Exploración dinámica de fronteras en entornos desconocidos basada en la entropía
[EN] Exploration in disaster areas provides valuable, high-fidelity information to rescue personnel in disaster situations, with the potential to reduce the time for search and recovery of victims. This paper presents an exploration strategy based on entropy to evaluate the frontiers of the known pa...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | español |
| OAI Identifier: | oai:riunet.upv.es:10251/192803 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/192803 |
| Access Level: | acceso abierto |
| Palabra clave: | Mobile robotics Autonomous mobile robotics Robot navigation Entropy Information theory Robótica móvil Robótica móvil autónoma Navegación de robots Entropía Teoría de la información |
| Sumario: | [EN] Exploration in disaster areas provides valuable, high-fidelity information to rescue personnel in disaster situations, with the potential to reduce the time for search and recovery of victims. This paper presents an exploration strategy based on entropy to evaluate the frontiers of the known part of the map using an expectation function. The proposed method employs this metric for exploration planning based on the expectation of future information gain, ensuring a strategy that minimises exploration time while maximising the inclusion of new information into the map. This approach avoids the dependency of the information gain method on fixed-size maps and proposes a sensor-independent model that considers the distribution of obstacles in the frontiers' surroundings. In the evaluation, results are presented in different environments with simulations that demonstrate the efficiency in the exploration planning of the unknown areas, until the complete knowledge of the environment to be explored is completed. The proposed method is publicly available at Godoy-Calvo et al. (2022). |
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