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About

Maram Ali is a robotics researcher whose work centers on autonomous navigation, swarm robotics, and dynamic obstacle avoidance for mobile systems. Her most significant contribution is a novel framework that integrates Probabilistic Roadmaps (PRM) with Pure Pursuit algorithms for differential drive robots, enabling efficient path planning in complex environments—a paper that has already garnered 7 citations since 2025. She has also advanced swarm robotics by applying random-walk search algorithms and cluster-based distribution factors for area exploration, demonstrating how nature-inspired methods can coordinate multiple robots effectively. Her research on dynamic obstacle avoidance introduces the concept of inertia into obstacle movement, moving beyond random trajectories to create more realistic and robust navigation in unpredictable settings. With a cumulative citation count of 22 across her key publications, Ali’s work is gaining traction for its practical improvements to real-world robotic autonomy. Her comparative analysis of path-planning algorithms further showcases her commitment to optimizing performance in dynamic environments, making her a rising voice in the field of mobile robotics and autonomous systems.