An Automated Planning Model for HRI: Use Cases on Social Assistive Robotics.

Sensors (Basel)

Computer Science Department, Universidad Carlos III de Madrid, 28911 Leganés, Spain.

Published: November 2020

AI Article Synopsis

  • Using automated planning for robotic control is gaining popularity, especially for defining tasks declaratively, but it can be challenging for non-experts to create complex models, particularly in Human Robot Interaction (HRI).
  • The manuscript details the design of a planning model tailored for social autonomous robots engaged in HRI, derived from the authors' experiences with Social Assistive Robotics (SAR) in healthcare.
  • The proposed model integrates two specific healthcare use cases into a unified planning domain, enabling effective management and integration with robotic software, and demonstrates the robot's ability to autonomously execute tasks within defined scenarios.

Article Abstract

Using Automated Planning for the high level control of robotic architectures is becoming very popular thanks mainly to its capability to define the tasks to perform in a declarative way. However, classical planning tasks, even in its basic standard Planning Domain Definition Language (PDDL) format, are still very hard to formalize for non expert engineers when the use case to model is complex. Human Robot Interaction (HRI) is one of those complex environments. This manuscript describes the rationale followed to design a planning model able to control social autonomous robots interacting with humans. It is the result of the authors' experience in modeling use cases for Social Assistive Robotics (SAR) in two areas related to healthcare: Comprehensive Geriatric Assessment (CGA) and non-contact rehabilitation therapies for patients with physical impairments. In this work a general definition of these two use cases in a unique planning domain is proposed, which favors the management and integration with the software robotic architecture, as well as the addition of new use cases. Results show that the model is able to capture all the relevant aspects of the Human-Robot interaction in those scenarios, allowing the robot to autonomously perform the tasks by using a standard planning-execution architecture.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7697113PMC
http://dx.doi.org/10.3390/s20226520DOI Listing

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