Weigao Mao

Papers

Total Citations

H-Index

About

Weigao Mao is a leading researcher in environmental sensing and robotics, specializing in bioinspired mobile algorithms and artificial olfactory systems for hazardous gas emission tracing. His work addresses critical challenges in identifying unknown leakage sources and gas compositions in outdoor environments, with direct applications in industrial safety and environmental monitoring. Mao’s most cited paper, “Emission source tracing based on bionic algorithm mobile sensors with artificial olfactory system” (2021, 16 citations), pioneers the integration of mobile robots equipped with gas sensors to autonomously trace and locate toxic volatile substance leaks, significantly improving response times to potential explosions or poisoning events. His follow-up study, “Comparison and Improvement of Bioinspired Mobile Algorithms to Trace the Emission Source Based on the Simulation Scenarios” (2022, 2 citations), systematically evaluates and enhances the performance, efficiency, and accuracy of various bioinspired algorithms for source localization. Through these contributions, Mao advances the practical deployment of autonomous robotic systems for real-world hazard detection, offering a scalable, precise solution that reduces human risk. His work is foundational for students and researchers exploring sensor fusion, swarm robotics, and environmental monitoring technologies.