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An Improved Hybrid Path Planning Algorithm in Indoor Environment Cover
By: Jiaxiang Fang and  Shuping Xu  
Open Access
|Jul 2024

Figures & Tables

Figure 1.

Raster map model
Raster map model

Figure 2.

A-Star algorithm smoothing processing diagram
A-Star algorithm smoothing processing diagram

Figure 3.

A-Star algorithm path smoothing results in 30×30 environment
A-Star algorithm path smoothing results in 30×30 environment

Figure 4.

Force analysis diagram of mobile robot
Force analysis diagram of mobile robot

Figure 5.

Modified repulsion field parameters force analysis
Modified repulsion field parameters force analysis

Figure 6.

Path planning comparison
Path planning comparison

Figure 7.

Complex obstacle test comparison
Complex obstacle test comparison

Figure 8.

Hybrid algorithm model diagram
Hybrid algorithm model diagram

Figure 9.

Static path comparison diagram
Static path comparison diagram

Figure 10.

Dynamic path planning diagram
Dynamic path planning diagram

Figure 11.

Hands-free robot platform
Hands-free robot platform

Figure 12.

Actual test scenario
Actual test scenario

Figure 13.

Actual scene construction effect
Actual scene construction effect

Figure 14.

A-Star Hybrid DWA algorithm path planning
A-Star Hybrid DWA algorithm path planning

Figure 15.

Improved A-Star hybrid improved artificial potential field algorithm
Improved A-Star hybrid improved artificial potential field algorithm

Algorithm comparison in static environment

AlgorithmPath length/mSearch time/sDoes the algorithm have the ability to handle dynamic obstacles
A-Star45.366.72No
IAPF48.0010.43Yes
DWA48.8628.21Yes
Hybrid algorithm46.548.14Yes

Comparison of the effects of A-Star algorithm improvement

AlgorithmPath length/mTime for path finding/sNumber of expansion nodesIs there a turning point
A-Star22.425.9166Yes
Improved A-Star21.565.559No

Results of algorithm comparison in real environment

Path planning algorithmPath length/mNumber of nodes passed throughSearch time/s
A-Star Hybrid DWA3.6612654.42
Hybrid algorithm in this paper3.249248.36

Comparison results of improved algorithm

Experiment NameAlgorithmPath length/mRun time/sNumber of cycles
Path planning testingAPF49.9707106.186677447
IAPF48.0030375.430491440

Complex obstacle testingAPF
IAPF51.5196906.801836451
Language: English
Page range: 67 - 81
Published on: Jul 21, 2024
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Jiaxiang Fang, Shuping Xu, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.