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About

Han-Jung Chou is a robotics researcher specializing in autonomous navigation and obstacle avoidance for nonholonomic mobile robots. His core research focuses on developing real-time path planning algorithms that leverage hydrodynamic principles—specifically, the harmonic potential fields of incompressible fluids governed by Laplace’s equation—to generate smooth, curvature-constrained trajectories. Chou’s major contributions include a streamline-based obstacle avoidance system that enables robots to navigate partially unknown environments with static obstacles while respecting kinematic constraints. His work demonstrates how fluid dynamics concepts can produce natural-looking, predictable paths for autonomous vehicles. Among his most cited works, "A real-time streamline-based obstacle avoidance system for curvature-constrained nonholonomic mobile robots" (2017, 6 citations) and "A Real-Time Hydrodynamic-Based Obstacle Avoidance System" (2018, 4 citations) establish his reputation in integrating numerical methods like log-space harmonic potential functions with practical robotics. Chou’s research bridges theoretical fluid dynamics and applied robotics, offering computationally efficient solutions for real-world navigation challenges. His simulation studies validate these approaches, positioning his work as a valuable resource for researchers developing autonomous systems in constrained environments.