Li-Hsiang Chou

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About

Li-Hsiang Chou is a robotics researcher specializing in autonomous navigation, obstacle avoidance, and cyber-physical systems for service robots. Their major contributions center on developing vision-based control methods that enable mobile robots to operate safely and efficiently in dynamic indoor environments. Chou’s most cited work, "Obstacle Avoidance of Mobile Robot Based on HyperOmni Vision" (2019, 21 citations), introduces a novel fusion of an improved dynamic window approach with artificial potential fields, allowing wheeled robots to navigate complex obstacle courses—a method validated under the rigorous rules of the RoboSot avoidance challenge. They have also advanced practical ROS-based navigation through "Auto-maps-generation through Self-path-generation in ROS-based Robot Navigation" (2018), which automates map creation and path planning simultaneously. More recently, Chou’s "Design and implementation of an autonomous service robot based on cyber physical modeling systems" (2022) demonstrates a fully integrated service robot incorporating human-robot interaction, indoor mapping, and CPS principles. With a growing citation impact and a focus on real-world deployment, Chou’s work bridges theoretical algorithms and tangible robotic systems, offering valuable insights for students and researchers in autonomous robotics and intelligent systems.