Activity Recommendation System for Social Assistive Robot Based on Ego Social Network Analysis in Multi-Human Environment
Date Issued
2014
Date
2014
Author(s)
Chu, Ting-Sheng
Abstract
Social interaction is an important means for maintaining our social relationship. It directly affects humans'' interpersonal relationship, acting as an important factors which influence humans'' mental status as well as physiological condition especially for elders. Owing to vast developments in the field of robotics in recent years, robotic assistance to enhance social interactions among humans is now a general expectation. For this reason, we hope to endow robots with an ability to help humans promote social interactions through recommending of appropriate social activities and providing of corresponding assistance.
With this as our aim, in this thesis we develop an innovative activity recommendation system for such social assistive robot based on the ego social network analysis in multi-human environment. At first, a novel idea to combine the first-person camera and the robot camera to construct an ego social network is introduced. Four types of social interaction features for perceiving the intimacy level are proposed subsequently based on a user study we have conducted. Afterwards, a social activity recommendation model is presented in order to recommend appropriate activities cooperating with the former ego social network analysis. Finally, through the evaluation by several conducted experiments, we demonstrate that our system have the ability to reason and offer the pertinent assistance for humans'' social interactions.
Subjects
社交機器人
社交輔助
自我社交網路
活動推薦
第一人稱視角攝影機
Type
thesis
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