Jinxiang Pian

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About

Jinxiang Pian is a researcher focused on advancing robotics through intelligent control and optimization algorithms. His work centers on two key areas: robot path planning and teleoperation systems. In his highly cited 2022 paper, "Research on Robot Path Planning Based on Improved Genetic Algorithm," Pian addressed critical limitations in traditional genetic algorithms—such as initial population blindness, excessive path turning points, and susceptibility to local optima—by integrating prior knowledge to initialize paths more effectively. This innovation enhances the efficiency and smoothness of autonomous robot navigation. Building on this, his 2023 study, "Research on master-slave teleoperation control algorithm based on exoskeleton master hand," tackles human-robot interaction by developing a wearable exoskeleton that captures real-time upper limb motion. Pian’s master-slave constraint algorithm enables intuitive, synchronous control of remote robots, offering a more anthropomorphic teleoperation experience. Though early in his career, with his most-cited works accumulating 2 and 1 citations respectively, Pian’s contributions are foundational for safer, more natural robotic systems. His research bridges optimization theory and practical human-robot collaboration, promising significant impact in autonomous navigation and remote manipulation.