Erdy Sulino Mohd Muslim Tan

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About

Erdy Sulino Mohd Muslim Tan is a robotics researcher whose work centers on autonomous mobile robot navigation, with a particular focus on environment mapping and localization. His most cited paper, "A Mapping Mobile Robot Using RP Lidar Scanner" (2015, 35 citations), addresses the foundational challenge of creating accurate environmental maps—a critical capability for tasks ranging from autonomous navigation to search and rescue operations. Tan has made significant contributions to improving localization algorithms, notably through his work on scan matching techniques. In "Scan Matching and KNN Classification for Mobile Robot Localisation Algorithm" (2017, 11 citations), he explored how combining scan matching with K-nearest neighbors classification can enhance a robot's ability to determine its position. He further refined this approach in "Improved KNN Scan Matching for Local Map Classification in Mobile Robot Localisation Application" (2019), where he addressed limitations in the standard Iterative Closest Point algorithm, which can suffer from inaccuracies. Tan's research is directly relevant to advancing the reliability and precision of mobile robots, enabling safer and more effective human-robot interaction in real-world environments.