Papers
3
Total Citations
14
H-Index
3
About
Ehsan Soleimani is a robotics and control systems researcher whose work focuses on the coordination and optimization of multi-agent systems, particularly unmanned aerial vehicles (UAVs) and rescue robots. His research integrates game theory, model predictive control, and swarm intelligence to solve complex routing and formation control problems. In his widely cited work on multiagent UAV routing, Soleimani compares distributed and decentralized models using a game theory approach, addressing the critical challenge of formation control in leader-follower robotic networks. He further advances the field with a cascade explicit tube model predictive controller designed for multi-robot systems, demonstrating robust performance under constraints. Earlier in his career, Soleimani developed a self-configurable particle swarm optimization algorithm to optimize the allocation and positioning of rescue robots in emergency scenarios. His contributions, each garnering 4–5 citations, have practical implications for autonomous search-and-rescue missions and cooperative drone operations. By bridging theoretical control methods with real-world robotic applications, Soleimani’s work continues to influence the design of intelligent, autonomous multi-agent systems.
Research Focus
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