Nicolás Hormazábal

Papers

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About

Nicolás Hormazábal is a leading researcher in artificial intelligence and robotics, with a primary focus on pathfinding algorithms for autonomous navigation. His most influential work, "Fast and Almost Optimal Any-Angle Pathfinding Using the 2k Neighborhoods" (2021, 8 citations), tackles the critical challenge of efficient, smooth robot movement on grid-based maps. Hormazábal’s key contribution lies in demonstrating that subgoal graphs—a pre-processing technique originally designed for standard 8-connected grids—can be adapted to the more complex 2k neighborhood model. This innovation enables near-optimal any-angle paths with dramatically reduced computational overhead, bridging the gap between speed and accuracy in path planning. His work has direct applications in autonomous robot navigation, video game AI, and logistics, where real-time decision-making is essential. By advancing the theoretical foundations of grid-based pathfinding while maintaining practical efficiency, Hormazábal has established himself as a rising figure in algorithmic robotics. His research continues to influence both academic studies and industry implementations, offering scalable solutions for complex navigation problems in dynamic environments.