Po-Lun Chen

National Taiwan University, University of Maryland, College Park

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About

Po-Lun Chen is a robotics researcher whose work bridges the gap between human expertise and autonomous systems, with a particular focus on agricultural robotics and collaborative human-robot interaction. His primary research areas include human-robot cooperation, adjustable autonomy, and active perception for mobile robots. Chen's most significant contribution is the development of a human-robot cooperative vehicle for tea plucking (2020, 12 citations), which addresses critical labor shortages in the tea industry by leveraging human harvesting expertise while providing robotic power assistance. He further advanced this concept with a collaborative robot for tea harvesting featuring adjustable autonomy (2021, 9 citations), enabling robots to execute stable side-by-side motions in narrow terrain gardens while allowing humans to maintain supervisory control. In his more recent work, Chen developed DyFOS (2023, 2 citations), an active perception method that dynamically finds optimal sensor states to minimize localization uncertainty for perception-denied rovers, demonstrating his versatility in tackling fundamental robotics challenges. His research exemplifies a practical, human-centered approach to robotics that prioritizes effective collaboration over full automation.