Lotfi Zeghmi
Papers
5
Total Citations
52
H-Index
4
About
Lotfi Zeghmi is a leading researcher in the field of autonomous mobile robotics, with a sharp focus on energy efficiency and intelligent navigation. His work addresses a critical industrial challenge: enabling battery-powered robots, such as Automated Guided Vehicles (AGVs) and autonomous forklifts, to operate for extended periods on a single charge. Zeghmi’s major contributions include pioneering investigations into energy-efficient motion planning, where he has demonstrated how factors like load position and local path planning can significantly reduce power consumption. His 2021 paper on energy-efficient motion for autonomous wheeled mobile robots has garnered 24 citations, establishing a foundational reference in the field. Zeghmi has also advanced localization techniques, proposing a novel Kalman-Particle hybrid filter to improve AGV positioning in complex indoor environments. More recently, he has explored online health-aware energy management for fuel cell hybrid robots and applied machine learning to predict charging queue wait times for autonomous forklift fleets. With over 50 total citations across his key publications, Zeghmi’s research directly impacts the practical deployment of sustainable, long-duration autonomous systems in manufacturing and logistics.
Research Focus
Key Achievements
Top Papers
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