Papers
33
Total Citations
529
H-Index
14
About
Wenhao Luo is a robotics researcher whose work sits at the intersection of multi-robot systems, autonomous coordination, and environmental sensing. His research primarily focuses on multi-robot coverage control, adaptive sampling, collision avoidance, and connectivity maintenance — areas critical to deploying reliable robot teams in real-world, uncertain environments. Luo's most influential contribution, "Adaptive Sampling and Online Learning in Multi-Robot Sensor Coverage with Mixture of Gaussian Processes" (2018, 90 citations), introduced a principled framework for robots to collaboratively model unknown environments in real time, moving beyond the restrictive assumption that environmental distributions are known in advance. This work has become a foundational reference in robotic environmental monitoring. He has further advanced the field through probabilistic safety guarantees for collision avoidance under uncertainty, k-connectivity maintenance for fault-tolerant teams, and Voronoi-based coverage with connectivity constraints — each garnering over 30 citations. Luo's portfolio also reflects a breadth of practical concerns, from heterogeneous robot coordination and swarm self-healing to safe autonomous vehicle merging using Control Barrier Functions. Collectively, his publications demonstrate a consistent commitment to making multi-robot systems both theoretically rigorous and deployable under realistic conditions, earning him recognition as a thoughtful contributor to modern autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 2Minimum k-Connectivity Maintenance for Robust Multi-Robot Systems43 citations · 2019
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- 8Trust-Aware Behavior Reflection for Robot Swarm Self-Healing19 citations · 2019
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