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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.12618 |
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| _version_ | 1866908657052024832 |
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| author | Leyva, Jordan Vera, Nahim J. Moran Xu, Yihan Durasno, Adrien Romero, Christopher U. Chimuka, Tendai Ramirez, Gabriel O. Huezo Dong, Ziqian Rojas-Cessa, Roberto |
| author_facet | Leyva, Jordan Vera, Nahim J. Moran Xu, Yihan Durasno, Adrien Romero, Christopher U. Chimuka, Tendai Ramirez, Gabriel O. Huezo Dong, Ziqian Rojas-Cessa, Roberto |
| contents | Obstacle avoidance path planning for uncrewed aerial vehicles (UAVs), or drones, is rarely addressed in most flight path planning schemes, despite obstacles being a realistic condition. Obstacle avoidance can also be energy-intensive, making it a critical factor in efficient point-to-point drone flights. To address these gaps, we propose EcoFlight, an energy-efficient pathfinding algorithm that determines the lowest-energy route in 3D space with obstacles. The algorithm models energy consumption based on the drone propulsion system and flight dynamics. We conduct extensive evaluations, comparing EcoFlight with direct-flight and shortest-distance schemes. The simulation results across various obstacle densities show that EcoFlight consistently finds paths with lower energy consumption than comparable algorithms, particularly in high-density environments. We also demonstrate that a suitable flying speed can further enhance energy savings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_12618 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | EcoFlight: Finding Low-Energy Paths Through Obstacles for Autonomous Sensing Drones Leyva, Jordan Vera, Nahim J. Moran Xu, Yihan Durasno, Adrien Romero, Christopher U. Chimuka, Tendai Ramirez, Gabriel O. Huezo Dong, Ziqian Rojas-Cessa, Roberto Robotics Obstacle avoidance path planning for uncrewed aerial vehicles (UAVs), or drones, is rarely addressed in most flight path planning schemes, despite obstacles being a realistic condition. Obstacle avoidance can also be energy-intensive, making it a critical factor in efficient point-to-point drone flights. To address these gaps, we propose EcoFlight, an energy-efficient pathfinding algorithm that determines the lowest-energy route in 3D space with obstacles. The algorithm models energy consumption based on the drone propulsion system and flight dynamics. We conduct extensive evaluations, comparing EcoFlight with direct-flight and shortest-distance schemes. The simulation results across various obstacle densities show that EcoFlight consistently finds paths with lower energy consumption than comparable algorithms, particularly in high-density environments. We also demonstrate that a suitable flying speed can further enhance energy savings. |
| title | EcoFlight: Finding Low-Energy Paths Through Obstacles for Autonomous Sensing Drones |
| topic | Robotics |
| url | https://arxiv.org/abs/2511.12618 |