Papers
2
Total Citations
5
H-Index
2
About
Juan Chen is a researcher whose work bridges the critical intersection of industrial automation, environmental sustainability, and advanced robotics. Her primary research areas include the environmental impact of global production networks and simultaneous localization and mapping (SLAM) for autonomous mobile robots. Chen’s major contributions are twofold: she has provided groundbreaking analysis on how industrial automation affects carbon emissions within global supply chains, offering an international comparative perspective that informs sustainable manufacturing policy. In robotics, she developed the improved Vibe (IVibe) algorithm for RGB-D SLAM, which significantly enhances dynamic object detection—such as walking people—that traditionally degrades autonomous navigation performance. Her most cited paper, “Evaluating the impact of industrial automation on China’s carbon emissions” (2025), has already garnered 3 citations, reflecting growing interest in her environmental work. Her notable achievement in robotics, the IVibe algorithm, addresses a fundamental challenge in mobile robot autonomy by enabling robust operation in dynamic environments. Chen’s dual focus on environmental sustainability and robotic perception positions her as a versatile researcher whose work has implications for both green manufacturing and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Dynamic Object Detection Using Improved Vibe for RGB-D SLAM2 citations · 2018