EgoAsk: Egocentric Teaching of Personalized Object Knowledge for Household Robots

2026-09-15

AI Summary

为解决家用机器人难以自动获取个性化物体知识的问题，EgoAsk系统通过智能眼镜主动嵌入日常活动教学，识别知识缺口并提出相关问题以辅助未来家庭服务。

Abstract

Unlike users, who know their own belongings and routines, household robots cannot easily acquire such personalized object knowledge automatically and depend on users to teach them. User-initiated teaching requires users to arrange dedicated teaching sessions and decide what to teach, even when they are unsure what the robot needs to learn. We introduce EgoAsk, a smart-glasses-based system that proactively embeds personalized object teaching into everyday activities. EgoAsk shares the user's first-person view with the robot, identifies gaps in personalized object knowledge, and analyzes ongoing activity to ask context-relevant questions that support future household assistance. To examine how teaching initiative and question timing affect users' teaching experiences, we conducted a within-subjects study with 18 participants and found lower reported knowledge-gap monitoring burden with robot-initiated questioning and less need for context reconstruction with EgoAsk. These findings characterize teaching burdens and timing preferences, offering design implications for egocentric robot-teaching systems.

Problem

• household robots
• personalized object knowledge
• user-initiated teaching

Innovation

• Egocentric Teaching
• Personalized Object Knowledge
• Smart-glasses-based System
• Context-relevant Questions