Pujie Xin

Papers

Total Citations

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About

Pujie Xin is a robotics researcher specializing in safe autonomous navigation and multi-robot coordination in dynamic, human-filled environments. Their most cited work, "Towards Safe Navigation Through Crowded Dynamic Environments" (2021, 23 citations), introduces a neural network-based control policy that fuses lidar data with pedestrian motion history to enable mobile robots to safely traverse spaces cluttered with both static obstacles and dense crowds. This early fusion architecture represents a significant contribution to collision avoidance in real-world settings, addressing a critical gap in socially-aware navigation. More recently, Xin has explored optimization methods for multi-robot, multi-target tracking (2024, 5 citations), comparing stochastic approaches to enhance coordination efficiency. Their research bridges deep learning and control theory, with potential applications in service robotics, warehouse automation, and autonomous delivery. By tackling the challenge of safe navigation amid unpredictable human behavior, Xin’s work lays groundwork for robots that can operate seamlessly alongside people, advancing the frontier of human-robot interaction in crowded spaces.