Research on a Random Route-Planning Method Based on the Fusion of the A* Algorithm and Dynamic Window Method
Abstract
:1. Introduction
2. Improved A* Algorithm
2.1. Optimize Search Point Selection Strategy
2.2. Inspiration Function of Optimization Algorithm
2.3. Redundant Point Removal Policy
3. Improved Dynamic Window Algorithm
3.1. Establishment of the Robot’s Motion Model
3.2. Determination of the Robotic Velocity Range
3.3. Improvement of the Evaluation Function
4. Simulation and Verification of the Robot Random Obstacle Avoidance Algorithm Based on an Improved A* Algorithm
4.1. The Experiment Analysis of an Improved A* Algorithm
4.2. Analysis of Random Barrier Avoidance Effect of the Improved A* Algorithm Fusion Dynamic Window Method
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
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α | Reserved Five Directions | Abandoned Three Directions |
---|---|---|
[337.5°, 360°) ∪ [0°, 22.5°) | n1 n2 n3 n4 n5 | n6 n7 n8 |
[22.5°, 67.5°) | n1 n2 n3 n5 n8 | n4 n6 n7 |
[67.5°, 112.5°) | n2 n3 n5 n7 n8 | n1 n4 n6 |
[112.5°, 157.5°) | n3 n5 n6 n7 n8 | n1 n2 n4 |
[157.5°, 202.5°) | n4 n5 n6 n7 n8 | n1 n2 n3 |
[202.5°, 247.5°) | n1 n4 n6 n7 n8 | n2 n3 n5 |
[247.5°, 292.5°) | n1 n2 n4 n6 n7 | n3 n5 n8 |
[292.5°, 337.5°) | n1 n2 n3 n4 n6 | n5 n7 n8 |
Algorithms | Environment I | Environment II | Environment III | ||||||
---|---|---|---|---|---|---|---|---|---|
after Smoothing Length /m | Time/s | Number of Turning Points | after Smoothing Length /m | Time/s | Number of Turning Points | after Smoothing Length /m | Time/s | Number of Turning Points | |
Traditional A* Algorithm | 33.1891 | 0.0075562 | 15 | 31.2136 | 0.01507 | 24 | 20.0765 | 0.004029 | 18 |
An Improved A* Algorithm for a 5 × 5 Neighborhood Search | 33.2204 | 0.017705 | 14 | 32.1737 | 0.02704 | 19 | 20.0739 | 0.011244 | 15 |
An Improved A* Algorithm for Path Planning | 33.1737 | 0.035745 | 8 | 31.7024 | 0.044917 | 12 | 20.1634 | 0.019895 | 12 |
An Improved A* Algorithm Based on Hop Search | 32.6157 | 0.055889 | 10 | 31.7562 | 0.062665 | 13 | 19.7577 | 0.029458 | 13 |
Number of Random Obstacles | Path Length/m | Time/s |
One random obstacle | 28.9960 | 112.3578 |
Two random obstacle | 28.9770 | 121.7401 |
Three random obstacle | 29.3370 | 122.9477 |
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Sun, Y.; Zhao, X.; Yu, Y. Research on a Random Route-Planning Method Based on the Fusion of the A* Algorithm and Dynamic Window Method. Electronics 2022, 11, 2683. https://doi.org/10.3390/electronics11172683
Sun Y, Zhao X, Yu Y. Research on a Random Route-Planning Method Based on the Fusion of the A* Algorithm and Dynamic Window Method. Electronics. 2022; 11(17):2683. https://doi.org/10.3390/electronics11172683
Chicago/Turabian StyleSun, Yicheng, Xianliang Zhao, and Yazhou Yu. 2022. "Research on a Random Route-Planning Method Based on the Fusion of the A* Algorithm and Dynamic Window Method" Electronics 11, no. 17: 2683. https://doi.org/10.3390/electronics11172683
APA StyleSun, Y., Zhao, X., & Yu, Y. (2022). Research on a Random Route-Planning Method Based on the Fusion of the A* Algorithm and Dynamic Window Method. Electronics, 11(17), 2683. https://doi.org/10.3390/electronics11172683