For an effective deployment in manufacturing, Collaborative Robots should be capable of adapting their behavior to the state of the environment and to keep the user safe and engaged during the interaction. Artificial Intelligence (AI) enables robots to autonomously operate understanding the environment, planning their tasks and acting to achieve some given goals. However, the effective deployment of AI technologies in real industrial environments is not straightforward. There is a need for engineering tools facilitating communication and interaction between AI engineers and Domain experts. This paper proposes a novel software tool, called TENANT (Tool fostEriNg Ai plaNning in roboTics) whose aim is to facilitate the use of AI planning technologies by providing domain experts like e.g., production engineers, with a graphical software framework to synthesize AI planning models abstracting from syntactic features of the underlying planning formalism.

Simplifying the A.I. Planning modeling for Human-Robot Collaboration

Elisa Foderaro;Amedeo Cesta;Alessandro Umbrico;Andrea Orlandini
2021

Abstract

For an effective deployment in manufacturing, Collaborative Robots should be capable of adapting their behavior to the state of the environment and to keep the user safe and engaged during the interaction. Artificial Intelligence (AI) enables robots to autonomously operate understanding the environment, planning their tasks and acting to achieve some given goals. However, the effective deployment of AI technologies in real industrial environments is not straightforward. There is a need for engineering tools facilitating communication and interaction between AI engineers and Domain experts. This paper proposes a novel software tool, called TENANT (Tool fostEriNg Ai plaNning in roboTics) whose aim is to facilitate the use of AI planning technologies by providing domain experts like e.g., production engineers, with a graphical software framework to synthesize AI planning models abstracting from syntactic features of the underlying planning formalism.
2021
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Inglese
30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)
1011
1016
6
978-1-6654-0492-1
https://ieeexplore.ieee.org/document/9515431/
IEEE
New York
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
8/8/2021-12/8/2021
Vancouver, Canada (Virtual Conference)
Robot control Human-Robot Collaboration
Tools
Syntactics
Planning
Artificial intelligence
4
none
Elisa Foderaro; Amedeo Cesta; Alessandro Umbrico; Andrea Orlandini;
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
   Safe and effective HumAn-Robot coopEration toWards a better cOmpetiveness on cuRrent automation lacK manufacturing processes.
   SHAREWORK
   H2020
   820807
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/397366
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