Kevin Pirewa Lagaza
Papers
2
Total Citations
32
H-Index
2
About
Kevin Pirewa Lagaza is a robotics researcher whose work focuses on intelligent navigation and path planning for autonomous mobile robots operating in complex, real-world environments. His key research areas include bio-inspired optimization algorithms, fuzzy logic control, and collision-free motion planning. Lagaza’s most impactful contribution is the application of the Spider Monkey Optimization Algorithm to solve the static path planning problem, achieving collision-free navigation and path optimization for mobile robots—a paper that has garnered 20 citations. He also developed a Minimum Fuzzy Rule-Based (MFRB) controller for dynamic environments, enabling a differential drive wheeled robot to successfully avoid both moving and stationary obstacles while reaching a goal using only a minimal set of sensor-actuator rules. This work, published in 2018, has been cited 12 times and demonstrates his ability to create efficient, low-complexity solutions for real-time navigation. Lagaza’s research bridges theoretical optimization and practical robotics, offering scalable approaches for autonomous systems. His work is particularly valuable for students and engineers seeking to understand how swarm intelligence and fuzzy logic can be harnessed for robust, adaptive robot control in unpredictable settings.
Research Focus
Key Achievements
Top Papers
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