Sami Sellami

Papers

Total Citations

H-Index

About

Sami Sellami is a robotics researcher specializing in autonomous systems, computer vision, and intelligent control. His work bridges perception and action, with a focus on enabling robots to operate reliably in dynamic, unstructured environments. His most cited paper (24 citations) presents a complete pipeline for autonomous visual detection, tracking, and landing of an AR.Drone 2.0 quadcopter on a moving ground vehicle, demonstrating real-time color-based tracking and closed-loop control—a foundational contribution to cooperative UAV-UGV systems. Sellami also addresses a critical industrial challenge in his 2021 work on deep learning-based robot positioning error compensation (5 citations), where he models and corrects non-geometric calibration errors to improve absolute accuracy beyond typical repeatability. Additionally, his 2020 paper on swing-up control of the Pendubot using virtual holonomic constraints within the Robot Operating System (ROS) framework (2 citations) showcases his expertise in nonlinear control and underactuated systems. Across these contributions, Sellami demonstrates a consistent ability to integrate perception, learning, and control for practical robotic applications, from aerial-ground coordination to precision manufacturing and benchmark control problems.