Tai-Yu Tsou

National Yang Ming Chiao Tung University

Papers

Total Citations

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About

Tai-Yu Tsou’s research lies at the intersection of assistive robotics, computer vision, and human-robot interaction, with a particular focus on developing intelligent navigation and tracking systems for wheelchair robots. His most impactful contribution is a Bayesian framework that integrates RGB-D sensor data from Microsoft Kinect for simultaneous localization and mapping (SLAM) and human tracking, enabling a wheelchair robot to autonomously navigate while following a caregiver. This work, published in 2013, has garnered 13 citations and is foundational for assistive mobility systems. Tsou further advanced human-robot interaction through a fuzzy controller-based system that fuses laser range finder and visual data to detect and follow an accompanist, demonstrating robust real-world performance. His adaptive online learning approach, combining multiple classifiers with an RGB-D appearance model, improved tracking efficiency in dynamic environments. Collectively, Tsou’s work addresses critical challenges in care assistance, enhancing the autonomy and safety of wheelchair robots. His contributions are particularly notable for their practical integration of low-cost sensors and real-time algorithms, making assistive robotics more accessible and reliable for elderly and disabled users.