Human-Robot Collaborative Scene Mapping from Relational Descriptions

Abstract. In this article we propose a method for cooperatively building a scene map between a human and a robot by using a spatial relational model employed by the robot to interpret human descriptions of the scene. The description will consist in a set of spatial relations between the objects in the scene. The scene map will contain the position of these objects. For this end we propose a model based on the generation of scalar elds of applicability for each of the available relations. The method can be summarized as follows. In rst place a person will come into the room and describe the scene to the robot, including in the description semantic information about the objects which the robot can't get from its sensors. From the description the robot will form the scene mental map. In second place the robot will sense the scene with a 2D range laser building the scene sensed map. The objects positions in the mental map will be used to guide the sensing process. In a third step the robot will fuse the two maps, linking the semantic information about the described objects to the corresponding sensed ones. The resulting map is called the scene enriched map.

Das System SOCCER: Simultane Interpretation und natuerlichsprachliche Beschreibung zeitveraenderlicher Szenen

Available from TIB Hannover: RO 4626(64) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

A REPLAI of SOCCER Recognizing intensions in the domain of soccer games

SIGLETIB Hannover: RO 4626(36) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Various views on spatial prepositions

SIGLETIB Hannover: RO 4626(33) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Recognizing intentions, interactions, and causes of plan failures

SIGLEAvailable from TIB Hannover: RO 4626(77) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Real-Time Spatio-Temporal Analysis of Dynamic Scenes in 3D Soccer Simulation

We propose a framework for spatio-temporal real-time analysis of dynamic scenes. It is designed to improve the grounding situation of autonomous agents in (simulated) physical domains. We introduce a knowledge processing pipeline ranging from relevance-driven compilation of a qualitative scene description to a knowledge-based detection of complex event and action sequences, conceived as a spatio-temporal pattern matching problem. A methodology for the formalization of motion patterns and their inner composition is introduced and applied to capture human expertise about domain-specific motion situations. We present extensive experimental results from the 3D soccer simulation that substantiate the online applicability of our approach under tournament conditions, based on 5 Hz a) precise and b) noisy/incomplete perception