Detalhes bibliográficos
| Resumo: | The ability to locate a robot is one of the main features to be truly autonomous. Different methodologies can be used to determine robots location as accurately as possible, however these methodologies present several problems in some circumstances. One of these problems is the existence of uncertainty in the sensing of the robot. To solve this problem, it is necessary to combine the uncertain information correctly. In this way, it is possible to have a system that allows a more robust localization of the robot, more tolerant to failures and disturbances. This paper evaluates an Extended Kalman Filter (EKF) that fuses odometry information with Ultra-WideBand Time-of-Flight (UWB ToF) measurements and camera measurements from the detection of ArUco markers in the environment. The proposed system is validated in a real environment with a differential robot developed for this purpose, and the achieved results are promising. |
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| Autores principais: | Faria, Sílvia |
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| Outros Autores: | Lima, José; Costa, Paulo Gomes da |
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| Assunto: | ArUco markers Autonomous mobile robot Extended kalman filter Localization Ultra-wideband Vision based system |
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| Ano: | 2021 |
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| País: | Portugal |
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| Tipo de documento: | comunicação em conferência |
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| Tipo de acesso: | acesso restrito |
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| Instituição associada: | Instituto Politécnico de Bragança |
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| Idioma: | inglês |
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| Origem: | Biblioteca Digital do IPB |
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