Robust UAV Path Planning with Obstacle Avoidance for Emergency Rescue
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915105501872128 |
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| author | Mao, Junteng Jia, Ziye Gu, Hanzhi Shi, Chenyu Shi, Haomin He, Lijun Wu, Qihui |
| author_facet | Mao, Junteng Jia, Ziye Gu, Hanzhi Shi, Chenyu Shi, Haomin He, Lijun Wu, Qihui |
| contents | The unmanned aerial vehicles (UAVs) are efficient tools for diverse tasks such as electronic reconnaissance, agricultural operations and disaster relief. In the complex three-dimensional (3D) environments, the path planning with obstacle avoidance for UAVs is a significant issue for security assurance. In this paper, we construct a comprehensive 3D scenario with obstacles and no-fly zones for dynamic UAV trajectory. Moreover, a novel artificial potential field algorithm coupled with simulated annealing (APF-SA) is proposed to tackle the robust path planning problem. APF-SA modifies the attractive and repulsive potential functions and leverages simulated annealing to escape local minimum and converge to globally optimal solutions. Simulation results demonstrate that the effectiveness of APF-SA, enabling efficient autonomous path planning for UAVs with obstacle avoidance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_09338 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust UAV Path Planning with Obstacle Avoidance for Emergency Rescue Mao, Junteng Jia, Ziye Gu, Hanzhi Shi, Chenyu Shi, Haomin He, Lijun Wu, Qihui Robotics Systems and Control The unmanned aerial vehicles (UAVs) are efficient tools for diverse tasks such as electronic reconnaissance, agricultural operations and disaster relief. In the complex three-dimensional (3D) environments, the path planning with obstacle avoidance for UAVs is a significant issue for security assurance. In this paper, we construct a comprehensive 3D scenario with obstacles and no-fly zones for dynamic UAV trajectory. Moreover, a novel artificial potential field algorithm coupled with simulated annealing (APF-SA) is proposed to tackle the robust path planning problem. APF-SA modifies the attractive and repulsive potential functions and leverages simulated annealing to escape local minimum and converge to globally optimal solutions. Simulation results demonstrate that the effectiveness of APF-SA, enabling efficient autonomous path planning for UAVs with obstacle avoidance. |
| title | Robust UAV Path Planning with Obstacle Avoidance for Emergency Rescue |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2501.09338 |