Double-Layer RRT* Objective Bias Anytime Motion Planning Algorithm
Abstract
:1. Introduction
- (1)
- This paper proposes a double-layer RRT* tree structure. In the first layer, initial path information is provided. In the second layer, an iterative optimization process is used to update the selected path and improve the path selection accuracy.
- (2)
- A new feedback-based objective bias strategy is used to obtain the initial path, and the initial path is smoothed by removing redundant processing through segmentation forward pruning.
- (3)
- The second layer of the RRT* scheme optimizes the selected path using the heuristic information provided by the spanning tree structure of the initial path.
2. Motion Planning Problem Statements
2.1. Robot Model and Control Input
2.2. Problem Statement
3. Initial Path Generation Algorithm
3.1. Initial Path Generation
Algorithm 1. Build Initial Path . |
1: 2: for from to do 3: 4: ; 5: ; 6: if then 7: ; 8: else 9: ; 10: end if 11: ; 12: for do 13: ; 14: ; 15: end for 16: ; 17: if then 18: return ; 19: end if 20: end for 21: ; |
3.2. Objective-Biased Sampling Strategy
3.3. Segmented Forward Pruning
4. Optimization Algorithm
4.1. Optimization Algorithm
Algorithm 2. Optimization . |
1: 2: ; 3: while do 4: ; 5: ; 6: ; 7: ; 8: if then 9: ; 10: else 11: ; 12: end if 13: ; 14: for do 15: ; 16: ; 17: end for 18: ; 19: if then 20: ; 21: ; 22: end if 23: end while |
4.2. Reverse Maintenance Strategy
5. Simulation and Experimental Results
5.1. Initial Path Generation Simulation
5.2. Optimization Simulation
6. DOB-RRT* Evaluations in Real Environment
6.1. Experimental Environment Configuration
6.2. Mobile Robot Applications
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
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Mean | Min | Max | ||
---|---|---|---|---|
RRT | Path Time | 0.23 | 0.13 | 0.41 |
Plan Length | 749.52 | 697.15 | 958.43 | |
RRT* | Path Time (s) | 3.81 | 1.51 | 9.22 |
Plan Length | 694.15 | 673.88 | 888.41 | |
DOB-RRT* | Path Time (s) | 0.42 | 0.26 | 1.13 |
Plan Length | 697.91 | 674.29 | 892.13 |
Mean | Min | Max | ||
---|---|---|---|---|
RRT | Path Time (s) | 0.48 | 0.26 | 0.98 |
Plan Length | 711.71 | 656.1 | 811.21 | |
RRT* | Path Time (s) | 3.81 | 1.51 | 9.22 |
Plan Length | 664.71 | 640.94 | 721.05 | |
DOB-RRT* | Path Time (s) | 0.68 | 0.44 | 1.24 |
Plan Length | 660.21 | 642.47 | 726.72 |
RRT* | 2.71 | 2.33 |
DOB-RRT* | 0.53 | 0.38 |
Plan Time (s) | Path Length (m) | ||
---|---|---|---|
0.34 | 2.57 | 2.24 | 3.26 |
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Esmaiel, H.; Zhao, G.; Qasem, Z.A.H.; Qi, J.; Sun, H. Double-Layer RRT* Objective Bias Anytime Motion Planning Algorithm. Robotics 2024, 13, 41. https://doi.org/10.3390/robotics13030041
Esmaiel H, Zhao G, Qasem ZAH, Qi J, Sun H. Double-Layer RRT* Objective Bias Anytime Motion Planning Algorithm. Robotics. 2024; 13(3):41. https://doi.org/10.3390/robotics13030041
Chicago/Turabian StyleEsmaiel, Hamada, Guolin Zhao, Zeyad A. H. Qasem, Jie Qi, and Haixin Sun. 2024. "Double-Layer RRT* Objective Bias Anytime Motion Planning Algorithm" Robotics 13, no. 3: 41. https://doi.org/10.3390/robotics13030041