Pengfei Ni

China University of Petroleum, East China

Papers

Total Citations

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About

Pengfei Ni is a researcher specializing in autonomous mobile robotics, with a particular focus on Simultaneous Localization and Mapping (SLAM) — a foundational challenge in enabling robots to navigate and understand unknown environments independently. His work centers on advancing the filtering algorithms that underpin SLAM systems, pushing beyond conventional approaches to improve robustness and computational reliability. His most notable contribution, "Square-root Unscented Kalman Filter Based Simultaneous Localization and Mapping" (2010), has garnered 14 citations and addresses a critical limitation in standard Unscented Kalman Filter (UKF) implementations by incorporating square-root filtering techniques to guarantee numerical stability through non-negative definiteness of covariance matrices. This refinement makes SLAM solutions more dependable in real-world robotic applications. Building on this, his 2011 work introduced an Unscented H∞ filter approach to SLAM, tackling the restrictive Gaussian noise assumption inherent in traditional Kalman-based methods, thereby enhancing system resilience under uncertain or non-ideal noise conditions. Ni's research collectively advances the practical autonomy of mobile robots by making localization and mapping algorithms more mathematically sound and adaptable. His contributions offer valuable tools for researchers and engineers working toward fully autonomous robotic navigation systems.