Tie Wang

Climate Centre, Taiyuan University of Technology

Papers

Total Citations

H-Index

About

Tie Wang is a robotics researcher whose work focuses on intelligent navigation and environmental perception for mobile robots, particularly in hazardous environments. His most influential contribution addresses a fundamental challenge in autonomous navigation: the "Path Planning of Mobile Robot Based on Improved Artificial Potential Field Method" (2023, 14 citations). This work innovatively solves two critical flaws in traditional path planning—target unreachability and entrapment in local minima—by introducing a distance factor between the robot and its goal, enabling smoother, more reliable trajectories. Earlier, Wang laid groundwork in spatial awareness with "3D Reconstruction Based on Binocular Stereo Vision of Robot" (2011, 6 citations), where he developed a binocular stereo vision system for coal mine detection robots. This system reconstructs 3D models of obstacles, allowing robots to navigate and identify threats in post-disaster environments where visibility is poor. Wang’s research is notable for its direct application to life-saving missions, bridging theoretical path optimization with practical, sensor-driven perception. His work continues to influence mobile robotics, particularly in safety-critical and unstructured settings.