Jingwen Fan

Papers

Total Citations

H-Index

About

Jingwen Fan is a robotics researcher whose work centers on autonomous navigation, path planning, and simultaneous localization and mapping (SLAM) for mobile robots. Her most impactful contribution, "PP-ST: An Indoor Mobile Robot Path Tracking Algorithm" (2023, 9 citations), addresses critical limitations in the Pure Pursuit algorithm, offering a solution that balances path approach speed and cornering stability—a practical advance for real-world indoor navigation. Fan further pushes the boundaries of perception with "A Multi-Sensor Deep Fusion SLAM Algorithm Based on TSDF Map" (2024, 4 citations), where she tackles the noise susceptibility of traditional 2D occupancy grid maps by integrating deep sensor fusion with Truncated Signed Distance Function (TSDF) mapping, enhancing backend optimization and data utilization. Her work on the "Improved A*-DWA fusion path planning algorithm with ideal path area constraints" (2023, 2 citations) combines global optimal pathfinding with real-time obstacle avoidance, a common yet challenging problem in mobile robotics. Collectively, Fan's research demonstrates a systematic effort to improve both the accuracy and robustness of robot navigation systems, making her a rising contributor to the field of autonomous mobile robotics.