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A Vehicle Path Planning Method Based on Improved Bidirectional Informed-rrt*

A path and vehicle technology, applied in vehicle position/route/altitude control, motor vehicle, two-dimensional position/navigation control and other directions, can solve the problem that the vehicle cannot reach the target point, cannot meet the vehicle driving requirements, waste search time, etc. problem, to achieve the effect of high path planning efficiency, reducing time consumption and reducing randomness

Active Publication Date: 2022-07-05
HEFEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, when the algorithm plans the initial path, there are many useless searches for blank areas, which wastes search time, and the planning efficiency is low, and the planned path cannot meet the requirements of vehicle driving, so that the vehicle cannot reach the target point quickly and effectively.

Method used

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  • A Vehicle Path Planning Method Based on Improved Bidirectional Informed-rrt*
  • A Vehicle Path Planning Method Based on Improved Bidirectional Informed-rrt*
  • A Vehicle Path Planning Method Based on Improved Bidirectional Informed-rrt*

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Embodiment Construction

[0061] In this embodiment, as figure 1 As shown, a vehicle path planning method based on improved bidirectional informed-RRT* includes the following steps:

[0062] Step 1. Use the lidar sensor or depth camera sensor that comes with the vehicle to collect environmental information around the vehicle, and use it to build a grid map, mark each grid in the grid map as an obstacle space or free space, and after marking Select a starting point x in the raster map of start and the target point x goal ; image 3 and Figure 4 , the black part is the obstacle space, and the white part is the free space;

[0063] Step 2. Adopt a combined expansion strategy combining target constraints and target gravity and integrate the traditional two-way RRT* algorithm to sample in the free space of the grid map to obtain the initial path;

[0064] Step 2.1. Define two fast-exploring random trees Ta and Tb;

[0065] Step 2.2. Obtain a new node x of the fast-exploring random tree Ta new_a , to...

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Abstract

The invention discloses a vehicle path planning method based on an improved two-way informed-RRT*, comprising: 1 establishing a grid map, and determining a starting point and a target point; 3. Use the improved two-way informed‑RRT* algorithm to obtain the elliptical state subset space and obtain sampling points; 4. Use the target gravity fusion two-way RRT* algorithm to optimize the initial path to obtain the optimized path, and update the ellipse area with the length of the optimized path. Sampling in the updated ellipse area to obtain sampling points; 5. Repeat step 4 to obtain the final path; 6. After pruning the final path, use the fourth-order Bezier curve for smoothing. The invention reduces sampling randomness, improves convergence efficiency, generates an optimal path and satisfies vehicle dynamics constraints, so that the vehicle can successfully avoid obstacles and quickly reach the target point.

Description

technical field [0001] The invention relates to a vehicle path planning method based on an improved two-way informed-RRT*, belonging to the field of vehicle path planning. Background technique [0002] At present, with the rapid development of driverless technology, path planning, as one of the key technologies of driverless vehicles, has been paid more and more attention. The path planning of the unmanned vehicle is based on a certain environment model, given the starting point and the target point, and successfully planning a collision-free feasible path in the free space from the starting point to the target point. [0003] Traditional path planning algorithms include artificial potential field method based on construction potential field, genetic algorithm, Dijkstra and A* based on graph search, etc., but the above algorithms all need to model obstacles in a certain space, which are not suitable for complex environments. Path planning in the environment. Rapid Explorat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02
CPCG05D1/0236G05D1/024G05D1/0253G05D1/0257G05D1/0276G05D2201/02
Inventor 姜平于海涛黄鹤吴润晨汤德江
Owner HEFEI UNIV OF TECH
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