Research on autonomous navigation of mobile robots based on IA-DWA algorithm
Abstract To improve the efficiency of mobile robot movement, this paper investigates the fusion of the A* algorithm with the Dynamic Window Approach (DWA) algorithm (IA-DWA) to quickly search for globally optimal collision-free paths and avoid unknown obstacles in time. First, the data from the odom...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-84858-3 |
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| _version_ | 1832594819656974336 |
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| author | Quanling He Zongyan Wang Kun Li Yuting Zhang Menglong Li |
| author_facet | Quanling He Zongyan Wang Kun Li Yuting Zhang Menglong Li |
| author_sort | Quanling He |
| collection | DOAJ |
| description | Abstract To improve the efficiency of mobile robot movement, this paper investigates the fusion of the A* algorithm with the Dynamic Window Approach (DWA) algorithm (IA-DWA) to quickly search for globally optimal collision-free paths and avoid unknown obstacles in time. First, the data from the odometer and the inertial measurement unit (IMU) are fused using the extended Kalman filter (EKF) to reduce the error caused by wheel slippage on the mobile robot’s positioning and improve the mobile robot’s positioning accuracy. Second, the prediction function, weight coefficients, search neighborhood, and path smoothing processing of the A* algorithm are optimally designed to incorporate the critical point information in the global path into the DWA calculation framework. Then, the length of time and convergence speed of path planning are compared and simulated in raster maps of different complexity. In terms of path planning time, the algorithm reduces by 23.3% compared to A*-DWA; in terms of path length, the algorithm reduces by 1.8% compared to A*-DWA, and the optimization iterations converge faster. Finally, the reliability of the improved algorithm is verified by conducting autonomous navigation experiments using a ROS (Robot Operating System) mobile robot as an experimental platform. |
| format | Article |
| id | doaj-art-327fb29aad094d1396148fbd88f3bbba |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-327fb29aad094d1396148fbd88f3bbba2025-01-19T12:19:12ZengNature PortfolioScientific Reports2045-23222025-01-0115111310.1038/s41598-024-84858-3Research on autonomous navigation of mobile robots based on IA-DWA algorithmQuanling He0Zongyan Wang1Kun Li2Yuting Zhang3Menglong Li4North University of China, School of Mechanical EngineeringNorth University of China, School of Mechanical EngineeringNorth University of China, School of Mechanical EngineeringNorth University of China, School of Mechanical EngineeringNorth University of China, School of Mechanical EngineeringAbstract To improve the efficiency of mobile robot movement, this paper investigates the fusion of the A* algorithm with the Dynamic Window Approach (DWA) algorithm (IA-DWA) to quickly search for globally optimal collision-free paths and avoid unknown obstacles in time. First, the data from the odometer and the inertial measurement unit (IMU) are fused using the extended Kalman filter (EKF) to reduce the error caused by wheel slippage on the mobile robot’s positioning and improve the mobile robot’s positioning accuracy. Second, the prediction function, weight coefficients, search neighborhood, and path smoothing processing of the A* algorithm are optimally designed to incorporate the critical point information in the global path into the DWA calculation framework. Then, the length of time and convergence speed of path planning are compared and simulated in raster maps of different complexity. In terms of path planning time, the algorithm reduces by 23.3% compared to A*-DWA; in terms of path length, the algorithm reduces by 1.8% compared to A*-DWA, and the optimization iterations converge faster. Finally, the reliability of the improved algorithm is verified by conducting autonomous navigation experiments using a ROS (Robot Operating System) mobile robot as an experimental platform.https://doi.org/10.1038/s41598-024-84858-3Mobile robotsAutonomous navigation systemA* algorithmDWA algorithmROS |
| spellingShingle | Quanling He Zongyan Wang Kun Li Yuting Zhang Menglong Li Research on autonomous navigation of mobile robots based on IA-DWA algorithm Scientific Reports Mobile robots Autonomous navigation system A* algorithm DWA algorithm ROS |
| title | Research on autonomous navigation of mobile robots based on IA-DWA algorithm |
| title_full | Research on autonomous navigation of mobile robots based on IA-DWA algorithm |
| title_fullStr | Research on autonomous navigation of mobile robots based on IA-DWA algorithm |
| title_full_unstemmed | Research on autonomous navigation of mobile robots based on IA-DWA algorithm |
| title_short | Research on autonomous navigation of mobile robots based on IA-DWA algorithm |
| title_sort | research on autonomous navigation of mobile robots based on ia dwa algorithm |
| topic | Mobile robots Autonomous navigation system A* algorithm DWA algorithm ROS |
| url | https://doi.org/10.1038/s41598-024-84858-3 |
| work_keys_str_mv | AT quanlinghe researchonautonomousnavigationofmobilerobotsbasedoniadwaalgorithm AT zongyanwang researchonautonomousnavigationofmobilerobotsbasedoniadwaalgorithm AT kunli researchonautonomousnavigationofmobilerobotsbasedoniadwaalgorithm AT yutingzhang researchonautonomousnavigationofmobilerobotsbasedoniadwaalgorithm AT menglongli researchonautonomousnavigationofmobilerobotsbasedoniadwaalgorithm |