Jiaping Cao

Papers

1

Total Citations

35

H-Index

1

About

Jiaping Cao is a researcher specializing in mobile robotics, multi-sensor fusion, and intelligent navigation systems. Their most-cited work introduces a novel map construction and path planning method for mobile robots operating in unknown environments, leveraging extended Kalman filters (EKF) to fuse ambient sensor data for enhanced environmental perception and obstacle avoidance. This contribution, published in 2022 and garnering 35 citations, addresses a critical challenge in autonomous vehicle navigation by improving both mapping accuracy and real-time path efficiency. Cao’s research bridges theoretical control algorithms with practical robotic applications, offering scalable solutions for intelligent transportation and industrial automation. By integrating multi-sensor information fusion with path planning, their work has influenced subsequent studies in autonomous systems, particularly in dynamic and unstructured settings. With a growing citation impact, Jiaping Cao continues to advance the field of mobile robotics, focusing on robust, sensor-driven decision-making frameworks that enable safer and more reliable autonomous navigation.

Research Focus

Key Achievements

1
H-Index
1
Papers
35
Total Citations
35
Avg Citations/Paper
🏆 Most Cited Paper
Map Construction and Path Planning Method for a Mobile Robot Based on Multi-Sensor Information Fusion
35 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago