Xiaowu He
Papers
1
Total Citations
7
H-Index
1
About
Xiaowu He is a leading researcher in edge-assisted multi-agent systems and real-time visual SLAM (Simultaneous Localization and Mapping), with a focus on scalable, collaborative architectures for mobile robotics. His most-cited work, “Scaling Up Edge-Assisted Real-Time Collaborative Visual SLAM Applications” (2023, 7 citations), addresses critical scalability challenges in multi-agent visual SLAM—a foundational technology for search-and-rescue, inventory automation, and industrial inspection. He proposed a central edge node to manage global maps and task scheduling, enabling efficient coordination among agents. However, his key contribution lies in identifying and mitigating the computational bottlenecks that arise as agent numbers grow, paving the way for practical, large-scale deployments. He’s recognized for bridging the gap between theoretical SLAM frameworks and real-world edge computing constraints, a vital step for autonomous systems operating in dynamic environments. His work has garnered attention for its direct impact on latency-sensitive applications, and he continues to advance the field by exploring resource-aware task allocation and distributed map fusion. For students and researchers, He’s work exemplifies how edge intelligence can unlock the full potential of collaborative robotics.
Research Focus
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Top Papers
- 1