Cunlong Fu

Papers

1

Total Citations

3

H-Index

1

About

Cunlong Fu is a researcher focused on advancing autonomous mobile robotics, with a particular emphasis on real-time navigation and obstacle avoidance systems. His most-cited work, "Mapping and Autonomous Obstacle Avoidance of Mobile Robot Based on ROS Platform" (2023, 3 citations), addresses a critical challenge in robotics: enabling robots to perceive their environment and navigate safely without human intervention. By leveraging the Robot Operating System (ROS), Fu’s research integrates mapping algorithms with autonomous decision-making, contributing to the broader goal of creating more intelligent and adaptable robots for applications ranging from industrial automation to service robotics. While his citation count is still growing, his work represents a practical step toward improving robot autonomy in dynamic environments. Fu’s contributions are particularly relevant as robotics becomes increasingly embedded in everyday life, from warehouse logistics to home assistance. His research underscores the importance of robust software platforms like ROS in bridging the gap between theoretical algorithms and real-world deployment, making him a promising voice in the field of mobile robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Mapping and Autonomous Obstacle Avoidance of Mobile Robot Based on ROS Platform
3 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago