Papers
11
Total Citations
49
H-Index
4
About
Astrid Rubiano is a researcher at the forefront of soft robotics and intelligent prosthetics, specializing in the integration of smart materials, artificial intelligence, and biomechanics to create next-generation assistive devices. Her work centers on developing under-actuated robotic hands and fingers that mimic human dexterity, with a particular focus on soft actuation mechanisms and artificial muscles. Rubiano’s most cited paper, “Smart Materials and Their Application in Robotic Hand Systems: A State of the Art” (2021, 15 citations), provides a comprehensive review of how shape-memory alloys and polymers are revolutionizing medical robotics. She introduced the innovative “Soft Driving Epicyclical Mechanism for Robotic Finger” (2019, 8 citations), a novel approach to achieving dexterous manipulation without rigid components. Her contributions extend to computer vision, where she applies deep learning and Hopfield networks for object recognition and grasping algorithms, as seen in her 2020 work on Faster R-CNN-based gripping. Rubiano also developed the hybrid kinematic model for the ProMain-I prosthetic hand (2015), bridging theoretical modeling with experimental validation. With a growing body of work spanning morphological optimization, path planning in virtual environments, and mathematical modeling of manipulators, Rubiano is shaping the future of wearable robotics—making human-like robotic assistance more accessible, adaptive, and intelligent.
Research Focus
Key Achievements
Top Papers
- 1
- 2Soft Driving Epicyclical Mechanism for Robotic Finger8 citations · 2019
- 3Object Recognition Through Artificial Intelligence Techniques5 citations · 2020
- 4
- 5Artificial Muscles Design Methodology Applied to Robotic Fingers4 citations · 2016
- 6
- 7Morphological Optimization of Prosthesis’ Finger for Precision Grasping2 citations · 2016
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