Overworld: Assessing the Geometry of the World for Human-Robot Interaction

For a robot to interact with humans in a given environment, a key need is to understand its environment in terms of the objects composing it, the other agents acting in it, and the relations between all of them. This capability is often called the geometrical situation assessment and is mainly relat...

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Vydáno v:IEEE robotics and automation letters Ročník 8; číslo 3; s. 1874 - 1880
Hlavní autor: Sarthou, Guillaume
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.03.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Cognition
Cognition & reasoning
Computer architecture
Computer Science
Human engineering
human-robot collaboration
Human-robot interaction
Knowledge based systems
Multi-modal perception for HRI
Reasoning
Robot kinematics
Robot sensing systems
Robots
Sensors
software architecture for robotic and automation
Human-Robot Collaboration
Multi-Modal Perception for HRI
Software Architecture for Robotic and Automation
ISSN:2377-3766, 2377-3766
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Shrnutí:For a robot to interact with humans in a given environment, a key need is to understand its environment in terms of the objects composing it, the other agents acting in it, and the relations between all of them. This capability is often called the geometrical situation assessment and is mainly related to spatial reasoning in time. In this letter, we present Overworld, a novel lightweight and open-source framework, merging the key features of a decade of research in the domain. It permanently maintains a geometric state of the world from the point of view of the robot by aggregating perceptual information from several sources and reasoning on them to create a coherent world. Furthermore, Overworld implements perspective-taking by emulating the humans' ability to perceive to estimate the state of the world from their perspective. Finally, thanks to a strong link with an ontology framework, it ensures knowledge coherence in the whole robotic architecture. This work is part of a broader effort to develop a complete, stable, and shareable decisional robotic architecture for Human-Robot Interaction.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2023.3238891