Papers
27
Total Citations
648
H-Index
13
About
Hongliang Guo is a versatile robotics and intelligent systems researcher whose work spans swarm robotics, bio-inspired computing, human-robot interaction, and autonomous navigation. He is perhaps best known for pioneering the application of gene regulatory networks (GRNs) and morphogenetic principles to multi-robot systems, enabling swarms of robots to self-organize into complex, adaptive formations without relying on predefined patterns — a breakthrough particularly valuable for dynamic, unstructured environments. This foundational body of work, accumulated across multiple highly cited papers from 2009 to 2012, has collectively garnered hundreds of citations and established Guo as a leading voice in bio-inspired swarm intelligence. Beyond swarm robotics, Guo has made significant contributions to human-exoskeleton interaction through hierarchical learning control frameworks (72 citations), demonstrating his ability to bridge theoretical biological inspiration with practical rehabilitation and assistive technologies. His 2022 work on E-LOAM advanced LiDAR-based odometry and mapping for autonomous systems operating in challenging unstructured terrains. Additional contributions to distributed reinforcement learning and neural network-based path planning further illustrate the remarkable breadth of his research portfolio. With over 470 cumulative citations across his most recognized works, Guo's scholarship continues to meaningfully shape the fields of autonomous robotics, swarm intelligence, and intelligent control systems.
Research Focus
Key Achievements
Top Papers
- 1Hierarchical learning control with physical human-exoskeleton interaction72 citations · 2017
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- 8Distributed Reinforcement Learning for Coordinate Multi-Robot Foraging31 citations · 2010
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