Papers
9
Total Citations
71
H-Index
5
About
Youyi Bi is at the forefront of research in human-robot interaction and smart manufacturing, with a focus on safe and adaptive motion planning. His major contributions include pioneering a co-evolution approach that integrates human digital twins and mixed reality to continuously improve both human safety cognition and robot motion strategies—a framework that has already garnered 20 citations since its 2025 publication. Bi also developed an adaptive multi-RRT approach for robot motion planning (18 citations) and formalized task characterization for human-robot autonomy allocation (12 citations), addressing the critical gap in understanding task difficulty in collaborative settings. His work extends to multi-agent systems, proposing integrated task assignment and path planning for mobile robots in smart factories, as well as leveraging Bayesian optimization-enhanced reinforcement learning and digital twins for adaptive motion planning. With recent papers exploring continual knowledge graph embedding for human-robot collaboration and imitation learning for decentralized multi-agent path planning, Bi’s research is shaping the future of safe, efficient, and intelligent robotic systems. His achievements demonstrate a deep commitment to advancing both theoretical foundations and practical applications in industrial automation.
Research Focus
Key Achievements
Top Papers
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- 2An adaptive multi-RRT approach for robot motion planning18 citations · 2024
- 3Formalized Task Characterization for Human-Robot Autonomy Allocation12 citations · 2019
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