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 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.