Zaisheng Pan

Zhejiang University, Zhejiang University of Technology

Papers

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About

Zaisheng Pan is a robotics researcher whose work lies at the intersection of deep reinforcement learning, multi-robot systems, and autonomous navigation. His most impactful contribution, "Mapless Collaborative Navigation for a Multi-Robot System Based on the Deep Reinforcement Learning" (2019, 34 citations), addresses a critical challenge in robotics: enabling teams of robots to navigate unknown environments without pre-existing maps. By leveraging deep reinforcement learning, Pan demonstrated how multi-robot systems can achieve higher efficiency and fault tolerance—key advantages for search, rescue, and escort missions. In "Ensemble Bootstrapped Deep Deterministic Policy Gradient for Vision-Based Robotic Grasping" (2021, 19 citations), Pan tackled the longstanding problem of generalizable robotic manipulation, proposing a method that allows manipulators to grasp unfamiliar objects without relying on prior knowledge—a significant step toward human-like dexterity in industrial automation. His additional work on hierarchical person re-identification for robotic navigation and drowning detection algorithms for intelligent lifebuoys showcases a practical, application-driven approach. With a growing citation footprint and contributions spanning collaborative autonomy, manipulation, and safety-critical systems, Pan is establishing himself as a versatile researcher advancing the frontier of intelligent, real-world robotics.