Papers
6
Total Citations
75
H-Index
5
About
Chunbo Luo is a leading researcher in robotics, multi-agent systems, and intelligent control, whose work bridges bio-inspired computation, cooperative sensing, and fault diagnosis. His most cited paper, “Using Social Behavior of Beetles to Establish a Computational Model for Operational Management” (28 citations), introduces a novel beetle-inspired algorithm for manipulator tracking control, demonstrating how simple olfactory-based foraging strategies can solve complex operational tasks. Luo has made significant contributions to robust visual odometry for dynamic environments, as seen in “DynPL-SVO: A Robust Stereo Visual Odometry for Dynamic Scenes” (19 citations), which addresses the challenge of feature tracking amidst moving pedestrians and vehicles. He also advanced cooperative robotics with a communication model that decouples path planning from connectivity optimization (9 citations), enabling more efficient multi-robot coordination. His work on a sensor self-aware distributed consensus filter (9 citations) improves simultaneous localization and tracking, while his recent “DRL-GCNet” (2025, 8 citations) applies deep reinforcement learning and graph convolutional networks to diagnose harmonic drive faults in industrial robots. With additional research on network coding for relay channels, Luo’s interdisciplinary approach—spanning from beetle behavior to deep learning—has earned over 75 total citations, establishing him as a versatile innovator in autonomous systems and intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2DynPL-SVO: A Robust Stereo Visual Odometry for Dynamic Scenes19 citations · 2024
- 3
- 4
- 5
- 6Multiple‐source multiple‐destinations relay channels with network coding2 citations · 2013