Miguel F. Arevalo‐Castiblanco
Papers
2
Total Citations
18
H-Index
2
About
Miguel F. Arevalo-Castiblanco is a robotics researcher whose work focuses on multi-agent systems, bio-inspired algorithms, and nonlinear control. His most notable contribution is the development of an ant-based multi-robot exploration algorithm for non-convex spaces, which eliminates the need for constant global connectivity constraints. This approach, published in 2019 and garnering 13 citations, emulates pheromone trails to enable efficient, decentralized exploration—a significant departure from traditional methods that require continuous communication links. Arevalo-Castiblanco also advanced control theory through his 2018 work on implementing a nonlinear fuzzy Takagi-Sugeno controller for a mobile inverted pendulum, earning 5 citations. His research bridges the gap between biological inspiration and practical robotics, offering scalable solutions for autonomous exploration in complex environments. By addressing real-world constraints like intermittent connectivity, his work has implications for search-and-rescue missions and planetary exploration. Arevalo-Castiblanco’s achievements demonstrate a commitment to pushing the boundaries of swarm robotics and intelligent control systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2