Ekaterina Nikandrova

Aalto University, Lappeenranta-Lahti University of Technology

Papers

Total Citations

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About

Ekaterina Nikandrova is a roboticist whose research bridges the critical gap between stable manipulation and task-aware grasping. Her work centers on probabilistic modeling and category-based reasoning to enable robots to grasp objects not just securely, but purposefully. In her highly cited 2015 paper, "Category-based task specific grasping" (33 citations), she pioneered methods linking object categories to task requirements, showing that a screwdriver must be grasped differently for turning versus handing it over. This insight moved beyond traditional stability metrics to incorporate functional context. Earlier, in "Probabilistic sensor-based grasping" (2012, 26 citations), she introduced a novel probabilistic framework that unifies grasp attributes, online sensor data, and stability predictions into a single model. This approach allows robots to dynamically adapt grasps based on real-time feedback, a foundational contribution to sensor-driven manipulation. Nikandrova’s work has been instrumental in advancing robotic grasping from rigid, pre-planned motions to flexible, context-aware actions. Her research is essential reading for students and engineers working at the intersection of perception, planning, and physical interaction, demonstrating how probabilistic reasoning and categorical knowledge can make robots more dexterous and intelligent in real-world tasks.