimed in claim 5, wherein: the three-dimensional feature of real-time barrier of monitoring on the robot path of travel includes:
taking an obstacle closest to a robot in a traveling direction on a traveling path as a real-time obstacle, detecting three-dimensional coordinates of the obstacle by using a three-dimensional radar carried by the robot, and respectively extracting three-dimensional coordinates of a plurality of obstacle avoidance selectable spaces of the real-time obstacle;
and taking the three-dimensional coordinates of the real-time obstacle and the three-dimensional coordinates of the plurality of obstacle avoidance selectable spaces as the three-dimensional characteristics of the real-time obstacle.
7. The robot path obstacle avoidance method based on the 3D technology as claimed in claim 6, wherein: the method for obtaining the real-time three-dimensional obstacle avoidance parameters of the robot by using the robot path obstacle avoidance model based on the three-dimensional characteristics of the real-time obstacles comprises the following steps:
inputting the three-dimensional characteristics of the real-time obstacle to the robot path obstacle avoidance model, and outputting real-time three-dimensional obstacle avoidance parameters of the robot by the robot path obstacle avoidance model, wherein the real-time three-dimensional obstacle avoidance parameters comprise a real-time effective obstacle avoidance space and a real-time obstacle avoidance path of the robot.
8. The method as claimed in claim 7, wherein the three-dimensional feature detection distance of the obstacle of the robot is greater than the safety braking distance of the robot.
9. The robot path obstacle avoidance method based on the 3D technology as claimed in claim 8, wherein when the number of real-time obstacle avoidance paths is greater than 1, evaluation weights of path smoothness and path length are set, and the path smoothness and the path length are weighted and summed as a selection function for selecting the real-time obstacle avoidance path, the selection function being:
where Jarge is the evaluation value of the real-time obstacle avoidance path,
for the evaluation value of the path smoothness of the real-time obstacle avoidance path,
w and V are respectively evaluation weights of path smoothness and path length for the path length evaluation value of the real-time obstacle avoidance path;
and the robot carries out real-time autonomous obstacle avoidance according to the real-time obstacle avoidance path with the highest evaluation value.
10. An obstacle avoidance system of the robot path obstacle avoidance method based on the 3D technology according to any one of claims 1 to 9, comprising a three-dimensional radar and a data processor, wherein the three-dimensional radar is in communication connection with the data processor, the three-dimensional radar is used for detecting three-dimensional features of obstacles, the data processor is used for receiving the three-dimensional features of the obstacles and obtaining three-dimensional obstacle avoidance parameters of the robot based on the three-dimensional features of the obstacles by using a robot path obstacle avoidance model, and the robot path obstacle avoidance model is built in the data processor.
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