Papers
6
Total Citations
49
H-Index
4
About
Hao Luan is a robotics and computational neuroscience researcher whose work bridges autonomous systems, bio-inspired perception, and multi-robot coordination. His most significant contributions lie in autonomous mobile manipulation, where he has developed sophisticated frameworks for robotic trolley collection—systems designed to reduce human labor and enhance hygiene in public spaces. His 2022 paper on progressive perception combined with nonlinear model predictive control, garnering 20 citations, established a formal algorithmic foundation that previous solutions had lacked, advancing both planning rigor and real-world applicability. Building on this, his 2023 work extended the paradigm to collaborative multi-robot transportation, addressing the longstanding challenge of coordinating nonholonomic robots in dynamic environments. Luan also draws inspiration from biological neural systems, with notable research modeling looming-sensitive neurons found in crabs to develop spatial localization networks applicable to collision detection—work that has attracted 13 citations. His exploration of human orientation estimation under partial observation further reflects his commitment to enabling robots to interpret human intent reliably. Early work on swarm modeling with covert leaders demonstrates a longstanding interest in emergent collective behavior. Across his career, Luan's research consistently targets the gap between theoretical robotics and deployable, perception-driven autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Human Orientation Estimation Under Partial Observation4 citations · 2024
- 5Modeling and Analyzing Large Swarms with Covert Leaders3 citations · 2013
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