Fabrice Le Bars – författare

Localization for underwater robots remains a challenging issue. Typical sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply Simultaneous Localization and Mapping (SLAM) methods to perform localization. Reliable Robot Localization presents an innovative new method which can be characterized as a raw-data SLAM approach. It differs from extant methods by considering time as a standard variable to be estimated, thus raising new opportunities for state estimation, so far underexploited. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization. This book not only presents original contributions to the field of mobile robotics, it also offers new perspectives on constraint programming and set-membership approaches. It provides a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated throughout this book with realistic robotic applications.

Localization for underwater robots remains a challenging issue. Typical sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply Simultaneous Localization and Mapping (SLAM) methods to perform localization. Reliable Robot Localization presents an innovative new method which can be characterized as a raw-data SLAM approach. It differs from extant methods by considering time as a standard variable to be estimated, thus raising new opportunities for state estimation, so far underexploited. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization. This book not only presents original contributions to the field of mobile robotics, it also offers new perspectives on constraint programming and set-membership approaches. It provides a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated throughout this book with realistic robotic applications.

Localization for underwater robots remains a challenging issue. Typical sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply Simultaneous Localization and Mapping (SLAM) methods to perform localization. Reliable Robot Localization presents an innovative new method which can be characterized as a raw-data SLAM approach. It differs from extant methods by considering time as a standard variable to be estimated, thus raising new opportunities for state estimation, so far underexploited. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization. This book not only presents original contributions to the field of mobile robotics, it also offers new perspectives on constraint programming and set-membership approaches. It provides a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated throughout this book with realistic robotic applications.

An autonomous sailboat robot is a boat that only uses the wind on its sail as propelling force, without remote control or human assistance to achieve its mission. This involves autonomy in energy (using batteries, solar panels, turbines...), sensor data processing (compass, GPS, wind sensor...), actuators control (rudder and sail angle control...) and decision making (embedded computer with adequate algorithms). Although robotic sailing is a relatively new field of research, several applications exist for this type of robots: oceanographic and hydrographic research, maritime environment monitoring, meteorology, harbor safety, assistance and rescue in dangerous areas...Over the last decade, several events such as the Microtransat challenge, the WRSC/IRSC and SailBot have been set up to stimulate research and development around robotic sailing. These proceedings cover the current and future academic and technology challenges raised by the development of autonomous sailboat robots presented at the WRSC/IRSC (World Robotic Sailing Championship/International Robotic Sailing Conference) 2013, in Brest, France, 2-6 September 2013.

An autonomous sailboat robot is a boat that only uses the wind on its sail as propelling force, without remote control or human assistance to achieve its mission. This involves autonomy in energy (using batteries, solar panels, turbines...), sensor data processing (compass, GPS, wind sensor...), actuators control (rudder and sail angle control...) and decision making (embedded computer with adequate algorithms). Although robotic sailing is a relatively new field of research, several applications exist for this type of robots: oceanographic and hydrographic research, maritime environment monitoring, meteorology, harbor safety, assistance and rescue in dangerous areas...Over the last decade, several events such as the Microtransat challenge, the WRSC/IRSC and SailBot have been set up to stimulate research and development around robotic sailing. These proceedings cover the current and future academic and technology challenges raised by the development of autonomous sailboat robots presented at the WRSC/IRSC (World Robotic Sailing Championship/International Robotic Sailing Conference) 2013, in Brest, France, 2-6 September 2013.