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The Simultaneous Localization And Mapping (SLAM) challenge entails reconstructing an unknown environment while also determining the location of a moving object. This problem is more general and difficult than the individual mapping or localization difficulties that can be considered as particular cases of SLAM.Many applications necessitate the reconstruction of a consistent map; in general, many applications may require a robot to explore an unknown environment and report its findings to a human operator. For example, in outdoor autonomous navigation of robots, SLAM is not required if the…mehr

Produktbeschreibung
The Simultaneous Localization And Mapping (SLAM) challenge entails reconstructing an unknown environment while also determining the location of a moving object. This problem is more general and difficult than the individual mapping or localization difficulties that can be considered as particular cases of SLAM.Many applications necessitate the reconstruction of a consistent map; in general, many applications may require a robot to explore an unknown environment and report its findings to a human operator. For example, in outdoor autonomous navigation of robots, SLAM is not required if the robot has access to GPS; conversely, in indoor environments, the use of GPS for localization scope is ruled out.
Autorenporträt
My name is Sai Krishna Vidiyala, MSc Graduate from Alma Mater Studiorum - Universita di Bologna with a Master's degree in Telecommunications Engineering.