Publications by authors named "Sangbeom Park"
Recent successes in robot learning have significantly enhanced autonomous systems across a wide range of tasks. However, they are prone to generate similar or the same solutions, limiting the controllability of the robot to behave according to user intentions. These limited robot behaviors may lead to collisions and potential harm to humans.
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- Negative lifestyle choices significantly impact health, and addressing these requires heightened self-awareness and continuous monitoring of behaviors.
- Traditional methods for tracking user behavior, like questionnaires and activity counters, have limitations such as subjectivity and a narrow focus.
- This work introduces a multimodal context mining framework that analyzes various contexts (activities, emotions, locations) using machine learning to create a comprehensive understanding of user behavior, demonstrated through real-time context identification and evaluation in realistic scenarios.