Design of a cloud robotic system to support senior citizens: the KuBo experience

This paper describes a system based on a robot, called KuBo, which relies on cloud resources to extend its capabilities for human interaction and environmental sensing to provide services for independent living. The robot uses text-to-speech and speech recognition services as well as an electronic agenda and web resources to perform several tasks. Moreover it retrieves smart environmental data from a DataBase to be aware of the context. In this paper, the cloud robotics approach is used to increase the skills of a robot, endowing the system with abilities for human–robot interaction and environmental sensing. The robotic services have been defined with a focus group involving 19 elderly volunteers and the system has been tested in a real environment with a couple of elderly users for five days. The aim of the experiment was to test the technical feasibility of the proposed cloud services using quantitative tools. The technical results show a success rate of 86.2 % for the navigation task and more than 90 % for the speech capabilities. Furthermore, the robustness of the system was also confirmed by users’ qualitative feedback.

[1]  Dejan Pangercic,et al.  Web-enabled Robots -- Robots that Use the Web as an Information Resource , 2011, ICRA 2011.

[2]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[3]  Alessandro Saffiotti,et al.  Network robot systems , 2008, Robotics Auton. Syst..

[4]  Paolo Dario,et al.  Preliminary Findings of the AALIANCE2 Ambient Assisted Living Roadmap , 2014 .

[5]  Alessandro Saffiotti,et al.  Design of cloud robotic services for senior citizens to improve independent living in multiple environments , 2015, Intelligenza Artificiale.

[6]  P. Dario,et al.  Supporting active and healthy aging with advanced robotics integrated in smart environment , 2016 .

[7]  Guoqiang Hu,et al.  Cloud robotics: architecture, challenges and applications , 2012, IEEE Network.

[8]  Pieter Abbeel,et al.  Image Object Label 3 D CAD Model Candidate Grasps Google Object Recognition Engine Google Cloud Storage Select Feasible Grasp with Highest Success Probability Pose EstimationCamera Robots Cloud 3 D Sensor , 2014 .

[9]  Mikhail Simonov,et al.  Ubiquitous Monitoring & Service Robots for Care , 2012 .

[10]  Paolo Dario,et al.  Design for Acceptability: Improving Robots’ Coexistence in Human Society , 2010, Int. J. Soc. Robotics.

[11]  Masayuki Inaba,et al.  Remote-Brained Robots , 1997, IJCAI.

[12]  Rüdiger Dillmann,et al.  Robot Companions for Citizens , 2011, FET.

[13]  Orsolya Lelkes,et al.  Poverty of Elderly People in EU25 , 2006 .

[14]  Paulo Menezes,et al.  Cloud Robotics: Toward Context Aware Robotic Networks , 2011 .

[15]  Sabrina Stula,et al.  Living in Old Age in Europe - Current Developments and , 2012 .

[16]  Vanessa Evers,et al.  Measuring acceptance of an assistive social robot: a suggested toolkit , 2009, RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication.

[17]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[18]  Filippo Cavallo,et al.  AALIANCE Ambient Assisted Living Roadmap , 2010, Ambient Intelligence and Smart Environments.

[19]  Gabriel L. Oliveira,et al.  View Planning For Cloud-Based Active Object Recognition , 2013 .

[20]  Horst-Michael Groß,et al.  Playing hide and seek with a mobile companion robot , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[21]  David R. Thomas,et al.  A General Inductive Approach for Analyzing Qualitative Evaluation Data , 2006 .

[22]  Wolfram Burgard,et al.  The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..

[23]  Shuichi Nishio,et al.  Cloud networked robotics , 2012, IEEE Network.

[24]  Alessandro Saffiotti,et al.  Development of a Socially Believable Multi-Robot Solution from Town to Home , 2014, Cognitive Computation.

[25]  M Tenorth,et al.  Web-Enabled Robots , 2011, IEEE Robotics & Automation Magazine.

[26]  Javier Civera,et al.  C2TAM: A Cloud framework for cooperative tracking and mapping , 2014, Robotics Auton. Syst..

[27]  Amedeo Cesta,et al.  GiraffPlus: a system for monitoring activities and physiological parameters and promoting social interaction for elderly. , 2014 .

[28]  Kenneth Y. Goldberg,et al.  Cloud-based robot grasping with the google object recognition engine , 2013, 2013 IEEE International Conference on Robotics and Automation.

[29]  Patrick Benavidez,et al.  Cloud-based realtime robotic Visual SLAM , 2015, 2015 Annual IEEE Systems Conference (SysCon) Proceedings.

[30]  A. Cesta,et al.  Enabling Social Interaction Through Embodiment in Ex CITE , 2010 .

[31]  David Nistér,et al.  Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[32]  Somaya Ben Allouch,et al.  Acceptance and use of a social robot by elderly users in a domestic environment , 2010, 2010 4th International Conference on Pervasive Computing Technologies for Healthcare.

[33]  D. Lorencik,et al.  Cloud robotics: Current trends and possible use as a service , 2013, 2013 IEEE 11th International Symposium on Applied Machine Intelligence and Informatics (SAMI).

[34]  Yinong Chen,et al.  Robot as a Service in Cloud Computing , 2010, 2010 Fifth IEEE International Symposium on Service Oriented System Engineering.