Wilson O. Quesada
Papers
2
Total Citations
45
H-Index
2
About
Wilson O. Quesada is a leading researcher in autonomous robotics and intelligent control systems, with a focus on multi-agent coordination and adaptive navigation. His seminal work on "Leader-Follower Formation for UAV Robot Swarm Based on Fuzzy Logic Theory" (2018, 30 citations) introduced a novel fuzzy logic framework for scalable and robust swarm coordination, enabling unmanned aerial vehicles to maintain formation in dynamic environments. This contribution has been foundational for decentralized swarm intelligence. Quesada further advanced the field with his 2019 paper on "Autonomous Navigation for Exploration of Unknown Environments and Collision Avoidance in Mobile Robots Using Reinforcement Learning" (15 citations), which pioneered the use of reinforcement learning for sensor-driven navigation without reliance on spatial maps. This work demonstrated how robots can autonomously explore and adapt to unstructured environments, significantly improving collision avoidance and exploration efficiency. His research bridges theoretical machine learning with practical robotic applications, offering scalable solutions for real-world deployment. With over 45 citations across his most-cited works, Quesada’s contributions are shaping the next generation of autonomous systems, from search-and-rescue missions to industrial automation. His innovative integration of fuzzy logic and reinforcement learning continues to inspire researchers in swarm robotics and intelligent navigation.
Research Focus
Key Achievements
Top Papers
- 1Leader-Follower Formation for UAV Robot Swarm Based on Fuzzy Logic Theory30 citations · 2018
- 2