Abstract
The deployment of robots at home must involve robots with pre-defined skills and the capability of personalizing their behavior by non-expert users. A framework to tackle this personalization is presented and applied to an automatic feeding task. The personalization involves the caregiver providing several examples of feeding using Learning-by-Demostration, and a ProMP formalism to compute an overall trajectory and the variance along the path. Experiments show the validity of the approach in generating different feeding motions to adapt to user’s preferences, automatically extracting the relevant task parameters. The importance of the nature of the demonstrations is also assessed, and two training strategies are compared.
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Notes
- 1.
A video showing the process of the personalized feeding task can be found at www.iri.upc.edu/groups/perception/frameworkFUTE.
References
Abdo, N., Stachniss, C., Spinello, L., Burgard, W.: Robot, organize my shelves! tidying up objects by predicting user preferences. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1557–1564 (2015)
Baraka, K., Veloso, M.: Adaptive interaction of persistent robots to user temporal preferences. In: Tapus, A., André, E., Martin, J.C., Ferland, F., Ammi, M. (eds.) Social Robotics. LNCS, vol. 9388, pp. 61–71. Springer, Heidelberg (2015)
Chen, T.L., Ciocarlie, M., Cousins, S., Grice, P.M., Hawkins, K., Hsiao, K., Kemp, C.C., King, C.H., Lazewatsky, D.A., Leeper, A.E., Nguyen, H., Paepcke, A., Pantofaru, C., Smart, W.D., Takayama, L.: Robots for humanity: using assistive robotics to empower people with disabilities. IEEE Robot. Autom. Magaz. 20(1), 30–39 (2013)
Chernova, S., Veloso, M.: Interactive policy learning through confidence-based autonomy. J. Artif. Intell. Res. 34, 1–25 (2009)
Clabaugh, C., Ragusa, G., Sha, F., Matarić, M.: Designing a socially assistive robot for personalized number concepts learning in preschool children. In: International Conference on Development and Learning and Epigenetic Robotics, pp. 314–319 (2015)
Colomé, A., Neumann, G., Peters, J., Torras, C.: Dimensionality reduction for probabilistic movement primitives. In: IEEE-RAS International Conference on Humanoid Robots, pp. 794–800 (2014)
Colomé, A., Pardo, D., Alenyà, G., Torras, C.: External force estimation during compliant robot manipulation. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3535–3540 (2013)
Fiore, M., Clodic, A., Alami, R.: On planning and task achievement modalities for human-robot collaboration. In: Hsieh, H.A., Khatib, O., Kumar, V. (eds.) Experimental Robotics. Springer Tracts in Advanced Robotics, vol. 109, pp. 293–306. Springer, Heidelberg (2016)
Gao, Y., Chang, H.J., Demiris, Y.: User modelling for personalised dressing assistance by humanoid robots. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1840–1845 (2015)
Greczek, J., Short, E., Clabaugh, C., Swift-Spong, K., Matarić, M.J.: Socially assistive robotics for personalized education for children. In: AAAI Fall Symposium on Artificial Intelligence and Human-Robot Interaction (2014)
Klee, S.D., Ferreira, B.Q., Silva, R., Costeira, J.P., Melo, F.S., Veloso, M.: Personalized assistance for dressing users. In: Tapus, A., André, E., Martin, J.C., Ferland, F., Ammi, M. (eds.) Social Robotics. LNCS, vol. 9388, pp. 359–369. Springer, Heidelberg (2015)
Leyzberg, D., Spaulding, S., Scassellati, B.: Personalizing robot tutors to individuals’ learning differences. In: ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 423–430. ACM (2014)
Maslow, A.H.: A theory of human motivation. Psych. Rev. 50(4), 370–396 (1943)
Niekum, S., Osentoski, S., Konidaris, G., Barto, A.G.: Learning and generalization of complex tasks from unstructured demonstrations. In: International Conference on Intelligent Robots and Systems (IROS), pp. 5239–5246. IEEE (2012)
Paraschos, A., Daniel, C., Peters, J., Neumann, G.: Probabilistic movement primitives. In: Advances in Neural Information Processing Systems (NIPS) (2013)
Song, W.K., Song, W.J., Kim, Y., Kim, J.: Usability test of KNRC self-feeding robot. In: International Conference on Rehabilitation Robotics, pp. 1–5 (2013)
Topping, M.: An overview of the development of handy 1, a rehabilitation robot to assist the severely disabled. Intell. Robot. Syst. 34(3), 253–263 (2002)
Zhang, X., Wang, X., Wang, B., Sugi, T., Nakamura, M.: Real-time control strategy for EMG-drive meal assistance robot - my spoon. In: International Conference on Control, Automation and Systems (ICCAS), pp. 800–803 (2008)
Acknowledgments
This work has been supported by the MINECO project RobInstruct TIN2014-58178-R and the ERA-Net CHIST-ERA project I-DRESS PCIN-2015-147. Gerard Canal is also supported by the Ministry of Economy and Knowledge of the Government of Catalonia via a FI-DGR 2016 fellowship.
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Canal, G., Alenyà, G., Torras, C. (2016). Personalization Framework for Adaptive Robotic Feeding Assistance. In: Agah, A., Cabibihan, JJ., Howard, A., Salichs, M., He, H. (eds) Social Robotics. ICSR 2016. Lecture Notes in Computer Science(), vol 9979. Springer, Cham. https://doi.org/10.1007/978-3-319-47437-3_3
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