Hongrui An

Papers

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About

Hongrui An is a researcher in intelligent manufacturing and robotics, with a focus on motion planning and obstacle avoidance for collaborative robots. Their most-cited work, "Obstacle Avoidance Path Planning Based on Improved APF and RRT" (2021, 15 citations), addresses a critical challenge in robotics: enabling robots to navigate complex environments safely and efficiently. By enhancing the Artificial Potential Field (APF) method—which often suffers from local minima and path inefficiencies—and integrating it with Rapidly-exploring Random Trees (RRT), An developed a hybrid approach that improves path smoothness and computational efficiency. This contribution is particularly relevant for collaborative robots in manufacturing, where real-time, adaptive navigation is essential. An’s research bridges theoretical algorithms and practical applications, offering solutions that reduce collision risks and optimize motion trajectories. Their work has been cited in subsequent studies on autonomous navigation and human-robot interaction, underscoring its impact on advancing intelligent automation. An’s dedication to solving real-world robotics problems makes them a notable figure in the field, with potential for further influence as collaborative robots become more prevalent in industry.