Qiaoliang Mo

Guangxi University of Science and Technology

Papers

Total Citations

H-Index

About

Qiaoliang Mo is a researcher specializing in mobile robotics and intelligent path planning, with a particular focus on navigation in dynamic environments. His most-cited work, "A Mobile Robot Path Planning Scheme for Dynamic Environments" (2020), introduces a novel four-direction search method for obstacle avoidance, integrating neural network-based modeling of obstacle collision energy. This contribution addresses the critical challenge of real-time navigation where obstacles are not static, offering a robust framework for adaptive robot movement. By testing different invariant step lengths in static environments, Mo provides practical insights into optimizing path efficiency. While his citation count is currently modest at 3, the foundational nature of this work holds promise for future impact in autonomous systems and robotics. Mo’s research bridges theoretical modeling and applied robotics, making it valuable for students and engineers developing safer, more responsive mobile robots. His work exemplifies the ongoing effort to enhance robot autonomy in unpredictable settings, a key area in modern robotics research.