Seeking and Approaching Users in Domestic Environments: Testing a Reactive Approach on Two Commercial Robots

Socially Assistive Robots used for elderly care are required to determine the location of a person and to approach him/her in order to provide assistance. Human tracking systems are applied to detect and track people that are already in the proximity of the robot, while its limited field of view makes the user easily lost. Moreover, navigation algorithms typically need the availability of reliable sensors on the robot and the possibility of marking possible user locations. On the contrary, in this work, we investigate the opportunity to use a reactive control mechanism for detecting and approaching people. Our approach is tested on two commercial mobile robots that present a different sensors configuration and by using off-the-shelf algorithms for people localization and tracking. Results show the feasibility of the approach with respect to the considered domain that does not require precise positioning, but hopes for a real application of such low-cost robot into the wild. Features of the considered robots and their impact on performance are also discussed.

[1]  Karsten Berns,et al.  A survey of human location estimation in a home environment , 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.

[2]  Pascal Fua,et al.  Making Action Recognition Robust to Occlusions and Viewpoint Changes , 2010, ECCV.

[3]  Silvia Rossi,et al.  Can you follow that guy? , 2014, ESANN.

[4]  Silvia Rossi,et al.  Periodic Adaptive Activation of Behaviors in Robotic Systems , 2008, Int. J. Pattern Recognit. Artif. Intell..

[5]  Silvia Rossi,et al.  User's Personality and Activity Influence on HRI Comfortable Distances , 2017, ICSR.

[6]  Diane J. Cook,et al.  Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments , 2016, J. Ambient Intell. Humaniz. Comput..

[7]  Silvia Rossi,et al.  Monitoring Strategies for Adaptive Periodic Control in Behavior-Based Robotic Systems , 2009, 2009 Advanced Technologies for Enhanced Quality of Life.

[8]  Axel Buendia,et al.  INTERACTIVE PERSON FOLLOWING FOR SOCIAL ROBOTS: HYBRID REASONING BASED ON FUZZY AND MULTIPLE-OBJECTIVES DECISION MAKING APPROACHES , 2011 .

[9]  A. Mcgregor,et al.  Body-Worn Sensor Design: What Do Patients and Clinicians Want? , 2011, Annals of Biomedical Engineering.

[10]  Robert Harle,et al.  Location Fingerprinting With Bluetooth Low Energy Beacons , 2015, IEEE Journal on Selected Areas in Communications.

[11]  Sheung-Tak Cheng Cognitive Reserve and the Prevention of Dementia: the Role of Physical and Cognitive Activities , 2016, Current Psychiatry Reports.

[12]  Yaser Sheikh,et al.  OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Silvia Rossi,et al.  Two deep approaches for ADL recognition: A multi-scale LSTM and a CNN-LSTM with a 3D matrix skeleton representation , 2017, 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).

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

[15]  Karsten Berns,et al.  Behavior-based search of human by an autonomous indoor mobile robot in simulation , 2013, Universal Access in the Information Society.

[16]  Horst-Michael Groß,et al.  Finding People in Apartments with a Mobile Robot , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.