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EnviRe - Environment Representation for Long-term Autonomy

Javier Hidalgo Carrió; Sascha Arnold; Arne Böckmann; Anna Born; Raúl Domínguez; Daniel Hennes; Christoph Hertzberg; Janosch Machowinski; Jakob Schwendner; Yong-Ho Yoo; Frank Kirchner
In: AI for Long-term Autonomy Workshop on the International Conference on Robotics and Automation (ICRA). IEEE International Conference on Robotics and Automation (ICRA-16), May 16-20, Stockholm, Sweden, 2016.


Data representation is a key element for robots to navigate and perform autonomous tasks in unstructured environments. This is due to autonomous tasks which call for an environment model suitable for systems that might operate during long periods of time. This work presents EnviRe, an environment representation model that facilitates long-term tasks for autonomous systems in real-world scenarios. The EnviRe model is a strongly connected directed graph which allows sensor data acquisition, data processing, reasoning and operations among different data formats in order to accomplish the navigation and planning demands.


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