Albert Esterline

North Carolina Agricultural and Technical State University

Papers

Total Citations

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About

Albert Esterline’s research lies at the intersection of robotics, artificial intelligence, and fuzzy logic, with a focus on enabling intelligent, autonomous navigation in complex environments. His most influential work introduces the application of Takagi-Sugeno fuzzy methods to robot motion planning, leveraging approximate cell decomposition to optimize path strategies—a paper that has garnered 9 citations. Esterline further advanced the field with a hybrid evolutionary system for global motion planning, combining obstacle representation with “visibility-based repair” to accelerate search processes, earning 8 citations. He also developed the goal-seeking with obstacle avoidance (GSOA) behavior for mobile robots, providing a practical hardware-software implementation using the Pioneer DX robot and integrating MATLAB with Visual C++. Additionally, his work on sensor fusion employs fuzzy integrals and diverse Bayesian networks to enhance perception reliability. Though citation counts are modest, Esterline’s contributions are notable for bridging theoretical fuzzy logic with real-world robotic applications, offering foundational techniques for autonomous navigation and sensor integration that continue to inform robotics research.