Tarik Jarou

Papers

Total Citations

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About

Tarik Jarou is a researcher focused on advancing autonomous mobile robotics, with key contributions in path planning, trajectory optimization, and machine learning for navigation. His work addresses fundamental challenges in enabling robots to operate efficiently and safely in complex environments. Notably, his 2022 paper on a novel sampling strategy for mobile robot path planning algorithms—enhancing the performance of RRT and RRT*—has garnered 8 citations, reflecting its impact on solving high-dimensional planning problems. Jarou further explores the integration of supervised learning for autonomous navigation, as seen in his 2023 work, and systematically identifies constraints in trajectory planning for autonomous robots in his 2025 study. His research bridges theoretical algorithm development with practical implementation, offering insights that are valuable for both students and practitioners in robotics. By tackling issues like real-time decision-making and environmental adaptability, Jarou’s contributions help push the boundaries of what autonomous systems can achieve, making his work a key reference for those exploring next-generation navigation technologies.