Papers
9
Total Citations
189
H-Index
6
About
Antonio Di Lallo is a pioneering researcher at the intersection of soft robotics, medical robotics, and wearable assistive technologies. His work addresses critical challenges in human-robot interaction, particularly for clinical care in infectious environments—a focus that gained urgency during the COVID-19 pandemic. His highly cited 2021 paper, "Medical Robots for Infectious Diseases: Lessons and Challenges from the COVID-19 Pandemic" (76 citations), outlines how robotic systems can mitigate disease spread while delivering quality care across prevention, screening, and treatment. Di Lallo has also made significant contributions to soft continuum robots, introducing dynamic morphological computation through damping design (21 citations), enabling under-actuated control for adaptive grippers and locomotion. More recently, he has advanced high-force soft wearable robots with untethered fluidic engines (7 citations), targeting human augmentation and gait rehabilitation. His 2024 work on adaptive hierarchical origami-based metastructures (34 citations) demonstrates shape-morphing capabilities for multifunctional metamaterials. With a portfolio spanning fundamental mechanics to applied healthcare robotics, Di Lallo’s research is shaping the future of safe, adaptive, and clinically relevant robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Adaptive hierarchical origami-based metastructures34 citations · 2024
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- 5Untethered Fluidic Engine for High‐Force Soft Wearable Robots7 citations · 2024
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- 8A Novel Approach to Under-Actuated Control of Fluidic Systems4 citations · 2018
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