ROAMFREE - Robust Odometry Applying Multisensor Fusion to Reduce Estimation Errors
Responsabile:
Ricerca
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Data inizio: 01/10/2011
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Sommario
Applications such as automatic transportation of goods or people, agriculture, patrolling or civil protection, very often require the ability, for a mobile robot, of moving through the environment keeping an accurate estimate of its position through a robust odometry system. In the robotics field, several solutions are proposed for the odometry problem. Each solution fits a given scenario, but proves to be inaccurate or even unusable in other scenarios.
The ROAMFREE project aims at a general solution to the problem of multisensor robust odometry for autonomous robots and vehicles. The approach leverages on the modular use of logical sensors (i.e., odometric systems composed by one or more physical sensors, and the software processing their output) to provide a robust, readily available, tool for odometry.
The ROAMFREE project aims at a general solution to the problem of multisensor robust odometry for autonomous robots and vehicles. The approach leverages on the modular use of logical sensors (i.e., odometric systems composed by one or more physical sensors, and the software processing their output) to provide a robust, readily available, tool for odometry.
Risultati del progetto ed eventuali pubblicazioni scientifiche/brevetti
Pubblicazioni:
- D. A. Cucci, M. Matteucci: “A Flexible Framework for Mobile Robot Pose Estimation and Multi-Sensor Self-Calibration”. In: In: Informatics in Control, Automation and Robotics (ICINCO), 2013 International Conference on., Reykjavík, Iceland, 2013.
- D. A. Cucci, M. Matteucci: “Position tracking and sensors self-calibration in autonomous mobile robots by gauss-newton optimization”. In: Robotics and Automation (ICRA), 2014 IEEE International Conference on. Hong Kong, China, 2014.
- D. A. Cucci, M. Matteucci: "On the Development of a Generic Multi-Sensor Fusion Framework for Robust Odometry Estimation". Journal of Software Engineering for Robotics (JOSER), 2014.