Luqi Wang

Hong Kong University of Science and Technology

Papers

Total Citations

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About

Luqi Wang is a robotics researcher whose work focuses on autonomous exploration, state estimation, and multi-robot coordination in unknown and GPS-denied environments. His most influential contribution, "Exploration with Global Consistency Using Real-Time Re-integration and Active Loop Closure" (2022, 17 citations), addresses a critical limitation in robotic exploration: the assumption of drift-free localization. By developing a systematic framework that integrates real-time re-integration and active loop closure, Wang enables robots to maintain globally consistent maps even under significant odometry drift—a practical necessity for real-world deployment. His earlier work, "CRASH: A Collaborative Aerial-Ground Exploration System Using Hybrid-Frontier Method" (2018, 5 citations), pioneered a novel hybrid-frontier approach that leverages the complementary strengths of UAVs and UGVs for efficient, collaborative exploration. More recently, Wang contributed to "VINS-Multi: A Robust Asynchronous Multi-camera-IMU State Estimator" (2024), enhancing the robustness of visual-inertial odometry for multi-sensor systems. Through these contributions, Wang has advanced the reliability and scalability of autonomous exploration systems, bridging the gap between theoretical algorithms and practical, drift-tolerant robotic navigation.