Chen‐Chien Hsu
Papers
43
Total Citations
398
H-Index
10
About
Chen-Chien Hsu is a leading researcher in intelligent robotics, with a primary focus on mobile robot navigation, path planning, and human-robot interaction. His most impactful work centers on applying deep reinforcement learning to enable robots to navigate safely and efficiently in crowded, dynamic environments—a critical challenge for autonomous systems. His 2024 comprehensive review on this topic has already garnered 38 citations, underscoring its significance as a foundational resource in the field. Hsu has also made substantial contributions to multi-robot coordination, developing improved D* Lite and ant colony optimization algorithms that enhance computational efficiency and path quality. Beyond navigation, his innovative work on vision-based learning from demonstration allows robotic arms to acquire new tasks intuitively, reducing the need for manual reprogramming. Notably, Hsu has explored the intersection of robotics and cultural heritage, creating a Chinese calligraphy-writing robot that learns stroke trajectories through deep learning and hypothesis generation. With over 200 total citations and a portfolio of high-impact papers spanning from 2011 to 2024, Chen-Chien Hsu is recognized for advancing both the theoretical foundations and practical applications of autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Path Planning for Mobile Robots Based on Improved Ant Colony Optimization24 citations · 2013
- 5Multi-robot path planning based on improved D* Lite Algorithm20 citations · 2015
- 6
- 7Vision-Based Learning from Demonstration System for Robot Arms15 citations · 2022
- 8
- 9
- 10