Sidi Mohamed Benslimane

École Nationale Supérieure d'Informatique

Papers

Total Citations

H-Index

About

Sidi Mohamed Benslimane is a researcher at the forefront of swarm robotics and human-robot interaction, with a focus on integrating machine learning to enhance collective robotic systems. His key research areas include swarm motion prediction, human-swarm interaction (HSI), and ensemble learning methods. Benslimane’s major contribution lies in pioneering data-driven approaches for swarm robotics, particularly through his work on a soft sensor that uses ensemble learning to predict swarm motion speed—a relatively unexplored area critical for sustaining pattern formation and other collective tasks. This work, published in 2021, has garnered 20 citations, demonstrating its growing influence in the field. Additionally, his 2022 bibliometric analysis of human-swarm interactions, though newer with 2 citations, provides a foundational mapping of this interdisciplinary domain, blending biology, robotics, computer science, and psychology. Benslimane’s research not only advances technical capabilities in swarm coordination but also bridges gaps in understanding how humans can effectively interact with autonomous swarms, making his contributions valuable for both theoretical and applied robotics.