Sajad Badalkhani

University of Tabriz, University of Birjand

Papers

Total Citations

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About

Sajad Badalkhani’s research lies at the intersection of robotics, control systems, and autonomous navigation, with a focus on enhancing robot performance in complex, real-world environments. His early work introduced a novel Neuro-PID controller for robot manipulators, leveraging neural networks to adaptively stabilize open-loop unstable systems and mitigate uncertainties—a contribution that has garnered 12 citations and laid groundwork for intelligent control in robotics. More recently, Badalkhani has advanced multi-robot simultaneous localization and mapping (SLAM), tackling the critical challenge of dynamic environments where moving objects degrade estimation accuracy. His 2021 paper on multi-robot SLAM with parallel maps (4 citations) proposes a robust framework for maintaining map integrity amid dynamic changes, while his study on the effects of moving landmark speed (2 citations) quantifies how velocity impacts SLAM performance, offering insights for real-time deployment. By addressing the fragility of traditional SLAM algorithms in dynamic settings, Badalkhani’s work pushes toward more resilient, collaborative robotic systems—essential for applications like search-and-rescue or autonomous fleets. His research continues to shape adaptive control and multi-agent perception, inspiring students and engineers to build robots that thrive beyond static labs.