Zhou Zheng

Shandong University of Science and Technology

Papers

Total Citations

H-Index

About

Zhou Zheng is a rising researcher in robotics and autonomous navigation, with a primary focus on path planning for mobile robots in complex, unknown environments. His work bridges reinforcement learning and multi-agent systems to enhance robotic adaptability and safety. His most cited paper, "A DRL-based path planning method for wheeled wheeled mobile robots in unknown environments" (2024), has already garnered 15 citations, demonstrating growing interest in his deep reinforcement learning approach for real-time obstacle avoidance. In earlier work, "An Adaptive Local Path Planning Algorithm for Multi-robot Systems" (2022), he proposed an improved Dynamic Window Approach (DWA) that integrates sensor-based cost functions into the evaluation metric, enabling more robust path selection for rescue robots operating in harsh, unpredictable settings. This contribution addresses critical challenges in multi-robot coordination and hazard response. Zheng’s research is notable for its practical orientation—combining theoretical advances with sensor-driven, real-world applicability. As his citation count rises, he is establishing himself as a key voice in intelligent robotic navigation, with potential for significant impact on autonomous systems in disaster response and industrial automation.