Luciano Buonocore

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About

Luciano Buonocore is a robotics researcher specializing in autonomous navigation, sensor fusion, and robotic construction. His work focuses on enabling robots to perceive, map, and interact with indoor environments using low-cost hardware and intelligent algorithms. In his most cited paper, "FastSLAM filter implementation for indoor autonomous robot" (2016, 9 citations), Buonocore developed a particle filter-based approach for simultaneous localization and mapping (SLAM) that efficiently handles unknown data associations to extract structural features like walls and doors. This work addresses a critical challenge in indoor robotics: robust mapping with limited computational resources. His earlier research on "Sensor Data Fusion Algorithm for Indoor Environment Mapping Using Low-Cost Sensors" (2013, 5 citations) further advanced accessible mapping techniques by integrating data from affordable sensors. Demonstrating versatility, Buonocore also explored robotic construction in "A Stochastic Learning Approach for Construction of Brick Structures with a Ground Robot" (2017, 5 citations), where he applied reinforcement learning to teach a mobile robot to autonomously assemble 3D brick structures from user designs. This interdisciplinary work bridges perception, planning, and manipulation, showcasing his contributions to both theoretical algorithms and practical robotic systems.