Dalong Liu

Guangdong University of Technology, Guangzhou Vocational College of Science and Technology

Papers

Total Citations

H-Index

About

Dalong Liu is a researcher specializing in robotics, with a focus on precision control, intelligent navigation, and autonomous systems. His key contributions lie in developing advanced algorithms for robot pose optimization and obstacle avoidance, addressing critical challenges in both industrial and underwater environments. Notably, his 2018 work on "Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement" introduced a dynamic tracking approach using actual D-H parameter measurements and feedback compensation, significantly enhancing robot positioning accuracy—a foundational contribution cited 3 times. Liu also advanced autonomous navigation with his 2019 study on "Design of Obstacle Avoidance Algorithm for Submarine Intelligent Robot," which proposed novel path-planning strategies for coastal and underwater robotics, earning 3 citations. His recent 2025 paper on "Robot path planning and obstacle avoidance algorithm based on visual perception" further integrates visual sensing for real-time navigation, reflecting his ongoing innovation in perception-driven robotics. With a cumulative impact of 7 citations across these works, Liu’s research bridges theoretical control methods and practical applications, offering valuable insights for students and engineers working on robotic autonomy, sensor integration, and marine robotics.