Dongdong Weng
Papers
4
Total Citations
20
H-Index
2
About
Dongdong Weng is a leading researcher at the intersection of mixed reality (MR), human-robot interaction, and intelligent telecollaboration systems. His work fundamentally addresses how humans can intuitively control and interact with robotic systems through immersive virtual and augmented environments. Weng’s most impactful contribution is the development of a viewpoint-controllable telepresence system that integrates a robotic arm with mixed reality, enabling remote users to actively manipulate their perspective during telecollaboration—a breakthrough that overcomes the passive viewing limitations of traditional video feeds (12 citations). He has also pioneered novel approaches in magnetic navigation for wheeled mobile robots, combining fuzzy logic and PID control for optimized path detection and motion. In healthcare robotics, Weng introduced RelaxMR, a mixed-reality-based digital human massage system that reduces user anxiety by replacing cold robotic arms with high-fidelity virtual representations. Additionally, his work on hierarchical knowledge transfer using virtual reality demonstrates how complex tasks like folding clothes can be taught to physical robots through abstract graph-based representations, validated on a Baxter robot. With a growing citation footprint, Weng’s research continues to shape the future of seamless, intuitive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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