Towards Adaptive Planning of Assistive-care Robot Tasks

Jordan Hamilton
(University of York)
Ioannis Stefanakos
(University of York)
Radu Calinescu
(University of York)
Javier Cámara
(University of Málaga)

This 'research preview' paper introduces an adaptive path planning framework for robotic mission execution in assistive-care applications. The framework provides a graph-based environment modelling approach, with dynamic path finding performed using Dijkstra's algorithm. A predictive module that uses probabilistic model checking is applied to estimate the human's movement through the environment, allowing run-time re-planning of the robot's path. We illustrate the use of the framework for a simulated assistive-care case study in which a mobile robot navigates through the environment and monitors an end user with mild physical or cognitive impairments.

In Matt Luckcuck and Marie Farrell: Proceedings Fourth International Workshop on Formal Methods for Autonomous Systems (FMAS) and Fourth International Workshop on Automated and verifiable Software sYstem DEvelopment (ASYDE) (FMAS2022 ASYDE2022), Berlin, Germany, 26th and 27th of September 2022, Electronic Proceedings in Theoretical Computer Science 371, pp. 175–183.
Published: 27th September 2022.

ArXived at: https://dx.doi.org/10.4204/EPTCS.371.12 bibtex PDF
References in reconstructed bibtex, XML and HTML format (approximated).
Comments and questions to: eptcs@eptcs.org
For website issues: webmaster@eptcs.org