Pi-Yun Chen
Papers
2
Total Citations
4
H-Index
2
About
Pi-Yun Chen is a robotics researcher specializing in autonomous navigation, human-robot interaction, and intelligent control systems. Their work bridges the gap between classical robotics algorithms and modern deep learning approaches, with a particular focus on enabling mobile robots to operate effectively in indoor environments. Chen's most-cited paper, "Indoor Mobile Robot Path Planning and Navigation System Based on Deep Reinforcement Learning" (2024), proposes a novel architecture that integrates end-to-end autonomous driving techniques with traditional navigation methods, addressing key limitations in real-world deployment. This work has already garnered attention for its practical approach to combining data-driven and model-based strategies. In earlier research, Chen developed a speech-controlled omnidirectional mobile robot using a Dynamic Time Warping (DTW)-based recognition algorithm (2016), demonstrating expertise in multimodal interaction systems. While citation counts are still growing, Chen's contributions represent important steps toward more intuitive and robust robotic systems. Their research holds particular promise for applications in service robotics, assistive technologies, and smart environments, where seamless human-robot collaboration and reliable autonomous navigation are critical.
Research Focus
Key Achievements
Top Papers
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- 2