Zhu Qing

East China University of Science and Technology

Papers

Total Citations

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About

Zhu Qing’s research lies at the intersection of bio-inspired robotics, cognitive navigation, and autonomous systems. His most influential work centers on applying Ant Colony Optimization (ACO) to path planning for mobile robots operating in complex, dynamic environments. In his landmark 2005 paper, which has garnered 14 citations, Zhu introduced a predictive ant algorithm that mimics the food-hunting behavior of ant colonies to enable robots to find global optimal paths while avoiding dynamic obstacles in unfamiliar settings. This work was further refined in a 2006 study (7 citations), where he proposed a rolling-planning ant algorithm that maps target nodes to the robot’s visible horizon, allowing two cooperating ant groups to efficiently navigate unknown terrains. Beyond robotics, Zhu has explored cognitive map models inspired by rodent spatial exploration, as seen in his 2013 paper (8 citations), which bridges biological navigation strategies and goal-oriented mental exploration. His contributions have advanced real-time, adaptive path planning in robotics, offering practical solutions for autonomous vehicles and search-and-rescue systems. With a focused yet impactful body of work, Zhu Qing continues to inspire researchers in swarm intelligence and bio-robotic navigation.