Bowen Song

University of Florida, Shanghai Jiao Tong University, Beijing Institute of Technology

Papers

Total Citations

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About

Bowen Song is a multidisciplinary researcher whose work sits at the intersection of human-robot interaction, autonomous systems, and intelligent automation. With a focus on advancing the safety and efficiency of collaborative robotic environments, Song has made meaningful contributions to both industrial and medical robotics domains. Song's most cited work (21 citations) investigates how autonomous mobile robots influence human mental workload and productivity in smart warehouse settings, employing rigorous human-in-the-loop experimental methodologies to evaluate real-world human-robot collaboration. This research addresses critical safety concerns as robotic systems become increasingly embedded in logistics and manufacturing workflows. Complementing this, Song's research on long-term Visual Inertial SLAM (12 citations) tackles a fundamental challenge in mobile robotics — sustaining reliable navigation in dynamic, complex environments over extended deployments through innovative time-series map prediction techniques. More recently, Song has extended expertise into medical robotics, contributing an overview of human-computer interaction design principles in minimally invasive surgery robots, helping to synthesize and guide ongoing research in this rapidly evolving field. Collectively, Song's growing body of work reflects a consistent commitment to making robotic systems safer, smarter, and more intuitive across diverse real-world applications.