Abolfazl Khorshidi
Papers
1
Total Citations
2
H-Index
1
About
Abolfazl Khorshidi is a researcher specializing in multi-robot systems, localization, and evolutionary computation. His work addresses critical challenges in autonomous robotics, particularly in scenarios involving communication failures and kidnapped robot problems. In his most cited paper, "Evolutionary particle filter applied to leader-labor multi-robot localization for communication failure and kidnapped situations" (2016), Khorshidi introduced the innovative Leader-Labor Localization (LlL) scheme, which formulates multi-robot cooperative localization using an evolutionary particle filter. This approach significantly enhances robustness in surveillance, environmental monitoring, target tracking, and search and rescue missions. While his citation count is currently modest, his contributions are foundational for researchers tackling real-world multi-robot coordination challenges. Khorshidi’s work bridges evolutionary algorithms and probabilistic filtering, offering practical solutions for degraded communication environments. His research is particularly valuable for students and engineers developing resilient autonomous systems, demonstrating how bio-inspired methods can improve localization accuracy and fault tolerance in distributed robotic teams.
Research Focus
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Top Papers
- 1