Papers

1

Total Citations

7

H-Index

1

About

Chao Ji is an emerging researcher specializing in robotics and autonomous systems, with a particular focus on bipedal humanoid robot locomotion and intelligent control. His work sits at the intersection of machine learning, multimodal perception, and robotic motion planning, addressing one of the most technically demanding challenges in modern robotics: enabling humanoid robots to walk adaptively across varied and unpredictable terrain. His most notable contribution, "Learning-based locomotion control fusing multimodal perception for a bipedal humanoid robot" (2025), has already garnered 7 citations within a short period of publication, signaling strong early interest from both academic and industrial communities. This work advances beyond traditional model-based control frameworks by integrating learning-driven approaches with rich sensory fusion, offering a more robust and scalable pathway toward practical humanoid deployment. Ji's research directly responds to growing demand from robotics industries seeking reliable, real-world locomotion solutions. As humanoid robotics rapidly accelerates in prominence, Ji's contributions position him as a promising voice in shaping the next generation of intelligent, adaptive robotic systems capable of operating effectively in complex human environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Learning-based locomotion control fusing multimodal perception for a bipedal humanoid robot
7 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Science and Technology of China

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago