Tang Swee Ho

University of Kuala Lumpur, University of Technology Malaysia

Papers

Total Citations

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About

Dr. Tang Swee Ho is a robotics researcher whose work centers on autonomous navigation and human-robot interaction. His primary contributions lie in advancing Simultaneous Localization and Mapping (SLAM) for mobile robots, a critical challenge in enabling machines to build maps of unknown environments while tracking their own position. His most cited work, a 2015 survey on SLAM based on filtering techniques, has garnered 20 citations and provides a comprehensive review of state estimation methods—including Kalman filters—that underpin modern robotic perception. Beyond SLAM, Dr. Tang explores human tracking and recognition, as demonstrated in his work on shirt pattern recognition using SURF (Speeded Up Robust Features) for moving targets. This research addresses the practical challenge of enabling robots to reliably follow and interact with humans by combining detection with continuous tracking and behavioral analysis. Though his citation counts are modest, his contributions reflect a focused effort on foundational problems in robotics, bridging theoretical filtering techniques with real-world applications in human-robot collaboration.