Hybrid A* autonomous parking path planning method based on artificial potential field guidance

An artificial potential field and path planning technology, applied in navigation, surveying and navigation, road network navigator, etc., can solve problems such as slow convergence speed, large number of node expansion, and lack of directional information

Active Publication Date: 2021-05-07
ZHEJIANG UNIV
View PDF10 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the above-mentioned defects, the present invention aims at problems such as the large number of node extensions, the lack of directional information, and the slow convergence speed in the current autonomous parking planning method with the Hybrid A* algorithm as the core, and proposes a method that uses artificial potential field information to guide nodes. extension method, in order to combine the two methods to obtain an improved planning algorithm

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Hybrid A* autonomous parking path planning method based on artificial potential field guidance
  • Hybrid A* autonomous parking path planning method based on artificial potential field guidance
  • Hybrid A* autonomous parking path planning method based on artificial potential field guidance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050]The application scenario of this embodiment is set to standard vertical parking scene, mainly compared to the performance of the parking path planning algorithm before and after the introduction of the manual potential boot information. This embodiment mainly includesfigure 2 The establishment of the artificial field map shown, such asimage 3 The Hybrid A * algorithm expanded details, etc.Figure 4 As shown, the main performance index analysis is shown in Table 1, where the Total Time refers to the overall consumption of the path planning, the Node number is the number of nodes accessed by the Hybrid A * algorithm in the generation of the final path result, the RS invalid connection The algorithm attempts to connect the current node and destination point at each loop, but does not pass collision detection, resulting in the total number of incomplete times of the operation, and can be seen by RS TIME, the less invalid connection, the more algorithm time short. PATH refers to the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a Hybrid A * autonomous parking path planning method based on artificial potential field guidance. According to the method, an artificial potential field graph is constructed in a regional mode for a priori map, then the artificial potential field graph and real-time pose information of a vehicle serve as input, the overall direction of node expansion of a Hybrid A * algorithm is determined according to the principle that the direction of a vehicle body is kept the same as the direction of a potential field, pruning operation is conducted on node expansion, and a drivable path is generated while few nodes are accessed. According to the method disclosed by the invention, the algorithm running time can be more effectively prolonged while the optimal path planning is ensured, the problem of redundant calculation caused by lack of directivity in the node expansion process of the Hybrid A * algorithm is solved, and the real-time performance of the algorithm is improved while a safe and reliable path is generated by the algorithm.

Description

Technical field[0001]The present invention relates to an unmanned vehicle path planning technique, and more particularly to an autonomous parking path planning method based on a manual potential bootbook-based Hybrid A *.Background technique[0002]With the rapid development of the automotive industry, the rise of artificial intelligence technology, unmanned technology came to life, and became the focus of today's research. In daily life, the automobile is an important means of transportation, and the number of increases has made parking into the primary problem facing by people. The gradually short parking area leads to the safety of the driver needs to be safe, reliably enter the parking space. Automatic parking systems can solve relevant problems to some extent.[0003]Self-parking plan is a key part of the driver's system. Its essence is a path search problem. The main task is to use a priori map to perform model abstraction, combined with the surrounding environment information, to...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/34
CPCG01C21/3446
Inventor 李翔沈会良柳一昊金晓
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap