Sani Iyal Abdulkadir

Papers

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About

Sani Iyal Abdulkadir is a robotics researcher whose work focuses on solving the fundamental challenge of indoor path planning. His primary contributions lie in optimizing the classic Dijkstra’s algorithm for robotic navigation, specifically addressing the computational inefficiencies of traditional adjacency matrix storage. In his highly cited 2015 paper (66 citations), Abdulkadir introduced a novel approach using multi-layer dictionaries to replace the adjacency matrix, dramatically reducing storage requirements and enabling more efficient shortest-path calculations in complex indoor environments. This innovation represents a significant practical improvement for real-world robotic systems operating in constrained spaces. His related work on indoor global path planning based on critical cells further refined grid-based navigation, using discretized floor plans to identify essential waypoints. While his second paper has garnered fewer citations (2), it demonstrates his systematic approach to breaking down environments into manageable, equal-sized grids for algorithmic processing. Abdulkadir’s research bridges the gap between classical computer science algorithms and modern robotics applications, offering tangible solutions for autonomous navigation in hospitals, warehouses, and smart buildings. His work remains essential reading for students and engineers developing efficient path-planning systems for mobile robots.