An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning
The advancement of mobile robot technology has made path planning a necessary condition for autonomous navigation, but traditional algorithms have issues with efficiency and reliability in dynamic and unstructured environments. This study proposes a Dynamic Hybrid A* (DHA*)–Adaptive Dynamic Window A...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Robotics |
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| Online Access: | https://www.mdpi.com/2218-6581/14/7/90 |
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| author | Yizhe Jia Yong Cai Jun Zhou Hui Hu Xuesheng Ouyang Jinlong Mo Hao Dai |
| author_facet | Yizhe Jia Yong Cai Jun Zhou Hui Hu Xuesheng Ouyang Jinlong Mo Hao Dai |
| author_sort | Yizhe Jia |
| collection | DOAJ |
| description | The advancement of mobile robot technology has made path planning a necessary condition for autonomous navigation, but traditional algorithms have issues with efficiency and reliability in dynamic and unstructured environments. This study proposes a Dynamic Hybrid A* (DHA*)–Adaptive Dynamic Window Approach (ADA-DWA) fusion algorithm for efficient and reliable path planning in dynamic unstructured environments. This paper improves the A* algorithm by introducing a dynamic hybrid heuristic function, optimizing the selection of key nodes, and enhancing the neighborhood search strategy, and collaboratively optimizes the search efficiency and path smoothness through curvature optimization. On this basis, the local planning layer introduces a self-adjusting weight-adaptive system in the DWA framework to dynamically optimize the speed, sampling distribution, and trajectory evaluation metrics, achieving a balance between obstacle avoidance and environmental adaptability. The proposed fusion algorithm’s comprehensive advantages over traditional methods in key operational indicators, including path optimality, computational efficiency, and obstacle avoidance capability, have been widely verified through numerical simulations and physical platforms. This method successfully resolves the inherent trade-off between efficiency and reliability in complex robot navigation scenarios, providing enhanced operational robustness for practical applications ranging from industrial logistics to field robots. |
| format | Article |
| id | doaj-art-4bf4877d247a4ba58e522149f8a7efd0 |
| institution | DOAJ |
| issn | 2218-6581 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Robotics |
| spelling | doaj-art-4bf4877d247a4ba58e522149f8a7efd02025-08-20T03:08:02ZengMDPI AGRobotics2218-65812025-06-011479010.3390/robotics14070090An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path PlanningYizhe Jia0Yong Cai1Jun Zhou2Hui Hu3Xuesheng Ouyang4Jinlong Mo5Hao Dai6Key Laboratory of Testing Technology for Manufacturing Process MOE, Southwest University of Science and Technology, Mianyang 621010, ChinaKey Laboratory of Testing Technology for Manufacturing Process MOE, Southwest University of Science and Technology, Mianyang 621010, ChinaKey Laboratory of Testing Technology for Manufacturing Process MOE, Southwest University of Science and Technology, Mianyang 621010, ChinaKey Laboratory of Testing Technology for Manufacturing Process MOE, Southwest University of Science and Technology, Mianyang 621010, ChinaKey Laboratory of Testing Technology for Manufacturing Process MOE, Southwest University of Science and Technology, Mianyang 621010, ChinaKey Laboratory of Testing Technology for Manufacturing Process MOE, Southwest University of Science and Technology, Mianyang 621010, ChinaSchool of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621000, ChinaThe advancement of mobile robot technology has made path planning a necessary condition for autonomous navigation, but traditional algorithms have issues with efficiency and reliability in dynamic and unstructured environments. This study proposes a Dynamic Hybrid A* (DHA*)–Adaptive Dynamic Window Approach (ADA-DWA) fusion algorithm for efficient and reliable path planning in dynamic unstructured environments. This paper improves the A* algorithm by introducing a dynamic hybrid heuristic function, optimizing the selection of key nodes, and enhancing the neighborhood search strategy, and collaboratively optimizes the search efficiency and path smoothness through curvature optimization. On this basis, the local planning layer introduces a self-adjusting weight-adaptive system in the DWA framework to dynamically optimize the speed, sampling distribution, and trajectory evaluation metrics, achieving a balance between obstacle avoidance and environmental adaptability. The proposed fusion algorithm’s comprehensive advantages over traditional methods in key operational indicators, including path optimality, computational efficiency, and obstacle avoidance capability, have been widely verified through numerical simulations and physical platforms. This method successfully resolves the inherent trade-off between efficiency and reliability in complex robot navigation scenarios, providing enhanced operational robustness for practical applications ranging from industrial logistics to field robots.https://www.mdpi.com/2218-6581/14/7/90path planningDynamic Hybrid A* algorithm (DHA*)dynamic obstacle avoidanceAdaptive Dynamic Window Approach (ADA-DWA)fusion algorithm |
| spellingShingle | Yizhe Jia Yong Cai Jun Zhou Hui Hu Xuesheng Ouyang Jinlong Mo Hao Dai An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning Robotics path planning Dynamic Hybrid A* algorithm (DHA*) dynamic obstacle avoidance Adaptive Dynamic Window Approach (ADA-DWA) fusion algorithm |
| title | An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning |
| title_full | An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning |
| title_fullStr | An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning |
| title_full_unstemmed | An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning |
| title_short | An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning |
| title_sort | improved dha star and ada dwa fusion algorithm for robot path planning |
| topic | path planning Dynamic Hybrid A* algorithm (DHA*) dynamic obstacle avoidance Adaptive Dynamic Window Approach (ADA-DWA) fusion algorithm |
| url | https://www.mdpi.com/2218-6581/14/7/90 |
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