Papers

10

Total Citations

459

H-Index

8

About

Yu-Chu Tian is a leading researcher at the intersection of robotics, edge computing, and cyber-physical systems (CPS), with a career-spanning focus on intelligent automation and resilient system design. His most influential work centers on robot path planning, where he pioneered enhanced simulated annealing approaches to enable mobile robots to navigate dynamic environments with both static and moving obstacles—a foundational contribution that has garnered over 144 citations. More recently, Tian has driven the integration of cloud and edge computing into robotic workflows, addressing critical challenges in smart factories and agricultural CPS. His 2019 paper on multi-objective resource allocation for edge cloud-based robotic workflows (129 citations) and his work on robotic edge resource allocation have shaped how distributed computing enhances real-time robotic operations. Tian has also advanced system resilience through deep reinforcement learning, proposing dynamic task allocation and anti-saturation control strategies to counter actuator attacks and mechanical disruptions. His forward-looking concepts, including "Mobility-as-a-Resilience Service" and "UAV-as-a-Service," push the boundaries of the Internet of Robotic Things. With over 400 total citations across his top publications, Tian’s research is essential reading for anyone exploring robust, intelligent, and resource-aware robotic systems.

Research Focus

Key Achievements

8
H-Index
10
Papers
459
Total Citations
46
Avg Citations/Paper
🏆 Most Cited Paper
Dynamic robot path planning using an enhanced simulated annealing approach
144 citations · 2013
📈 Most Prolific Year: 2008 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Queensland University of Technology, Zhejiang University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago