# Towards Adaptive Planning of Assistive-care Robot Tasks

arXiv: https://arxiv.org/abs/2209.14041 · HTML: https://mlsanity.com/paper/2209.14041/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Sep 2022.

## Built on by (most cited first, 4 of 4)

- [Model Checking for Closed-Loop Robot Reactive Planning](https://mlsanity.com/paper/2311.09780/) (2023)
- [ROSA: A Knowledge-based Solution for Robot Self-Adaptation](https://mlsanity.com/paper/2505.00733/) (2025)
- [Real-Time Model Checking for Closed-Loop Robot Reactive Planning](https://mlsanity.com/paper/2508.19186/) (2025)
- [Social, Legal, Ethical, Empathetic and Cultural Norm Operationalisation for AI Agents](https://mlsanity.com/paper/2603.11864/) (2026)

## 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.