S. Maloku

Papers

Total Citations

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About

S. Maloku is a robotics researcher whose work bridges artificial intelligence and mechanical control systems, with a primary focus on autonomous navigation and bipedal locomotion. His most influential contribution, "Genetic and Fuzzy logic algorithms for robot path finding" (2016, 17 citations), introduces a novel approach for detecting and avoiding both static and dynamic obstacles using only a single camera—without requiring environmental mapping. By integrating Genetic Algorithms with Fuzzy Logic, Maloku developed an optimization method that enables mobile robots to navigate closed systems efficiently, reducing computational overhead while maintaining robust obstacle avoidance. In his second major work, "Trajectory Planning and Inverse Kinematics Solver for Real Biped Robot with 10 DOF-s" (2016, 11 citations), he addresses the complex challenge of humanoid robot stability during walking. Maloku presents a gait synthesis method for planar bipedal robots, tackling both single and double support phases to ensure balanced locomotion on level ground. His research is particularly notable for tackling real-world implementation constraints, offering practical solutions for robots operating without pre-mapped environments. With a combined 28 citations across these foundational papers, Maloku's work continues to influence developments in autonomous robotics and humanoid gait control.