Hasith Karunasekera

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About

Hasith Karunasekera is a robotics researcher specializing in autonomous navigation and computer vision, with a particular focus on the challenging problem of negative obstacle detection. His work addresses a critical gap in autonomous ground vehicle (UGV) safety: while positive obstacles like vehicles and pedestrians are well-studied, hazards such as ditches, potholes, and drop-offs—negative obstacles—remain underexplored. Karunasekera’s most cited paper, “Stereo vision based negative obstacle detection” (2017, 18 citations), pioneered stereo-vision methods for identifying these dangerous terrain features, enabling UGVs to navigate more safely in off-road and industrial environments. He further advanced this field with an “Energy Minimization Approach for Negative Obstacle Region Detection” (2019, 13 citations), introducing efficient computational techniques to detect negative obstacles in real time. His contributions are vital for applications ranging from military robotics to agricultural automation, where avoiding hidden hazards is essential. By pushing the boundaries of stereo vision and energy-based modeling, Karunasekera has established himself as a key innovator in making autonomous systems more robust and reliable in complex, unstructured terrains.