Pin-Yi Tseng

National Yang Ming Chiao Tung University

Papers

Total Citations

H-Index

About

Pin-Yi Tseng’s research lies at the intersection of assistive robotics, computer vision, and human-robot interaction, with a focus on developing intelligent wheelchair systems that enhance mobility and care for individuals with disabilities. His most cited work introduces a novel RGB-D sensor-based approach to simultaneous localization and mapping (SLAM) combined with human tracking, using a Bayesian framework to enable a wheelchair robot to navigate autonomously while following a caregiver. This paper has garnered 13 citations for its practical integration of low-cost Kinect sensors with robust feature extraction algorithms like SURF. Tseng further advanced this line of inquiry by proposing a fuzzy controller for accompanist detection and following, fusing laser range finder data with multisensory inputs to reliably track a target person in dynamic environments. His work on adaptive online learning for human tracking, employing a cascaded multiple-classifier system with an RGB-D appearance model, demonstrates a commitment to real-time, efficient care assistance. Though his citation counts are modest, Tseng’s contributions are notable for their applied focus on improving quality of life through accessible robotic aids, bridging perception and control in service robotics.