A low-cost vision system for online reciprocal collision avoidance with UAVs
In this article, we propose a reciprocal collision avoidance system for autonomous drones, based on computer vision and using relative positioning in an indoor environment. This dynamic environment represents a demanding challenge, but it is crucial for any future existence of multiple drones operat...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad del País Vasco |
| Repositorio: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/67931 |
| Acceso en línea: | http://hdl.handle.net/10810/67931 |
| Access Level: | acceso abierto |
| Palabra clave: | quadrotor collision-avoidance RCA autonomous navigation |
| Sumario: | In this article, we propose a reciprocal collision avoidance system for autonomous drones, based on computer vision and using relative positioning in an indoor environment. This dynamic environment represents a demanding challenge, but it is crucial for any future existence of multiple drones operating in urban areas. We use commercial AR Drone 2.0 robots, which represent that our proposal is suitable for low-cost equipment. In our case, we attempt to achieve the collision avoidance of two drones that fly one towards the other and react online autonomously to signals received by their computer vision systems with a decentralized control strategy. We test this in four different experiments with demanding conditions. For this purpose, we get the camera signal of the onboard drones and tune their behavior to react smoothly and precisely. We report encouraging positive results and provide the code we use in the experiments for replication. |
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