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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    Title :

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


    Additional title:

    Lect. Notes in Networks, Syst.



    Conference:

    Iberian Robotics conference ; 2023 ; Coimbra, Portugal November 22, 2023 - November 24, 2023



    Publication date :

    2024-04-27


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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