Zulkarnain Zainudin

Technical University of Malaysia Malacca

Papers

Total Citations

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About

Zulkarnain Zainudin is a leading researcher in robotics perception, with a primary focus on people detection and tracking using laser-based sensors. His work centers on developing robust algorithms for autonomous systems operating in dynamic, populated environments—a critical challenge for applications in robotics, healthcare, automotive, and security. Zainudin’s foundational contribution, “Torso detection and tracking using a 2D laser range finder” (2010, 21 citations), established a practical framework for identifying and following human subjects with a single 2D LiDAR sensor. This work has been influential in enabling safe human-robot interaction. More recently, Zainudin has advanced the field by addressing the limitations of conventional Bayesian filters. His 2023 paper, “Gaussian Processes-BayesFilters with Non-Parametric Data Optimization for Efficient 2D LiDAR Based People Tracking,” introduces a novel hybrid approach that combines Gaussian Processes with Bayes filters to handle highly maneuverable targets and long-term occlusions—scenarios where traditional Kalman and Particle Filters often fail. This work demonstrates his ongoing commitment to improving tracking accuracy and reliability in real-world, cluttered settings. Zainudin’s research continues to push the boundaries of autonomous perception, making robots more aware and responsive to the people around them.