Mohammad Ebrahim Shiri
Papers
2
Total Citations
8
H-Index
2
About
Mohammad Ebrahim Shiri’s research focuses on advancing autonomous robotics, with key contributions in humanoid locomotion and multi-robot coordination for critical applications. His most cited work, “Evolutionary approach for developing fast and stable offline humanoid walk” (2013, 4 citations), addresses the complex challenge of achieving stable, high-speed walking in humanoid robots. By integrating attitude estimation, dynamic stability control, and path planning, Shiri’s evolutionary method reduces reliance on exact mechanical modeling, enabling more adaptive and robust bipedal motion—a foundational step for real-world humanoid deployment. In “Using Self-Configurable Particle Swarm Optimization for Allocation Position of Rescue Robots” (2010, 4 citations), he pioneers a self-configuring swarm intelligence algorithm to optimize the placement of rescue robots in disaster scenarios. This work tackles the autonomy challenge in complex systems, allowing robots to dynamically adapt their positions without human intervention, thereby improving search-and-rescue efficiency. Though his citation counts are modest, Shiri’s impact lies in bridging evolutionary optimization and swarm robotics for practical, life-saving applications. His achievements highlight a commitment to making autonomous systems both intelligent and operationally reliable, offering valuable insights for researchers in robotics, swarm intelligence, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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