Zongmao Cheng
Papers
2
Total Citations
22
H-Index
2
About
Zongmao Cheng is a researcher focused on the intersection of robotics, logistics, and intelligent scheduling, with a particular emphasis on autonomous charging strategies for mobile robots. His work addresses a critical bottleneck in warehouse automation: keeping robots operational without human intervention. Cheng’s most cited paper, “Research on robot charging strategy based on the scheduling algorithm of minimum encounter time” (2019, 13 citations), pioneers the use of mobile chargers that dynamically route to robots mid-task, minimizing downtime. He extended this line of inquiry in “Research on online scheduling and charging strategy of robots based on shortest path algorithm” (2021, 9 citations), integrating real-time path optimization to further boost efficiency. By modeling charging as a scheduling problem rather than a fixed-pile solution, Cheng has contributed foundational algorithms that reduce operational costs and improve throughput in automated storage systems. His work is particularly notable for its practical orientation, directly addressing real-world constraints like task continuity and energy limits. For students and researchers in robotics and logistics, Cheng’s research offers a clear, applied framework for designing resilient, self-sustaining robot fleets—a key step toward fully autonomous warehouses.
Research Focus
Key Achievements
Top Papers
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