Towards Adaptive Planning of Assistive-care Robot Tasks
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Sep 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1; 2024: 0; 2025: 2; 2026: 1.
4 papers.
- 2023Model Checking for Closed-Loop Robot Reactive Planningcited by 1
- 2025ROSA: A Knowledge-based Solution for Robot Self-Adaptationcited by 0
- 2025Real-Time Model Checking for Closed-Loop Robot Reactive Planningcited by 0
- 2026Social, Legal, Ethical, Empathetic and Cultural Norm Operationalisation for AI Agentscited by 0
- 2026Social, Legal, Ethical, Empathetic and Cultural Norm Operationalisation for AI Agents12 Mar 2026
- 2025Real-Time Model Checking for Closed-Loop Robot Reactive Planning26 Aug 2025
- 2025ROSA: A Knowledge-based Solution for Robot Self-Adaptation29 Apr 2025
- 2023Model Checking for Closed-Loop Robot Reactive Planning16 Nov 2023