Hailin Chen

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About

Hailin Chen is a researcher specializing in robotics and autonomous systems, with a particular focus on motion planning and control for mobile robots. His work integrates model predictive control (MPC) with potential field methods to enhance the navigation and path planning of omni-directional mobile robots, addressing key challenges in dynamic and obstacle-rich environments. His most-cited paper, "MPC Control and Path Planning of Omni-Directional Mobile Robot with Potential Field Method" (2018), has garnered 11 citations, reflecting its foundational contribution to the field. Chen’s research is notable for its practical approach to real-time trajectory optimization, enabling robots to operate more safely and efficiently in complex settings. His work is particularly relevant to applications in warehouse automation, service robotics, and autonomous exploration. By combining theoretical rigor with simulation and experimental validation, Chen has provided valuable insights for both academic researchers and engineers developing next-generation mobile robotic systems. His contributions continue to influence the design of robust, adaptive control strategies for autonomous vehicles.