CN113074730A - Underwater path planning method and system - Google Patents

Underwater path planning method and system Download PDF

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CN113074730A
CN113074730A CN202110285235.XA CN202110285235A CN113074730A CN 113074730 A CN113074730 A CN 113074730A CN 202110285235 A CN202110285235 A CN 202110285235A CN 113074730 A CN113074730 A CN 113074730A
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underwater vehicle
underwater
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water flow
path planning
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CN113074730B (en
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李渝舟
金山
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Huazhong University of Science and Technology
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Abstract

The invention discloses an underwater path planning method and system, and belongs to the technical field of path planning. The influence of water flow in the underwater environment is large, most of obstacles under water are not static, but the movement of the underwater vehicle is influenced by the water flow when the obstacles move along with the water flow, the factors are fully considered, and a cost function aiming at the underwater environment is designed by combining the kinematics characteristic of the underwater vehicle, the influence of the water flow, the running speed, the running time and the like of the underwater vehicle; when the track is optimized, a safe and dynamic feasible track can be generated by adopting a BSpline algorithm in combination with the speed of water flow and the smoothness of the track, and the method is more suitable for path planning of an underwater environment; and the invention adopts the vision SLAM to construct the underwater map, compared with sonar, the invention is cheaper and easier to obtain, and the cost is lower.

Description

Underwater path planning method and system
Technical Field
The invention belongs to the technical field of path planning, and particularly relates to an underwater path planning method and system.
Background
Since the 21 st century, with the increasing severity of land resource shortage, population expansion, environmental deterioration, and other problems, various countries have been focusing on oceans to accelerate the development and utilization of oceans. The underwater vehicle is used as an important tool for developing and exploring the ocean, and is very suitable for underwater searching, underwater identification and underwater salvage operation. The path planning technology is used as a core part of the underwater vehicle, and the height of the path planning level marks the height of the intelligent level of the underwater vehicle. Therefore, the research on the path planning algorithm of the underwater vehicle is crucial to the development of the underwater vehicle.
At present, the underwater path planning algorithm is developed very rapidly, and the path planning algorithms commonly used in the underwater mainly include an algorithm A, an RRT algorithm, a Hybrid algorithm A and the like. The A-star algorithm adopts Euclidean geometric distance as a cost function, the kinematics characteristic of the underwater vehicle is not considered, and the generated track is often not in accordance with the actual movement condition. When the RRT algorithm is used for path planning, the influence of underwater water flow on the motion of the underwater vehicle is not considered, and large deviation can occur in a real underwater environment. Hybrid a algorithms deal with static obstacles that do not take into account that underwater obstacles are not stationary due to the effect of water flow, but move with the water flow. Therefore, it is desirable to design a path planning algorithm suitable for underwater environments.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides an underwater path planning method and an underwater path planning system, aiming at improving the existing path planning and optimizing algorithm aiming at an underwater operation environment and generating a safe and dynamic feasible track for an underwater vehicle.
In order to achieve the above object, the present invention provides an underwater path planning method, comprising:
s1, positioning an underwater vehicle and obtaining a point cloud picture of the surrounding environment;
s2, constructing a dense map by using the pose information of the positioning equipment and the point cloud map;
s3, planning a path of the underwater vehicle by using a Hybrid A algorithm in combination with the kinematic characteristics of the underwater vehicle, the influence of water flow on the energy consumption of the underwater vehicle, the running speed of the underwater vehicle and the running time of the underwater vehicle;
s4, optimizing the planned path by using a Bspline algorithm according to the direction of the obstacle relative to the underwater vehicle and the water flow direction to obtain a final operation path of the underwater vehicle; wherein, the direction of the barrier relative to the underwater vehicle is obtained according to the density map.
Further, step S1 is to use the vision sensor to locate the underwater vehicle and obtain a cloud point map of the surrounding environment, so as to reduce the cost.
Further, step S2 is specifically to construct an ESDF map by using the pose information and the point cloud map of the vision sensor, so as to query distance and gradient information of the obstacle, thereby reducing the calculation amount.
Further, step S3 specifically includes:
01. predicting the arrival node of the underwater vehicle at the next moment:
using a cost function ftotal＝λ1J(T)+λ2Wc+λ3T+λ4FvSelecting a node with the minimum cost value in a neighborhood set by the underwater vehicle as a next-time arrival node of the underwater vehicle;
ftotalvalues representing the total cost function, J (T) representing the kinematic behaviour of the underwater vehicle, WcRepresenting the influence of water flow in the underwater environment on the energy consumption of the underwater vehicle; lambda [ alpha ]1、λ2、λ3、λ4Representing a set constant, T representing the operating time of the underwater vehicle, FvRepresenting a speed limit for the underwater vehicle;
02. collision detection: judging whether the position of the barrier moving along with the water flow in the delta t time is the same as the node position predicted in the corresponding time period; if yes, judging that collision occurs, and continuing to execute the step 01-02 in the rest nodes; if not, the process proceeds to step S4.
Further, the influence W of water flow in the underwater environment on the energy consumption of the underwater vehiclecThe expression is as follows:
Figure BDA0002980184900000031
vwindicating the speed, v, of the water flowcRepresenting the velocity of the underwater vehicle.
Further, the speed limit F of the underwater vehiclevThe expression of (a) is:
Fv＝fxv+fyv+fzv
Figure BDA0002980184900000032
Figure BDA0002980184900000036
vμcrepresenting underwater vehicle velocity vcVelocity components in the x, y, z axes, vmaxRepresenting the maximum set underwater vehicle speed, fμvA cost value representing the velocity of the underwater vehicle on one of the axes.
Further, step S4 is specifically to select f by using the following cost functionsumThe position of the minimum control point realizes the optimization of the track;
fsum＝λ5fw+λ6fs
Figure BDA0002980184900000033
Figure BDA0002980184900000034
Figure BDA0002980184900000035
fsumrepresenting the total cost function, fsCost function representing the smoothness of the curve, fwCost function, Q, representing the effect of water flow on trajectoryiIndicating the position of the control point to be optimized, pbRepresenting the number of times of the spline curve, N +1 representing the number of control points, pioDirection vector, v, representing obstacle relative to control pointicRepresenting the velocity vector, λ, of the water flow5Indicating a set constant.
In general, the above technical solutions contemplated by the present invention can achieve the following advantageous effects compared to the prior art.
The scheme of the invention is more suitable for underwater environment. The influence of water flow in the underwater environment is large, most of obstacles under water are not static, but the movement of the underwater vehicle is influenced by the water flow when the obstacles move along with the water flow, the factors are fully considered, and a cost function aiming at the underwater environment is designed by combining the kinematics characteristic of the underwater vehicle, the influence of the water flow, the running speed, the running time and the like of the underwater vehicle; when the track optimization is carried out, a safe and dynamic feasible track can be generated by adopting a BSpline algorithm in combination with the speed of water flow and the smoothness of the track.
The scheme of the invention has lower cost. Most of the traditional underwater submerging devices adopt sonar to build images, and the price is high; the method mainly adopts the vision SLAM to build the underwater map, and the price of the vision sensor is lower than that of sonar and is easier to obtain, so the cost is lower, and the method is more suitable for the application requirement of the underwater vehicle running in shallow water.
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Fig. 1 is a flowchart of an underwater path planning method provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Referring to fig. 1, the underwater path planning method provided by the present invention includes:
s1, positioning an underwater vehicle and obtaining a point cloud picture of the surrounding environment;
positioning the underwater vehicle by using the visual inertial navigation odometer to obtain the position of the underwater vehicle in the environment; meanwhile, in order to reduce cost, a sparse point cloud picture of the surrounding environment is obtained through a camera and is used for constructing a dense picture to carry out path planning.
S2, constructing a dense map by using the pose information of the vision sensor and the point cloud map;
because Distance and gradient information can be conveniently inquired about the obstacle in the ESDF, and the calculation amount is reduced in the actual underwater vehicle motion process, an ESDF (approximate Signed Distance fields) Euclidean Distance field is constructed in the embodiment of the invention.
S3, carrying out path planning on the underwater vehicle by utilizing a Hybrid A-algorithm according to the kinematic characteristics of the underwater vehicle, the influence of water flow on the energy consumption of the underwater vehicle, the operation speed of the underwater vehicle and the operation time of the underwater vehicle;
the invention comprehensively considers the factors of the kinematic characteristics of the underwater vehicle, the influence of water flow on the energy consumption of the underwater vehicle, the running speed of the underwater vehicle and the running time of the underwater vehicle, and designs a Hybrid A algorithm aiming at the underwater environment, wherein the cost function is as follows:
ftotal＝λ1J(T)+λ2Wc+λ3T+λ4Fv
the cost function mainly represents the cost required by the underwater vehicle to move to a certain node when the underwater vehicle moves underwater, the higher the cost value is, the lower the possibility of moving to the point is, and the lower the cost value is, the higher the possibility of moving to the point is.
J (t) represents the kinematics of the underwater vehicle, mainly considering the changes of speed and acceleration, and the expression is:
Figure BDA0002980184900000051
pgindicating the position of the target point, vgRepresenting the velocity, p, of the target pointcIs the position of the current point, vcIs the speed of the current point (underwater vehicle);
Wcshows the influence of water flow in the underwater environment on the energy consumption of the underwater vehicle, when the speed of the water flow is opposite to that of the underwater vehicle, the waterThe underwater vehicle needs to consume more energy to maintain the current motion, and when the speed of the water flow is the same as that of the underwater vehicle, the underwater vehicle consumes less energy. The expression is as follows:
Figure BDA0002980184900000052
vwindicating the speed, v, of the water flowcRepresenting the speed of the underwater vehicle;
t denotes the running time of the underwater vehicle, vmaxRepresenting maximum speed, v, of underwater vehiclecRepresenting the velocity of the underwater vehicle, which can be decomposed into v, since it is a vectorμcWherein
Figure BDA0002980184900000062
I.e. the velocity is resolved on the x-axis, y-axis, z-axis, fμvA cost value representing the speed of the underwater vehicle on one of the axes when the speed of the underwater vehicle is greater than vmaxThere is a certain cost value. FvRepresenting the sum of the cost values on three axes, the effect of speed on the underwater vehicle can be characterized: when the speed is too high, the underwater vehicle is unstable in motion and has a large cost value; when the speed is small, the underwater vehicle moves stably, the cost value is small, wherein fμvThe expression of (a) is:
Figure BDA0002980184900000061
Fv＝fxv+fyv+fzv
vμcrepresenting speed in one axis, fxvCost value, f, representing the velocity on the x-axisyvCost value, f, representing velocity on the y-axiszvA cost value representing velocity in the z-axis; lambda [ alpha ]1、λ2、λ3、λ4Represents a set constant;
selecting a node with the minimum cost value in a neighborhood set by the underwater vehicle as a next-time arrival node of the underwater vehicle by using the cost function;
when a trajectory in a space is predicted, collision detection needs to be performed on the trajectory. In the conventional path planning algorithm, the situation that when an obstacle is static and moves, the obstacle collides is considered. The invention considers the influence of water flow, the underwater barrier moves along with the water flow under water, and the movement speed of the barrier is considered to be consistent with the speed of the water flow, wherein the water flow speed is vwThen, after the time Δ t, the distance that the obstacle moves with the water flow is Δ t · vwIf the position of the obstacle is the same as the predicted node position, the predicted track collides with the obstacle; continuously searching the node with the minimum cost value from the rest nodes and carrying out collision detection until finding out a track which cannot collide with the obstacle;
and S4, optimizing the planned path by using a B-spline curve Bspline algorithm according to the direction of the obstacle relative to the underwater vehicle and the water flow direction to obtain the final operation path of the underwater vehicle.
The water flow in the underwater environment can cause certain deviation of the track generated by the robot, so that the Bslpine algorithm is improved by combining the influence of the water flow when the track is optimized. Specifically, the distance and gradient information of the obstacle closest to the underwater vehicle can be conveniently obtained in the ESDF, namely the direction of the obstacle relative to the underwater vehicle can be obtained, and when the water flow speed is consistent with the direction, the water flow pushes the underwater vehicle to the obstacle. When the direction is opposite, the water flow pushes the underwater vehicle away from the barrier. The invention utilizes the information to optimize the control point (Q) to be optimized in the Bslpine algorithmpb,Qpb+1,...,QN-pbAnd (3) adjusting (namely the path planned in the step (3)), so as to realize the optimization of the track.
Selecting the position of the control point using a cost function such thatsumAnd at the minimum, the optimization of the track is realized by changing the position of a control point in the track:
fsum＝λ5fw+λ6fs
Figure BDA0002980184900000071
Figure BDA0002980184900000072
Figure BDA0002980184900000073
fsumrepresenting the total cost function, fsCost function representing the smoothness of the curve, fwCost function, Q, representing the effect of water flow on trajectoryiDenotes that the control point to be optimized is, pbRepresenting the number of times of the spline curve, N +1 representing the number of control points, pioA direction vector representing the relative control point of the obstacle, which value is conveniently obtained from the ESDF map, vicRepresenting the velocity vector of the water flow.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (8)

1. An underwater path planning method, comprising:
s1, positioning an underwater vehicle and obtaining a point cloud picture of the surrounding environment;
s2, constructing a dense map by using the pose information of the positioning equipment and the point cloud map;
s3, planning a path of the underwater vehicle by using a Hybrid A algorithm in combination with the kinematic characteristics of the underwater vehicle, the influence of water flow on the energy consumption of the underwater vehicle, the running speed of the underwater vehicle and the running time of the underwater vehicle;
s4, optimizing the planned path by using a Bspline algorithm according to the direction of the obstacle relative to the underwater vehicle and the water flow direction to obtain a final operation path of the underwater vehicle; wherein, the direction of the barrier relative to the underwater vehicle is obtained according to the density map.
2. The method for underwater path planning according to claim 1, wherein step S1 is specifically to locate the underwater vehicle by using a vision sensor and obtain a cloud point map of the surrounding environment.
3. The underwater path planning method according to claim 2, wherein the step S2 is specifically configured to construct the ESDF map by using pose information of the vision sensor and a point cloud map.
4. The underwater path planning method according to any one of claims 1 to 3, wherein the step S3 specifically includes:
01. predicting the arrival node of the underwater vehicle at the next moment:
using a cost function ftotal＝λ1J(T)+λ2Wc+λ3T+λ4FvSelecting a node with the minimum cost value in a neighborhood set by the underwater vehicle as a next-time arrival node of the underwater vehicle;
ftotalvalues representing the total cost function, J (T) representing the kinematic behaviour of the underwater vehicle, WcRepresenting the influence of water flow in the underwater environment on the energy consumption of the underwater vehicle; lambda [ alpha ]1、λ2、λ3、λ4Representing a set constant, T representing the operating time of the underwater vehicle, FvRepresenting a speed limit for the underwater vehicle;
02. collision detection: judging whether the position of the barrier moving along with the water flow in the delta t time is the same as the node position predicted in the corresponding time period; if yes, judging that collision occurs, and continuing to execute the step 01-02 in the rest nodes; if not, the process proceeds to step S4.
5. An underwater path planning method according to claim 4 in which the effect W of water flow in the underwater environment on the energy consumption of the underwater vehiclecThe expression is as follows:
Figure FDA0002980184890000021
vwindicating the speed, v, of the water flowcRepresenting the velocity of the underwater vehicle.
6. An underwater path planning method according to claim 4 in which the speed limit of the underwater vehicle is FvThe expression is as follows:
Fv＝fxv+fyv+fzv
Figure FDA0002980184890000022
Figure FDA0002980184890000023
vμcrepresenting underwater vehicle velocity vcVelocity components in the x, y, z axes, vmaxRepresenting the maximum set underwater vehicle speed, fμvA cost value representing the velocity of the underwater vehicle on one of the axes.
7. An underwater path planning method according to any one of claims 1 to 6, wherein step S4 is specifically to select f using the following cost functionsumThe position of the minimum control point realizes the optimization of the track;
fsum＝λ5fw+λ6fs
Figure FDA0002980184890000024
Figure FDA0002980184890000025
Figure FDA0002980184890000026
fsumrepresenting the total cost function, fsCost function representing the smoothness of the curve, fwCost function, Q, representing the effect of water flow on trajectoryiIndicating the position of the control point to be optimized, pbRepresenting the number of times of the spline curve, N +1 representing the number of control points, pioDirection vector, v, representing obstacle relative to control pointicRepresenting the velocity vector, λ, of the water flow5Indicating a set constant.
8. An underwater path planning system, comprising: a computer-readable storage medium and a processor;
the computer-readable storage medium is used for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium and execute the underwater path planning method of any one of claims 1 to 7.
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