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About

Mohand Lagha is a researcher specializing in autonomous systems, unmanned aerial vehicles (UAVs), and intelligent control systems. His work has made meaningful contributions to the fields of swarm robotics, search and rescue operations, and human-robot interaction, earning him recognition within the robotics and autonomous systems community. Lagha's most impactful contribution, "Quadrotors UAVs Swarming Control Under Leader-Followers Formation" (2018, 24 citations), introduced a novel trajectory-tracking scheme for coordinated multi-UAV systems, addressing key challenges in reliability and mission efficiency. This foundational work was complemented by his research on autonomous search and rescue systems, with two dedicated studies (2020 and 2021, 14 and 17 citations respectively) advancing the deployment of quadrotor UAVs in critical real-world operations such as fire protection and disaster response. More recently, Lagha has expanded his research horizon, exploring the integration of large language models for intuitive UAV control (2025) and applying reinforcement learning to fractional-order PID controllers for upper limb rehabilitation robotics (2023). These contributions reflect a researcher continuously bridging emerging AI techniques with practical engineering challenges, making his work relevant across autonomous systems, healthcare robotics, and human-centered design.