Calvins Otieno
Papers
4
Total Citations
12
H-Index
2
About
Calvins Otieno is a researcher focused on advancing autonomous mobile robot navigation, with particular expertise in obstacle avoidance, path planning, and fuzzy logic control systems. His work addresses critical challenges in enabling robots to operate reliably in static unknown environments, where sensor uncertainty and nonlinear dynamics pose significant hurdles. Otieno’s most cited paper, “A Survey on Obstacles Avoidance Mobile Robot in Static Unknown Environment” (2018, 7 citations), provides a foundational review of collision avoidance methodologies that has guided subsequent research in the field. He has made notable contributions to optimizing fuzzy logic controllers, as seen in his studies on the effects of membership functions (2020, 2 citations) and a comparative analysis of their role in path planning optimization (2025, 1 citation). His recent co-simulation framework integrating MATLAB and CoppeliaSim (2025, 2 citations) offers a modular, scalable tool for testing nonholonomic robot navigation, addressing practical constraints of cost and safety. Otieno’s work bridges simulation and real-world application, providing valuable insights for students and researchers developing intelligent, collision-free mobile robot systems.
Research Focus
Key Achievements
Top Papers
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