Yasir Hussain

Liverpool John Moores University, Nanjing University of Aeronautics and Astronautics

Papers

Total Citations

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About

Yasir Hussain is a leading researcher in autonomous mobile robotics, specializing in path planning and collision avoidance for dynamic environments. His work bridges artificial intelligence and robotics, with a focus on leveraging large language models (LLMs) and deep reinforcement learning to enhance robot navigation. Hussain’s most impactful contribution is his 2025 paper on "Robust mobile robot path planning via LLM-based dynamic waypoint generation," which has already garnered 19 citations, reflecting its immediate influence in the field. He also pioneered a novel approach in his 2024 study, integrating Collision Probability (CP) with the Soft Actor-Critic Lagrangian (SACL-L) framework to enable mobile robots to safely navigate both static and dynamic obstacles. This work, though newer with 2 citations, demonstrates his innovative thinking in ensuring real-time adaptability and safety. Hussain’s research is vital for advancing autonomous systems in applications like warehouse logistics, search-and-rescue, and self-driving vehicles. His achievements highlight a promising trajectory, positioning him as a rising voice in intelligent robotics and AI-driven navigation.