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About

Iker Lluvia is a robotics and automation researcher whose work spans autonomous navigation, simultaneous localization and mapping (SLAM), mobile manipulation, and industrial wireless communications. His most influential contribution, a comprehensive survey on active mapping and robot exploration (2021, 155 citations), has become a key reference for researchers entering the field, synthesizing decades of progress in autonomous robotic navigation and environmental mapping. Lluvia has also made significant strides in applying deep reinforcement learning to mobile manipulation, developing positioning policies that enable robots to intelligently coordinate base movement with arm reachability constraints — work that bridges theoretical machine learning with practical robotics deployment. Beyond laboratory settings, Lluvia has demonstrated a strong commitment to real-world applications. His involvement in the EU H2020-funded GreenPatrol project produced multiple publications exploring autonomous robot navigation and GNSS-based precise positioning for pest detection in commercial greenhouses, reflecting an ability to translate research into agricultural innovation. His earlier work on redundancy in industrial wireless communications addressed reliability challenges critical to Industry 4.0 adoption. Rounding out his portfolio, Lluvia has explored human-robot interaction through service robots in industrial environments. Collectively, his research reflects a versatile, application-driven approach to making autonomous robotic systems smarter, more reliable, and more deployable across diverse real-world domains.