Edwin Paul Herrera Alarcon
Papers
4
Total Citations
35
H-Index
3
About
Edwin Paul Herrera Alarcon is a robotics researcher whose work bridges autonomous aerial systems and humanoid safety. His primary contributions lie in developing efficient exploration algorithms for Unmanned Aerial Vehicles (UAVs), particularly in object-oriented exploration and operations within GNSS-denied environments. His most cited work, “An Efficient Object-Oriented Exploration Algorithm for Unmanned Aerial Vehicles” (2021, 14 citations), redefines exploration by prioritizing the rapid localization of specific objects over maximizing volumetric coverage—a crucial shift for search-and-rescue and monitoring missions. Building on this, his 2023 framework for autonomous UAV missions in partially unknown, GNSS-denied settings (12 citations) enables low-cost multirotors to execute complex tasks without human intervention, advancing real-world deployment in challenging conditions. Herrera Alarcon also contributes to humanoid robotics with an integrated fall protection and recovery system for two-wheeled humanoids (2020, 6 citations), addressing a critical safety gap. His recent work on learning heuristics via Graph Neural Networks for environment exploration (2023) further showcases his commitment to intelligent, adaptive autonomy. With a growing citation record and a focus on practical, robust solutions, Herrera Alarcon is shaping the future of autonomous robotics in unstructured environments.
Research Focus
Key Achievements
Top Papers
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