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About

Weigang Pan is a robotics researcher whose work centers on intelligent navigation, path planning, and robust control for mobile robots operating in challenging environments. His primary contributions lie in developing bio-inspired and adaptive algorithms to solve real-world robotic mobility problems. Notably, his 2022 paper on a "reformative bat algorithm" for mobile robot path planning, which applies the Doppler effect to enhance frequency updates, has garnered 9 citations, marking a significant contribution to heuristic optimization in robotics. Pan has also advanced the field of tracking control, addressing the critical issue of slipping and skidding in car-like mobile robots through an event-triggered extended state observer, a work that has earned 5 citations. His research extends to practical applications, including enhancing navigation accuracy for guidance line drawing robots using dual-antenna GNSS and MEMS IMU, as well as developing robust obstacle avoidance strategies for unmanned delivery robots using sequential quadratic programming. Through these works, Pan demonstrates a clear focus on bridging theoretical control methods with deployable robotic systems, making his research highly relevant for students and engineers working on autonomous ground vehicles and field robotics.