Lilita Kiforenko

Papers

Total Citations

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About

Lilita Kiforenko’s research focuses on the intersection of robotic grasping, gripper design, and sensor data fusion, with a particular emphasis on improving industrial automation. Her major contributions center on developing methods to compensate for pose uncertainties in robotic grasping—a critical challenge in manufacturing environments where object positions can vary unpredictably. In her most cited work, "Compensating Pose Uncertainties through Appropriate Gripper Finger Cutouts" (2018, 9 citations), she introduces a novel approach to gripper finger design that reduces the need for costly, time-consuming engineering iterations when switching production batches. By optimizing gripper geometries through dynamic simulation, as detailed in her 2016 paper (3 citations), Kiforenko demonstrates how simple parallel-finger grippers can be adapted for greater reliability and efficiency. Additionally, her work on fusing stereo and active-sensor data (2016, 2 citations) advances perception systems for robotic platforms, improving depth estimation accuracy. Though her citation counts are modest, Kiforenko’s research addresses practical, industry-driven problems, offering tangible solutions that reduce downtime and engineering effort. Her contributions are particularly valuable for students and researchers interested in bridging the gap between theoretical robotics and real-world manufacturing constraints.