About

Zhiqiang Cao is a prominent robotics researcher whose work spans mobile robot navigation, multi-robot systems, computer vision, and legged robotics. Over two decades of sustained research, Cao has made significant contributions to how autonomous robots perceive, navigate, and cooperate within complex environments. His early foundational work in multi-robot coordination, including formation control and cooperative hunting strategies using distributed local interaction frameworks, established him as a leading voice in swarm and multi-agent robotics, with these papers accumulating nearly 85 citations combined. Cao's research subsequently expanded into bio-inspired approaches, notably his spiking neural network-based target tracking system, and comprehensive reviews of quadruped robot development, reflecting his broad command of embodied intelligence. More recently, Cao has tackled practical sensing and perception challenges, developing cost-effective UWB and LiDAR fusion mapping solutions, robust relative localization methods for infrastructure-free environments, and high-precision calibration frameworks for industrial vision-guided robot systems. His two-stream CNN for robotic grasping further demonstrates his fluency in deep learning applications. Collectively, his portfolio exceeds 450 citations, representing a body of work that meaningfully bridges theoretical robotics and real-world autonomous systems deployment.

Research Focus

Key Achievements

23
H-Index
104
Papers
1,361
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Vision-Based Target-Following Guider for Mobile Robot
63 citations · 2019
📈 Most Prolific Year: 2021 (13 Papers)
🤝 Key Collaborators: 165
🏛 Institutions: Shandong Institute of Automation, Southwest University of Science and Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Singapore University of Technology and Design, Institute of Automation

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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