Extracting common sense knowledge from text for robot planning

Abstract — Autonomous robots often require domain knowl-edge to act intelligently in their environment. This is particu-larly true for robots that use automated planning techniques, which require symbolic representations of the operating en-vironment and the robot’s capabilities. However, the task of specifying domain knowledge by hand is tedious and prone to error. As a result, we aim to automate the process of acquiring general common sense knowledge of objects, relations, and actions, by extracting such information from large amounts of natural language text, written by humans for human readers. We present two methods for knowledge acquisition, requiring only limited human input, which focus on the inference of spatial relations from text. Although our approach is applicable to a range of domains and information, we only consider one type of knowledge here, namely object locations in a kitche

Developing and Analyzing Intuitive Modes for Interactive Object Modeling

In this paper we present two approaches for intuitive interactive modelling of special object attributes by use of specific sensoric hardware. After a brief overview over the state of the art in interactive, intuitive object modeling, we motivate the modeling task by deriving the different object attributes that shall be modeled from an analysis of important interactions with objects. As an example domain, we chose the setting of a service robot in a kitchen. Tasks from this domain were used to derive important basic actions from which in turn the necessary object attributes were inferred. In the main section of the paper, two of the derived attributes are presented, each with an intuitive interactive modeling method. The object attributes to be modeled are stable object positions and movement restrictions for objects. Both of the intuitive interaction methods were evaluated with a group of test persons and the results are discussed. The paper ends with conclusions on the discussed results and a preview of future work in this area, in particular of potential applications

Entwicklung einer intuitiven Mensch-Maschine-Schnittstelle für die automatisierte Kleinserienmontage

Sinkende Losgrößen in der industriellen Montage erfordern neue Konzepte, um flexible Robotersysteme schnell, einfach und robust für neue Aufgaben einzurichten. Der Beitrag dieser Arbeit liegt in der Entwicklung einer Mensch-Maschine-Schnittstelle, mit der Nicht-Experten diese Systeme innerhalb weniger Stunden für komplexe, bildgeführte Applikationen in Betrieb nehmen. Die Robustheit wird durch eine autonome Störungsbehandlung mit selbstständiger Optimierung über einen POMDP erreicht