Yutian Mao

Beijing Institute of Technology, Shandong Institute of Automation

Papers

Total Citations

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About

Yutian Mao is a researcher specializing in multi-robot systems, autonomous navigation, and cooperative control, with a focus on solving fundamental challenges in swarm robotics and indoor automation. Their most cited work, "Combined complete coverage path planning for autonomous mobile robot in indoor environment" (2009, 15 citations), introduces a novel hybrid strategy that merges template-based and heuristic path planning to achieve efficient and thorough area coverage—a critical problem for service robots and floor-cleaning automation. Mao further advances the field with influential contributions to multi-agent coordination, including "Flocking of multi-robot systems with connectivity maintenance on directed graphs" (2014, 7 citations), which presents bounded control protocols ensuring stable swarm cohesion despite directed communication constraints. Complementing this, "Formation control based on flocking algorithm in multi-agent system" (2010, 7 citations) adapts Reynolds’ classic "boids" model to nonholonomic robots, bridging theoretical flocking with practical formation control. Collectively, Mao’s work addresses key gaps in coverage completeness, connectivity preservation, and decentralized coordination, offering scalable solutions for autonomous exploration and cooperative robotics. Their research continues to influence applications in search-and-rescue, environmental monitoring, and intelligent logistics.