Use este identificador para citar o ir al link de este elemento:
http://hdl.handle.net/1843/JCES-AS7PBJ
Tipo: | Tese de Doutorado |
Título: | Detecting and predicting environmental boundaries with a team of robots |
Autor(es): | David Julian Saldana Santacruz |
primer Tutor: | Mario Fernando Montenegro Campos |
primer Co-tutor: | Renato Martins Assuncao |
primer miembro del tribunal : | Luiz Chaimowicz |
Segundo miembro del tribunal: | Luciano Cunha de Araujo Pimenta |
Tercer miembro del tribunal: | Ani Hsieh |
Cuarto miembro del tribunal: | Rafael Fierro |
Resumen: | Large area disasters are usually triggered by small-scale anomalies in small areas which could possibly be detected in their early stages. The past decade has seen effective proposals to approach this problem with the deployment of mobile sensors for monitoring disaster prone areas. In this work, we study three important tasks to achieve an autonomous system that can monitor the environment and prevent catastrophes. The first task concerns the disaster detection. The challenge is to coordinate multiple robots to explore the environment in order to find anomalies. The second task concerns the subsequent disaster tracking. Once the anomaly is detected, the robots must coordinate themselves to track the behavior of the environmental boundary. In the third task, the resulting tracking information from the second task is used to estimate the current and to predict its future shape. The combination of these three tasks integrates a monitoring system that can alert and mitigate the risk suffered by human and animal beings. In this dissertation, we present some contributions for each one of these tasks and for their integration. We validate our proposed methods by simulations and with actual robots. Our experiments showed good performance results |
Abstract: | Large area disasters are usually triggered by small-scale anomalies in small areas which could possibly be detected in their early stages. The past decade has seen effective proposals to approach this problem with the deployment of mobile sensors for monitoring disaster prone areas. In this work, we study three important tasks to achieve an autonomous system that can monitor the environment and prevent catastrophes. The first task concerns the disaster detection. The challenge is to coordinate multiple robots to explore the environment in order to find anomalies. The second task concerns the subsequent disaster tracking. Once the anomaly is detected, the robots must coordinate themselves to track the behavior of the environmental boundary. In the third task, the resulting tracking information from the second task is used to estimate the current and to predict its future shape. The combination of these three tasks integrates a monitoring system that can alert and mitigate the risk suffered by human and animal beings. In this dissertation, we present some contributions for each one of these tasks and for their integration. We validate our proposed methods by simulations and with actual robots. Our experiments showed good performance results. |
Asunto: | Robótica Computação Sistemas multi-robôs Monitoramento ambiental |
Idioma: | Inglês |
Editor: | Universidade Federal de Minas Gerais |
Sigla da Institución: | UFMG |
Tipo de acceso: | Acesso Aberto |
URI: | http://hdl.handle.net/1843/JCES-AS7PBJ |
Fecha del documento: | 14-jul-2017 |
Aparece en las colecciones: | Teses de Doutorado |
archivos asociados a este elemento:
archivo | Descripción | Tamaño | Formato | |
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davidjuliansaldanha.pdf | 11.2 MB | Adobe PDF | Visualizar/Abrir |
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