Papers
3
Total Citations
20
H-Index
2
About
Yuda Chen is a robotics researcher specializing in state estimation, autonomous navigation, and multi-robot coordination for mobile manipulation systems. Their work focuses on hybrid wheeled-legged robots, where they have made significant contributions to sensor fusion and locomotion control. Chen's most cited paper (2021, 12 citations) introduces a novel state estimation framework that seamlessly integrates multiple sensor inputs for hybrid robots performing mobile manipulation, featuring a unified odometry approach that eliminates tracking discontinuities. Their research on supervised autonomy (2021, 6 citations) advances remote teleoperation of quadrupedal bimanual manipulators by combining advanced perception with intuitive human-in-the-loop decision-making. Chen has also addressed fundamental challenges in multi-robot systems, developing MPC-based trajectory generation methods with theoretical guarantees for deadlock resolution and recursive feasibility (2022). Their work bridges critical gaps between theoretical guarantees and practical deployment in complex, shared environments. With growing citation impact and contributions spanning perception, control, and human-robot interaction, Chen is establishing themselves as an emerging leader in mobile manipulation robotics, particularly for applications requiring robust autonomy in unstructured settings.
Research Focus
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Top Papers
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