KnowRob: A knowledge processing infrastructure for cognition-enabled robots

By Moritz Tenorth, Michael Beetz. Int. J. Robotics Res., 2013

450 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/97ff478959931fddf8eab9c924dc6a849ddb3270

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In Artificial Intelligence

Citations in the corpus

Image Object Label 3 D CAD Model Candidate Grasps Google Object Recognition Engine Google Cloud Storage Select Feasible Grasp with Highest Success Probability Pose EstimationCamera Robots Cloud 3 D Sensor (2014, background): “While sensor data such as images and point clouds have a small number of widely-used formats, even relatively simple data such as trajectories have no common standards yet but research is ongoing [129], [147], [149].”
Automated Planning and Acting (2016, background): “The RoboEarth and KnowRob projects [592, 569] aim at allowing actors having different platforms to share and reuse knowledge over the network for the purpose of performing new tasks.”
On-line simultaneous learning and recognition of everyday activities from virtual reality performances (2017, unknown): “This system produces a set of observed activities and the ontology classes of the objects used in each (using the default KnowROB[4] ontology), as well as a graph of the task space explored by the participants.”
A Survey of Research on Cloud Robotics and Automation (2015, background): “New approaches are required that are robust to dirty data.”
A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving (2017, background): “With the ability to deﬁne hierarchical classes and relationships between these classes, ontologies have been used to represent the contextual entities and expert knowledge unambiguously in knowledge-intensive systems [21,22].”
Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora (2017, background): “Such knowledge is often represented in the form of ontologies and knowledge graphs [2, 3, 4], but although these structures are easily integrated with robotic reasoning systems, they fail to represent the full complexity of human thought.”
Deliberation for autonomous robots: A survey (2017, methodology): “, the RoboEarth, [218], KnowRob [208] and CRAM [18] systems, which rely on OWL, the standard Web Ontology Language.”
Statistical Relational Artificial Intelligence: Logic, Probability, and Computation (2016, methodology): “Generally, statistical relational methods are essential for enabling autonomous robots to do the right thing to the right object in the right way [Tenorth and Beetz, 2013].”