Towards Lifelong Social Robot Navigation in Dynamic Environments

Qi Zhang*, Ioannis Stefanakos, Javier Camara Moreno, Radu Calinescu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We describe a work-in-progress approach to solving the problem of robot navigation in dynamically changing, social environments. Our approach employs reinforcement learning informed by a continually updated model that predicts the evolution of the environment, and handles two common scenarios: (1) a person moving within the environment, and (2) static obstacles with positions that change over time. We assess the effectiveness of the approach in a simulated assistive-care application in which a mobile robot supports a person with mild cognitive or physical impairments with simple everyday tasks.
Original languageEnglish
Title of host publication24th Towards Autonomous Robotic Systems Conference (TAROS), Proceedings
Number of pages5
Publication statusPublished - 15 Sept 2023
Event24th Towards Autonomous Robotic Systems Conference (TAROS) - Cambridge, United Kingdom
Duration: 13 Sept 202315 Sept 2023


Conference24th Towards Autonomous Robotic Systems Conference (TAROS)
Abbreviated titleTAROS
Country/TerritoryUnited Kingdom
Internet address

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.


  • Reinforcement Learning
  • Navigation
  • Self-Adaptive Systems
  • Assistive-Care Robots

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