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About

Leonardo Garrido’s research lies at the intersection of cooperative robotics, world representation, and humanoid locomotion. His most influential work introduces a novel hexagonal grid map as an alternative to traditional quadrangular grids for cooperative robot exploration, demonstrating improved efficiency in unknown environments. This foundational idea, published in 2007, has garnered 13 citations and remains a key reference in multi-robot exploration strategies. Garrido also made significant contributions to humanoid robotics with a decoupled closed-form solution for the lower limb kinematics of the NAO robot, enabling omnidirectional and analytically precise motion control—a paper cited 8 times for its practical utility. His work on automated generation of Central Pattern Generator (CPG)-based locomotion further advanced adaptive walking in humanoids. Across his publications, Garrido’s research consistently emphasizes robust, scalable solutions for dynamic and uncertain worlds, with cumulative citations reflecting sustained interest from the robotics community. His achievements highlight a career dedicated to bridging theoretical kinematics and practical exploration algorithms, offering valuable tools for both simulated and real-world robotic systems.