Jonna Laaksonen

Lappeenranta-Lahti University of Technology

Papers

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About

Jonna Laaksonen is a leading researcher in robotic grasping and manipulation, with a focus on integrating tactile and proprioceptive sensing to enhance robot dexterity. Her work addresses the fundamental challenge of enabling robots to interact reliably with uncertain environments, a critical step toward human-like manipulation. Laaksonen’s major contributions include developing probabilistic frameworks for grasp planning that leverage sensor feedback to estimate grasp stability in real time. Her 2012 paper, "Learning continuous grasp stability for a humanoid robot hand based on tactile sensing," has garnered 44 citations, establishing a foundation for data-driven approaches in tactile-based grasping. In "Probabilistic sensor-based grasping" (26 citations), she introduced a novel probabilistic model that unifies grasp attributes, sensor data, and stability predictions, advancing the field beyond traditional force-closure metrics. Her work on "Tactile-Proprioceptive Robotic Grasping" (10 citations) further demonstrates how combining tactile and proprioceptive cues can improve grasp robustness, particularly in soft-contact scenarios. Laaksonen’s research is pivotal for developing autonomous robots capable of handling complex, unstructured tasks, making her a key figure in modern robotics. Her achievements underscore the importance of sensor integration in bridging the gap between robotic and human manipulation capabilities.