scholarly journals Extending the Application of an Assistant Personal Robot as a Walk-Helper Tool

Robotics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 27 ◽  
Author(s):  
Palacín ◽  
Clotet ◽  
Martínez ◽  
Martínez ◽  
Moreno
Keyword(s):  
Mobile Robot ◽  
User Interaction ◽  
Automatic Generation ◽  
Physical Support ◽  
Higher Weights ◽  
Personal Robot ◽  
Walking Aid ◽  
At Home

This paper presents the application of a mobile robot designed as an Assistant Personal Robot (APR) as a walk-helper tool. The hypothesis is that the height and weight of this mobile robot can be used also to provide a dynamic physical support and guidance to people while they walk. This functionality is presented as a soft walking aid at home but not as a substitute of an assistive cane or a walker device, which may withstand higher weights and provide better stability during a walking. The APR operates as a walk-helper tool by providing user interaction using the original arms of the mobile robot and by using the onboard sensors of the mobile robot in order to avoid obstacles and guide the walking through free areas. The results of the experiments conducted with the walk-helper have showed the automatic generation of smooth walking trajectories and a reduction in the number of manual trajectory corrections required to complete a walking displacement.

scholarly journals Automatic Generation of an Optimal Guide Map for a Mobile Robot.

1993 ◽  
Vol 59 (563) ◽  
pp. 1968-1975
Author(s):  
Toshihiko Kanbara ◽  
Jun Miura ◽  
Yoshiaki Shirai ◽  
Minoru Asada
Keyword(s):  
Mobile Robot ◽  
Automatic Generation

scholarly journals Speech Rate Adjustments in Conversations With an Amazon Alexa Socialbot

2021 ◽  
Vol 6 ◽  
Author(s):  
Michelle Cohn ◽  
Kai-Hui Liang ◽  
Melina Sarian ◽  
Georgia Zellou ◽  
Zhou Yu
Keyword(s):  
Human Computer Interaction ◽  
Speech Rate ◽  
User Interaction ◽  
Interaction Studies ◽  
User Ratings ◽  
Computer Interaction ◽  
At Home

This paper investigates users’ speech rate adjustments during conversations with an Amazon Alexa socialbot in response to situational (in-lab vs. at-home) and communicative (ASR comprehension errors) factors. We collected user interaction studies and measured speech rate at each turn in the conversation and in baseline productions (collected prior to the interaction). Overall, we find that users slow their speech rate when talking to the bot, relative to their pre-interaction productions, consistent with hyperarticulation. Speakers use an even slower speech rate in the in-lab setting (relative to at-home). We also see evidence for turn-level entrainment: the user follows the directionality of Alexa’s changes in rate in the immediately preceding turn. Yet, we do not see differences in hyperarticulation or entrainment in response to ASR errors, or on the basis of user ratings of the interaction. Overall, this work has implications for human-computer interaction and theories of linguistic adaptation and entrainment.

2A2-B10 Automatic Generation of Image-Based Indoor Walkthrough Environments by a Mobile Robot

2007 ◽  
Vol 2007 (0) ◽  
pp. _2A2-B10_1-_2A2-B10_2
Author(s):  
Kentaro TAKEMURA ◽  
Tsuyoshi SUENAGA ◽  
Osamu MATSUMOTO ◽  
Yoshio MATSUMOTO ◽  
Tsukasa OGASAWARA
Keyword(s):  
Mobile Robot ◽  
Automatic Generation

SG-Robot: CDMA Network-Operated Mobile Robot for Security Guard at Home

2006 ◽  
pp. 633-638 ◽  
Author(s):  
Je-Goon Ryu ◽  
Se-Kee Kil ◽  
Hyeon-Min Shim ◽  
Sang-Moo Lee ◽  
Eung-Hyuk Lee ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Security Guard ◽  
At Home

HUMAN GAIT BEHAVIOR INTERPRETATION BY A MOBILE HOME HEALTHCARE ROBOT

2012 ◽  
Vol 12 (04) ◽  
pp. 1240021 ◽  
Author(s):  
MYAGMARBAYAR NERGUI ◽  
YUKI YOSHIDA ◽  
WENWEI YU
Keyword(s):  
Mobile Robot ◽  
Motor Function ◽  
Human Behavior ◽  
Lower Limb ◽  
Home Healthcare ◽  
Depth Image ◽  
Human Gait ◽  
Mobile Home ◽  
Joint Angles ◽  
At Home

The ultimate goal of this study is to develop autonomous mobile home healthcare robots which closely monitor and evaluate the patients' motor function, and their at-home training therapy process, providing automatically calling for medical personnel in emergency situations. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs), and meanwhile, relieve therapists from great burden in canonical rehabilitation. In order to achieve this goal, we have developed the following programs/algorithms for monitoring human activities and recognizing human behaviors: (1) control programs for a mobile robot to track and follow a human subject by three different viewpoints; (2) algorithms for analyzing lower limb joint angles from RGB-D images from a Kinect sensor setup at a mobile robot; and (3) algorithms for recognizing human gait behavior. In (1), side viewpoint, front/back viewpoint and a middle angle viewpoint (between two former viewpoints) tracking were developed. In (2), depth image compensation with colored markers was implemented to deal with the skeleton point extraction error caused by mixing-up and frame flying of depth image during tracking and following human subjects by the mobile robot. In (3), we have proposed a hidden Markov model (HMM) based human behavior recognition using lower limb joint angles and trunk angle. Experimental results showed that joint trajectory could be measured and analyzed with high accuracy compared to a motion tracking system, and human behavior could be recognized from the joint trajectory.

Towards Long-Term Deployment of a Mobile Robot for at-Home Ambient Assisted Living of the Elderly

2019 ◽  
Author(s):  
Matteo Luperto ◽  
Javier Monroy ◽  
J. Raul Ruiz-Sarmiento ◽  
Francisco-Angel Moreno ◽  
Nicola Basilico ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
The Elderly ◽  
At Home
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