A Knowledge-Based Approach to Robotic Perception using Unstructured Information Management

In order to achieve a human-like skill level in manipulation, autonomous robots that perform everyday manipulation tasks require perception capabilities that go beyond recognition delivered by single perception algorithms. In previous work we have presented ROBOSHERLOCK, an ensemble-based, knowledge driven robotic perception system and OPENEASE an online framework for knowledge representation and reasoning. We propose to demonstrate, by combining these two frameworks, how knowledge processing can boosts the perception capabilities of a robotic agent performing household chores. Categories and Subject Descriptors I.2.10 [Artificial Intelligence]: Vision and Scene Understanding— 3D/stereo scene analysis, Perceptual reasoning, Architecture and control structures Keywords robot perception, knowledge based reasoning, personal robotics

• Type: Journal
• Year: 2015
• Where: ATAL
• Authors: Ferenc Balint-Benczedi, Thiemo Wiedemeyer, Moritz Tenorth, Daniel Beßler, Michael Beetz
• Keywords: ATAL 2015, Intelligent Agents