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• W2291794640 abstract "Abstract-The sensory acquisition of the environment is themost important task of mobile robotics, as it is the foundationfor any ability that the robot shall have, later on. Sophisticatedtasks often require an environment model for path planning,obstacle avoidance and many more. Furthermore, the robotneeds to know where it is located within the environment tobuild-up, complement and update the model. Thus, besidesenvironment perception, localization belongs to the most importanttasks of mobile robot systems. Most approaches towardsself-localization and mapping are very specific, either to onesensor type, or a strictly predefined set of sensors, prohibitingthe use of the provided techniques on many different mobilesystems (robots, cars or other moving platforms equipped withsensors). We present a general approach supporting the use ofarbitrary numbers and types of sensors simultaneously. Thisallows to operate with a large variety of already existing systemswithout changing the hardware setup. Furthermore, thesemantic environment model, generated by our solution, candirectly be used for sophisticated and automated environmentanalyses." @default.
• W2291794640 created "2016-06-24" @default.
• W2291794640 creator A5002991197 @default.
• W2291794640 creator A5038197268 @default.
• W2291794640 date "2015-12-01" @default.
• W2291794640 modified "2023-09-24" @default.
• W2291794640 title "Semantic Environment Perception, Localization and Mapping" @default.
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• W2291794640 doi "https://doi.org/10.1109/aims.2015.84" @default.
• W2291794640 hasPublicationYear "2015" @default.
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