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About

Zican Wang is a rising researcher in the field of haptic teleoperation and human-robot interaction, with a focus on enhancing the transparency and intuitiveness of remote control systems. His work centers on three key areas: subjective haptic experience prediction, variable impedance control, and interactive shared control. In his most cited paper (2022, 11 citations), Wang introduced a novel quality assessment approach for predicting subjective haptic experience in time-delayed teleoperation, addressing a critical challenge in remote robot control and virtual reality. He further advanced the field with a haptic sensor-aided Variable Impedance Controller (2024, 6 citations) that simultaneously estimates both environment and human operator stiffness, enabling more adaptive and natural human-in-the-loop applications. Wang’s innovative Interactive Semantic Shared Control framework (2023) exploits an active high-level communication loop between human operators and robots, significantly improving time efficiency in teleoperation tasks. Through these contributions, Wang is helping to bridge the gap between human intent and robotic action, making teleoperation systems more responsive and user-friendly for applications ranging from remote surgery to hazardous environment exploration.