Jiaxu Wu
Papers
6
Total Citations
32
H-Index
3
About
Jiaxu Wu is a leading researcher in autonomous mobile robot navigation, with a focus on safe and socially aware human-robot interaction in crowded environments. His work addresses critical challenges in pedestrian trajectory prediction, risk-sensitive navigation, and the detection of distracted pedestrians. Wu’s most cited paper, “Pedestrian trajectory prediction using BiRNN encoder–decoder framework” (2019, 14 citations), introduced a novel deep learning approach for forecasting human movement, enabling robots to anticipate and avoid collisions. He further advanced robot safety with “Smartphone Zombie Detection From LiDAR Point Cloud for Mobile Robot Safety” (2020, 12 citations), which identifies texting pedestrians—a common but hazardous behavior. His recent contributions include “Risk-Sensitive Mobile Robot Navigation in Crowded Environment via Offline Reinforcement Learning” (2023, 3 citations), which bridges the sim-to-real gap for robust navigation. Wu’s innovative use of reinforcement learning and diversity-aware crowd models, as seen in his 2025 works, pushes the boundaries of autonomous navigation, making robots more perceptive and considerate of human unpredictability. His research has garnered growing attention, with citations spanning from foundational trajectory prediction to cutting-edge safety systems.
Research Focus
Key Achievements
Top Papers
- 1Pedestrian trajectory prediction using BiRNN encoder–decoder framework14 citations · 2019
- 2Smartphone Zombie Detection From LiDAR Point Cloud for Mobile Robot Safety12 citations · 2020
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