Song Yong

Shandong University, Shandong University of Technology

Papers

Total Citations

H-Index

About

Song Yong is a leading researcher in mobile robotics and bionic locomotion, with a focus on intelligent path planning and autonomous navigation in complex environments. His most influential work addresses the critical challenge of local minima in artificial potential field methods for mobile robot path planning, proposing novel solutions that prevent robots from becoming trapped in dead zones while navigating around obstacles. This research, published in 2020, has garnered 26 citations and is widely referenced by engineers developing real-time obstacle avoidance systems. Yong has also made significant contributions to complete coverage path planning, introducing a Finite State Machine and rolling window approach that enables robots to systematically explore unknown environments using only onboard sensors—a breakthrough for autonomous cleaning and inspection robots. His work on quadruped bionic robots further demonstrates his versatility, where he developed dynamic gait planning algorithms that enhance stability and energy efficiency in legged locomotion. With a career marked by practical, implementation-focused research, Yong’s algorithms are directly applicable to industrial and service robotics, and his papers continue to guide new generations of roboticists seeking robust, sensor-driven navigation solutions.