Gao Ping-an

Central South University, Xiangtan University

Papers

Total Citations

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About

Gao Ping-an is a pioneering researcher in multi-robot systems, with a primary focus on decentralized task allocation and evolutionary computation. His work addresses the critical challenge of coordinating teams of mobile robots to efficiently explore unknown environments. In his most cited paper (2009, 16 citations), Gao introduced an evolutionary computation approach to decentralized multi-robot task allocation, minimizing the maximum path cost among robots—a significant improvement over traditional auction-based methods. His earlier foundational study (2006, 11 citations) laid the groundwork for multi-robot exploration task allocation, establishing key principles for balancing workload and communication constraints. Gao's contributions have directly influenced the development of scalable, robust algorithms for real-world applications such as search-and-rescue missions, planetary exploration, and warehouse automation. By combining evolutionary strategies with decentralized decision-making, he has advanced the field's understanding of how to achieve near-optimal performance without centralized control. His work remains a vital reference for researchers designing autonomous robot teams capable of adapting to dynamic environments.