Towards a No Code Deployment of Social Robotics Use Cases

ABSTRACT Social Autonomous Robotics aims to deploy robots in scenarios that involve intensive and continuous interaction with humans. To control the behaviour of robotic platforms in such environments, the use of automated planning (AP) within a control architecture has been proposed as an effective...

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Published inExpert systems Vol. 42; no. 6
Main Authors Gragera, Alba, Díaz‐de‐Mera, Carmen, Bandera, Juan Pedro, García‐Olaya, Ángel, Fernández, Fernando
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Publishing Ltd 01.06.2025
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Abstract ABSTRACT Social Autonomous Robotics aims to deploy robots in scenarios that involve intensive and continuous interaction with humans. To control the behaviour of robotic platforms in such environments, the use of automated planning (AP) within a control architecture has been proposed as an effective mechanism. However, the design of AP models is time‐consuming and typically carried out by domain experts and engineers. A significant amount of knowledge must be acquired in order to properly define the use case description by specifying the different tasks performed by the robot. In this paper, we present DeVPlan, a framework for graphically designing robotic use cases and configuring the platform for the desired execution. DeVPlan provides an interface that allows domain experts, in collaboration with knowledge engineers, to use state transition diagrams to specify the tasks a robot can perform and define recovery strategies for exogenous events that disrupt normal execution. This graphical design is automatically translated into the standard Planning Domain Definition Language (PDDL). Additionally, to facilitate the integration of the AP model with the robot's control architecture, DeVPlan includes a module for generating the configuration files required to set up the control system. The proposed framework has been successfully used to design and deploy two different use cases in a real environment in a retirement home.
AbstractList ABSTRACT Social Autonomous Robotics aims to deploy robots in scenarios that involve intensive and continuous interaction with humans. To control the behaviour of robotic platforms in such environments, the use of automated planning (AP) within a control architecture has been proposed as an effective mechanism. However, the design of AP models is time‐consuming and typically carried out by domain experts and engineers. A significant amount of knowledge must be acquired in order to properly define the use case description by specifying the different tasks performed by the robot. In this paper, we present DeVPlan, a framework for graphically designing robotic use cases and configuring the platform for the desired execution. DeVPlan provides an interface that allows domain experts, in collaboration with knowledge engineers, to use state transition diagrams to specify the tasks a robot can perform and define recovery strategies for exogenous events that disrupt normal execution. This graphical design is automatically translated into the standard Planning Domain Definition Language (PDDL). Additionally, to facilitate the integration of the AP model with the robot's control architecture, DeVPlan includes a module for generating the configuration files required to set up the control system. The proposed framework has been successfully used to design and deploy two different use cases in a real environment in a retirement home.
Social Autonomous Robotics aims to deploy robots in scenarios that involve intensive and continuous interaction with humans. To control the behaviour of robotic platforms in such environments, the use of automated planning (AP) within a control architecture has been proposed as an effective mechanism. However, the design of AP models is time‐consuming and typically carried out by domain experts and engineers. A significant amount of knowledge must be acquired in order to properly define the use case description by specifying the different tasks performed by the robot. In this paper, we present DeVPlan , a framework for graphically designing robotic use cases and configuring the platform for the desired execution. DeVPlan provides an interface that allows domain experts, in collaboration with knowledge engineers, to use state transition diagrams to specify the tasks a robot can perform and define recovery strategies for exogenous events that disrupt normal execution. This graphical design is automatically translated into the standard Planning Domain Definition Language (PDDL). Additionally, to facilitate the integration of the AP model with the robot's control architecture, DeVPlan includes a module for generating the configuration files required to set up the control system. The proposed framework has been successfully used to design and deploy two different use cases in a real environment in a retirement home.
Author Bandera, Juan Pedro
Gragera, Alba
Díaz‐de‐Mera, Carmen
García‐Olaya, Ángel
Fernández, Fernando
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Snippet ABSTRACT Social Autonomous Robotics aims to deploy robots in scenarios that involve intensive and continuous interaction with humans. To control the behaviour...
Social Autonomous Robotics aims to deploy robots in scenarios that involve intensive and continuous interaction with humans. To control the behaviour of...
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wiley
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SubjectTerms automated planning
Engineers
Knowledge management
Robot control
Robotics
Robots
social autonomous robotics
Subject specialists
use case modeling
Title Towards a No Code Deployment of Social Robotics Use Cases
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fexsy.70038
https://www.proquest.com/docview/3229086025
Volume 42
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