Kao-Ting Hung
Papers
1
Total Citations
18
H-Index
1
About
Kao-Ting Hung is a researcher in robotics and computational intelligence, with a primary focus on autonomous navigation and multi-objective optimization. His most cited work, "A comparative study of smooth path planning for a mobile robot by evolutionary multi-objective optimization" (2007, 18 citations), introduces a novel framework for generating smooth, collision-free paths in static environments. By modeling path cost as a combination of path length and penetration depth to polygonal obstacles, Hung demonstrates how evolutionary algorithms can effectively balance competing objectives—efficiency and safety. This contribution is particularly valuable for mobile robotics, where smooth trajectories are critical for energy conservation and mechanical stability. Hung’s approach provides a systematic method for optimizing path quality without sacrificing computational feasibility. While his citation count reflects a focused but impactful body of work, his research offers practical insights for students and engineers developing autonomous systems. Hung’s work stands as a clear example of how evolutionary multi-objective optimization can address real-world robotic challenges, making his contributions a useful reference for those exploring path planning in constrained environments.
Research Focus
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Top Papers
- 1