Papers
10
Total Citations
427
H-Index
7
About
Jeng‐Shyang Pan is a leading figure in swarm intelligence and autonomous robotics, whose work has fundamentally advanced the field of path planning for mobile robots and unmanned aerial vehicles (UAVs). His research centers on developing novel, nature-inspired optimization algorithms—including the cuckoo search, whale optimization, and ions motion algorithms—to solve complex, multi-objective navigation problems. Pan’s most influential contribution is a parallel compact cuckoo search algorithm for three-dimensional path planning, which has garnered 166 citations for its efficiency in constrained environments. He has also pioneered multi-objective approaches, such as the whale optimization algorithm for robot path planning (98 citations), demonstrating that robotic navigation must satisfy multiple conflicting criteria simultaneously. His comprehensive overview of swarm intelligence algorithms (76 citations) serves as a foundational resource for researchers. Beyond path planning, Pan has contributed to visual SLAM systems and safe UAV operations for transmission line inspection. With over 400 citations across his top papers, his adaptive parallel arithmetic optimization algorithm (38 citations) continues to shape modern applied intelligence, making him a pivotal figure in the intersection of computational intelligence and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1A parallel compact cuckoo search algorithm for three-dimensional path planning166 citations · 2020
- 2
- 3Overview of Algorithms for Swarm Intelligence76 citations · 2011
- 4
- 5Modern Advances in Applied Intelligence22 citations · 2014
- 6A Multi-objective Ions Motion Optimization for Robot Path Planning10 citations · 2018
- 7An Improved JPS Algorithm in Symmetric Graph9 citations · 2015
- 8
- 9Effects of algorithmic parameters on swarm robotic search3 citations · 2010
- 10