Challenges in Using Semantic Knowledge for 3D Object Classification
Corina Gurău, Andreas Nüchter · 2013
To cope with a wide variety of tasks, robotic systems need to perceive and understand their environments. In particular, they need a representation of individual objects, as well as contextual relations between them. Visual information is the primary data source used to make predictions and inferences about the world. There exists, however, a growing tendency to introduce high-level semantic knowledge to enable robots to reason about objects. We use the Semantic Web framework to represent knowledge and make inferences about sensor data, in order to detect and classify objects in the environment. The contribution of this work is the identification of several challenges that co-occur when combining sensor data processing with such a reasoning method.