Papers

3

Total Citations

22

H-Index

3

About

Yukun Chen is a leading researcher in autonomous mobile robotics, with a focused expertise in path planning algorithms for intelligent systems operating in complex environments. Chen's major contributions lie in advancing optimization techniques for robot navigation, particularly through the integration of bio-inspired and reinforcement learning methods. Their seminal 2018 review on representation, models, algorithms, and constraints for mobile robot path planning has garnered 10 citations, establishing a foundational framework for the field. Chen further innovated by developing an improved reinforcement learning optimization approach for path planning (2019, 6 citations), addressing the limitations of constant parameter settings in adaptive functions. Additionally, their work on an enhanced ant colony optimization algorithm (2020, 6 citations) demonstrated how bionic algorithms can be synergized with Q-learning to solve complex navigation problems. These contributions collectively advance the efficiency and adaptability of autonomous mobile robots, making Chen's research essential reading for students and researchers working at the intersection of artificial intelligence, robotics, and optimization algorithms.

Research Focus

Key Achievements

3
H-Index
3
Papers
22
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
A Review of Representation, Model, Algorithm and Constraints for Mobile Robot Path Planning
10 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: China Academy of Launch Vehicle Technology, Universidad del Noreste, Northeastern University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago