Max Robotics — Global Service Robot Directory + US Certification

About

Jinge Cao’s research lies at the intersection of multi-robot systems, swarm intelligence, and biomedical nanorobotics, with a focus on developing efficient task allocation and cooperative control strategies. Her major contributions include a market-based task allocation algorithm that optimizes multi-robot coordination by incorporating task intensity, distance fitness, and time urgency—a framework that has garnered 12 citations for its practical improvements in robot team efficiency. She also advanced the field of nanomedicine by proposing an Improved Bacterial Foraging Optimization Algorithm (IBFOA) with cooperative learning, enabling nanorobots to collaboratively locate and eradicate cancer cells in blood vessels (7 citations). Additionally, Cao introduced a dynamic adjustment auction algorithm for multi-robot target hunting, enhancing coordination and adaptability in pursuit tasks (5 citations). Her work bridges theoretical optimization with real-world applications, from autonomous robot teams to targeted cancer therapy, demonstrating significant impact in both robotics and biomedical engineering.