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Adapting robot task planning to user preferences: an assistive shoe dressing example

  • Gerard Canal
  • Guillem Alenyà
  • Carme Torras
Article
  • 74 Downloads
Part of the following topical collections:
  1. Special Issue: Learning for Human-Robot Collaboration

Abstract

Healthcare robots will be the next big advance in humans’ domestic welfare, with robots able to assist elderly people and users with disabilities. However, each user has his/her own preferences, needs and abilities. Therefore, robotic assistants will need to adapt to them, behaving accordingly. Towards this goal, we propose a method to perform behavior adaptation to the user preferences, using symbolic task planning. A user model is built from the user’s answers to simple questions with a fuzzy inference system, and it is then integrated into the planning domain. We describe an adaptation method based on both the user satisfaction and the execution outcome, depending on which penalizations are applied to the planner’s rules. We demonstrate the application of the adaptation method in a simple shoe-fitting scenario, with experiments performed in a simulated user environment. The results show quick behavior adaptation, even when the user behavior changes, as well as robustness to wrong inference of the initial user model. Finally, some insights in a non-simulated world shoe-fitting setup are also provided.

Keywords

Planning with preferences Behavior adaptation Task personalization Shoe fitting 

Notes

Acknowledgements

The authors thank Clea Parcerisas, Sergi Foix and Adrià Colomé for their help in the realization of the experiments, pictures and video.

Supplementary material

Supplementary material 1 (mp4 104868 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institut de Robòtica i Informàtica Industrial, CSIC-UPCBarcelonaSpain

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