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About

Jakub Mlotek is a robotics researcher whose work bridges industrial precision and soft robotic adaptability. His primary research areas include robot repeatability compensation, soft gripping mechanisms, and kinematic representation conversion. Mlotek’s most impactful contribution addresses a critical industrial challenge: thermal drift in robots. His 2021 paper, cited 21 times, introduces a novel compensation method that reduces repeatability differences between cold and warm operating conditions, moving beyond traditional absolute accuracy approaches to enhance real-world manufacturing reliability. In soft robotics, Mlotek’s 15-citation work on FinRay finger structural optimization advances passive shape-adaptable gripping, enabling robots to securely wrap objects of varying geometries without active control—a key requirement for dynamic environments. He also developed the RobKin Interpreter, an automated tool for converting between robot kinematic representations, simplifying complex analytical processes for serial robot analysis. Though his 2022 work on shape-changing manipulators is nascent, it explores how deformable segments can expand a robot’s working area, hinting at future applications in reconfigurable automation. Mlotek’s research demonstrates a dual focus on solving practical industrial problems and pushing the boundaries of adaptive robotic systems.