A Path Planning Method Based on Improved A* and Fuzzy Control DWA of Underground Mine Vehicles
Abstract
:1. Introduction
- (1)
- The logarithmic function is introduced to improve the heuristic function coefficient. The adaptive adjustment of the A* algorithm is realized, and the key node selection strategy and 3 times Clamped-B spline are used to optimize and smooth the global path.
- (2)
- A DWA fuzzy controller based on the fuzzy control principle is proposed and designed, which adjusts the coefficient weight of the DWA evaluation function in real-time by judging the distance between the vehicle, obstacles, and target points.
- (3)
- A hybrid path planning method based on the improved A* algorithm and the fuzzy control DWA algorithm is proposed, and the global path key points are used as the local target points of the DWA to guide the vehicle and perform dynamic obstacle avoidance.
2. Related Work
3. Methods
3.1. Improved A* Algorithm
3.1.1. Optimization Heuristic Function
3.1.2. Key Node Selection Strategy
3.1.3. Path Smoothing
3.1.4. Simulation Experiment
3.2. Improved DWA Algorithm
3.2.1. DWA Algorithm
3.2.2. DWA Fuzzy Controller Design
- Fuzzification
- Establish fuzzy rules.
3.2.3. Simulation Experiment
3.3. Fusion of Path Planning Method
4. Experiments
4.1. Experimental Settings
4.2. Analysis of Experimental Results
- Unknown environment
- Dynamic environment
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Algorithm | Number of Nodes | Planning Time (ms) | Path Length | |
---|---|---|---|---|
Scenario 1 | A* | 172 | 213.915 | 159.682 |
Extended A* | 166 | 193.178 | 154.424 | |
Improved A* | 143 | 186.308 | 149.731 | |
Scenario 2 | A* | 227 | 562.713 | 231.812 |
Extended A* | 209 | 540.341 | 228.453 | |
Improved A* | 189 | 494.104 | 217.036 |
Rule Number | Input | Output | |||
---|---|---|---|---|---|
G | O | α | β | γ | |
1 | S | S | M | M | S |
2 | S | M | L | M | S |
3 | S | L | L | S | S |
4 | M | S | M | M | S |
5 | M | M | M | M | M |
6 | M | L | M | S | M |
7 | L | S | S | L | M |
8 | L | M | S | L | M |
9 | L | L | L | M | L |
Parameter | Value | Parameter | Value |
---|---|---|---|
α | 0.15 | Maximum angular rate | 60 rad/s |
β | 0.4 | Maximum linear acceleration | 0.1 m/s2 |
γ | 0.3 | Trajectory prediction time | 2 s |
Maximum linear speed | 1 m/s |
Experiment | Algorithm | Planning Time (s) | Path Length | Success Rate |
---|---|---|---|---|
Scenario 1 | DWA | 235.172 | 196.342 | 90% |
improved DWA | 246.374 | 184.751 | 96% | |
Scenario 2 | DWA | 219.532 | 174.285 | 94% |
improved DWA | 224.784 | 170.764 | 98% | |
Scenario 3 | DWA | 220.429 | 175.479 | 86% |
improved DWA | 226.425 | 169.427 | 96% |
Name | Parameters |
---|---|
Shape | 2490 × 1550 × 616 mm |
Bearing spacing | 1900 mm |
Wheel spacing | 1355 mm |
Maximum speed | 40 km/h |
Steering type | Four-wheel steering |
Braking type | Four-wheel disc brake |
Equipment | Model |
---|---|
Computer | CPU i7-9700 |
Graphics card | |
RTX3060 | |
LIDAR | Velodyne VLP-16 |
IMU | LPMS-IG1 |
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Share and Cite
Zhang, C.; Yang, X.; Zhou, R.; Guo, Z. A Path Planning Method Based on Improved A* and Fuzzy Control DWA of Underground Mine Vehicles. Appl. Sci. 2024, 14, 3103. https://doi.org/10.3390/app14073103
Zhang C, Yang X, Zhou R, Guo Z. A Path Planning Method Based on Improved A* and Fuzzy Control DWA of Underground Mine Vehicles. Applied Sciences. 2024; 14(7):3103. https://doi.org/10.3390/app14073103
Chicago/Turabian StyleZhang, Chuanwei, Xinyue Yang, Rui Zhou, and Zhongyu Guo. 2024. "A Path Planning Method Based on Improved A* and Fuzzy Control DWA of Underground Mine Vehicles" Applied Sciences 14, no. 7: 3103. https://doi.org/10.3390/app14073103
APA StyleZhang, C., Yang, X., Zhou, R., & Guo, Z. (2024). A Path Planning Method Based on Improved A* and Fuzzy Control DWA of Underground Mine Vehicles. Applied Sciences, 14(7), 3103. https://doi.org/10.3390/app14073103