Yuyao He

Northwestern Polytechnical University, Chang'an University

Papers

Total Citations

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About

Yuyao He is a leading researcher in bio-inspired robotics and autonomous search strategies, with a focus on enabling robots to locate signal-emitting sources in complex, cue-sparse environments. His most influential work, “Collaborative infotaxis: Searching for a signal-emitting source based on particle filter and Gaussian fitting” (2020, 35 citations), introduces a novel multi-robot approach that combines particle filtering with Gaussian fitting to efficiently and collaboratively track intermittent or sporadic cues—a critical advance for applications like chemical plume tracing or disaster response. Earlier foundational contributions include an adaptive sliding mode tracking control law for nonholonomic mobile robots (2007, 8 citations), which uses backstepping and robust control to achieve global asymptotic trajectory tracking despite unknown parameters and bounded uncertainties. He has also developed bio-inspired guiding strategies (2016, 6 citations) that allow a single robot to seek an intermittent information source by exploiting local, dispersed cues such as light, heat, or chemical gradients. Across these works, He’s research bridges theoretical control design and practical robotic search, demonstrating how principles from animal foraging can be translated into robust, scalable algorithms. His work has been cited over 50 times, reflecting its growing influence in the fields of swarm robotics, sensor-based search, and adaptive control.