Xiaotao Zhang

Dalian University, Tianjin University of Technology

Papers

Total Citations

H-Index

About

Xiaotao Zhang’s research bridges critical frontiers in computer vision and robotics, with a focus on pedestrian detection and rescue robot dynamics. His pioneering work on pedestrian detection—a cornerstone for autonomous driving and video surveillance—introduced a Regional Proposal Network with feature fusion, achieving major performance gains in deep learning-based detection systems. This 2018 study, cited 6 times, laid groundwork for safer self-driving vehicles and intelligent security systems. More recently, Zhang has advanced rescue robotics by modeling the dynamics and impact response of robots equipped with two flexible manipulators. His 2024 paper, already garnering 5 citations, addresses the complex challenge of deploying robots in disaster scenarios, where adaptive, compliant manipulation is critical for victim extraction. By integrating flexible manipulators with robust control strategies, Zhang’s work enhances the survivability and effectiveness of rescue operations. His dual focus—on perception systems for autonomous navigation and on physical interaction for emergency response—demonstrates a rare ability to tackle both algorithmic and mechanical challenges. With growing citation impact, Zhang is establishing himself as a versatile researcher whose contributions directly improve safety and autonomy in real-world applications.