Liqiang Zhang

Shanghai University of Engineering Science

Papers

Total Citations

H-Index

About

Liqiang Zhang’s research focuses on intelligent robotics and autonomous navigation, with particular emphasis on path planning algorithms for service robots. His most cited work, “A Path Planning Algorithm for Sweeping Robot Based on Improved Neural Network” (2019), addresses critical limitations in traditional path planning methods, specifically their lack of self-learning capability and poor performance in local path planning. Zhang proposes an enhanced neural network-based approach that generates collision-free, efficient routes for sweeping robots, contributing to more adaptive and intelligent autonomous systems. While his citation count remains modest at 3, this work represents a meaningful step toward integrating neural network learning into practical robotic navigation. Zhang’s contributions are valuable for researchers and engineers developing next-generation domestic robots, as his algorithm offers a foundation for improving robot autonomy in dynamic environments. His work underscores the ongoing challenge of balancing computational efficiency with real-time adaptability in mobile robotics.