Papers
11
Total Citations
505
H-Index
7
About
Adham Atyabi is a leading researcher at the intersection of computational intelligence, swarm robotics, and soft robotics. His work focuses on developing novel algorithms for multi-robot systems, particularly in navigation and path planning under uncertainty. Atyabi is best known for introducing the Area Extension Particle Swarm Optimization (AEPSO) algorithm, a modified version of PSO that significantly improves swarm coordination in uncharted and noisy environments. His highly cited 2020 comparative review on mobile robot path planning (232 citations) has become a foundational resource for researchers choosing between classical and meta-heuristic methods. Atyabi also made notable contributions to soft robotics, co-designing a lightweight pneumatic continuum robot arm with decoupled variable stiffness and positioning (159 citations), demonstrating his versatility across robotic domains. His work on cooperative learning in heterogeneous swarms and the effects of communication constraints has advanced the practical deployment of robotic teams. With over 500 total citations, Atyabi’s research continues to influence autonomous systems, offering elegant computational solutions to real-world robotic challenges.
Research Focus
Key Achievements
Top Papers
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- 3Applying Area Extension PSO in Robotic Swarm33 citations · 2009
- 4Navigating a robotic swarm in an uncharted 2D landscape32 citations · 2009
- 5Particle swarm optimization with area extension (AEPSO)13 citations · 2007
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