Unmanned vehicle path planning algorithm based on improved RRT algorithm

A technology for unmanned vehicles and path planning, applied in vehicle position/route/height control, motor vehicles, two-dimensional position/course control, etc., can solve the problems of unsatisfied vehicle kinematics constraints, long search time, and large memory usage and other issues, to achieve the effect of good engineering practical value, less memory usage, and shortened path length

Pending Publication Date: 2022-05-27
DUT ARTIFICIAL INTELLIGENCE INST DALIAN +1
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Problems solved by technology

[0004] The main purpose of the present invention is: the present invention proposes a kind of improved RRT that is applied to the field of smart cars in view of the problems that the algorithm search time is long, the path is too long, the memory is too large, and the vehicle kinematics constraints are not satisfied in the RRT algorithm. path planning algorithm

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  • Unmanned vehicle path planning algorithm based on improved RRT algorithm
  • Unmanned vehicle path planning algorithm based on improved RRT algorithm
  • Unmanned vehicle path planning algorithm based on improved RRT algorithm

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[0021] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and technical solutions.

[0022] An unmanned vehicle path planning algorithm based on improved RRT algorithm, the steps are as follows:

[0023] Step 1: Initialize the map space, the pose of the starting point and the target point, the basic parameters of the car, the algorithm parameters and the obstacle information in the environment;

[0024] Step 1: Initialize the map space and enter the starting point X of the unmanned vehicle init and end point X goal And the obstacle information distributed in the environment; input the basic parameter information of the unmanned vehicle, including the minimum turning radius R min , maximum front wheel angle and wheelbase L, so that the vehicle can satisfy the kinematic constraints during driving. The schematic diagram of the kinematic constraints is shown in figure 2 shown. front wheel angle les...

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Abstract

The invention belongs to the field of unmanned driving path planning, and relates to an unmanned vehicle path planning algorithm based on an improved RRT algorithm. Initializing positions and course angles of a map space, a starting point and a target point, automobile basic parameters, algorithm parameters and obstacle information in the environment; and introducing a target probability sampling strategy to obtain the position of a random sampling point Xrand. And defining a nearest node Xnear by using a multi-information fusion evaluation method. And expanding the random tree by using a target bias expansion mode, and performing smooth connection by using a Bezier curve in a node connection process. And repeating the steps until the random tree is expanded to the connectable range of the target point, and directly connecting the random tree and the target point by using a Reeds-Shepp curve. According to the method, the convergence speed of the algorithm can be effectively improved, the path length is shortened, the path smoothness is improved, the memory occupation is reduced, the kinematics constraint of the intelligent automobile is considered, and the method has good engineering practical value.

Description

technical field [0001] The invention belongs to the field of unmanned path planning, relates to the improvement of a rapidly expanding random tree (rapidly-exploring random tree, RRT) algorithm, and in particular relates to an improved unmanned vehicle path planning algorithm based on the RRT algorithm Background technique [0002] With the vigorous development of intelligent driving technology, unmanned vehicles have gradually entered the public eye. Path planning is one of the important core technologies of unmanned vehicles. It can find a continuous collision-free path from the initial pose to the target pose in the entire pose space. Constraints such as kinematic constraints. At present, the widely used path planning algorithms include A* algorithm, genetic algorithm, ant colony algorithm, artificial potential field method, fast expanding random number algorithm and so on. Among them, the RRT algorithm adopts the planning method of random sampling, does not need to pre...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0214G05D1/0221G05D2201/0212Y02T10/40
Inventor 冷阳唐琪康斌
Owner DUT ARTIFICIAL INTELLIGENCE INST DALIAN
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