Papot Jaroenapibal
Papers
1
Total Citations
27
H-Index
1
About
Papot Jaroenapibal is a researcher specializing in robotics, optimization algorithms, and multiobjective trajectory planning. His work focuses on developing advanced computational methods to enhance robotic motion efficiency, particularly for six-degree-of-freedom (6D) robots. His most-cited paper, "Self-adaptive MRPBIL-DE for 6D robot multiobjective trajectory planning" (2019), with 27 citations, introduces a novel self-adaptive multiobjective optimization algorithm that integrates memory-based population and differential evolution. This contribution addresses critical challenges in robot path planning, balancing competing objectives like energy consumption, time, and smoothness. Jaroenapibal’s research has implications for industrial automation, where efficient trajectory planning reduces operational costs and improves precision. His work is recognized for bridging the gap between theoretical optimization and practical robotic applications, making him a notable figure in the field of computational robotics.
Research Focus
Key Achievements
Top Papers
- 1Self-adaptive MRPBIL-DE for 6D robot multiobjective trajectory planning27 citations · 2019