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Wenjuan Yang is a leading researcher in intelligent robotics for extreme environments, with a primary focus on mining and industrial automation. Her work addresses critical challenges in autonomous navigation, precision manipulation, and energy efficiency for heavy machinery operating in confined, hazardous underground spaces. Yang’s most impactful contribution is her pioneering use of infrared thermography on an inspection robot for belt conveyor systems (32 citations), solving the long-standing problem of blind-spot monitoring and excessive manual workload. She has since advanced the field with an ant colony optimization method for energy-efficient cutting trajectory planning in axial robotic roadheaders (16 citations), significantly reducing operational energy consumption. Her recent innovations include a hybrid visual servo control system enabling high-precision anchor drilling in coal mines (4 citations) and a collision-prediction-based safe path planning algorithm for narrow tunnels (3 citations). Yang also developed a novel inverse kinematics solution using workspace analysis and iterative step coefficient adjustment (6 citations), improving the dexterity of general-purpose robots. Her work is instrumental in transitioning underground mining from manual, dangerous operations to safe, autonomous systems.