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The Use of Semantic Knowledge in Task Planning for Robotic Agents, Minimising Human Error

  • Conference paper
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Robot 2023: Sixth Iberian Robotics Conference (ROBOT 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 976))

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Abstract

As technology advances, robotic agents are being applied to more areas. Consequently, their environments are becoming more complex, moving away from the standard - mainly static - work cells, where operators and machines follow strictly defined boundaries and schedules. The non-deterministic workflow of these workspaces raises concerns about planning tasks and actions between resources. The traditional approach to human-robot interfaces is based on explicit programming and pre-defined commands. However, with AI and natural language processing advances, incorporating semantic knowledge into the interfaces may enable more natural, intuitive and context-aware interactions between humans and robots. Semantic knowledge and ontologies enable the interface to understand the context of the task planning process. This understanding allows robotic agents to consider the overall situation, the environment and any relevant previous tasks or actions, resulting in more context-appropriate task execution. Following these requirements, this paper presents a graphical user interface which uses semantic knowledge to assist an operator human in task planning for robotic agents, minimising human error.

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Notes

  1. 1.

    http://wiki.ros.org/mongodb_store.

  2. 2.

    https://www.universal-robots.com/pt/produtos/ur3-robot/.

  3. 3.

    https://robotiq.com/products/2f85-140-adaptive-robot-gripper.

  4. 4.

    https://github.com/AI-Planning/pddl.

  5. 5.

    http://wiki.ros.org/mongodb_store.

  6. 6.

    https://fai.cs.uni-saarland.de/hoffmann/ff.html.

  7. 7.

    https://www.qt.io.

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Acknowledgments

This work is financed by national funds through FCT - Foundation for Science and Technology, I.P., through IDMEC, under LAETA, project UIDB/50022/2020. The work of Rodrigo Bernardo was supported by the PhD Scholarship BD/6841/2020 from FCT. This work has indirectly received funding from the European Union’s Horizon 2020 programme under StandICT.eu 2026 (under Grant Agreement No.: 101091933).

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Authors and Affiliations

  1. IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

    Rodrigo Bernardo & João M. C. Sousa

  2. IDMEC, Instituto Politécnico de Castelo Branco, Castelo Branco, Portugal

    Rodrigo Bernardo & Paulo J. S. Gonçalves

Authors
  1. Rodrigo Bernardo
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  2. João M. C. Sousa
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  3. Paulo J. S. Gonçalves
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Corresponding author

Correspondence to Rodrigo Bernardo .

Editor information

Editors and Affiliations

  1. Dep. de Eng. Electrotecnica e de Computadores, University of Coimbra, Coimbra, Portugal

    Lino Marques

  2. Department of Electrónica Industrial, University of Minho, Escola de Engenharia, Guimarães, Portugal

    Cristina Santos

  3. Department of Electrical Engineering, Polytechnic Institute of Bragança, Bragança, Portugal

    José Luís Lima

  4. Centro Universitario de la Defensa, Zaragoza, Spain

    Danilo Tardioli

  5. Centre for Automation and Robotics UPM-CSIC, Universidad Politecnica de Madrid, Madrid, Spain

    Manuel Ferre

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Bernardo, R., Sousa, J.M.C., Gonçalves, P.J.S. (2024). The Use of Semantic Knowledge in Task Planning for Robotic Agents, Minimising Human Error. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-031-58676-7_1

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