Papers
14
Total Citations
444
H-Index
11
About
Gianni Stano is a pioneering researcher at the intersection of additive manufacturing (AM) and soft robotics, whose work has fundamentally advanced how soft robotic systems are designed, fabricated, and sensed. His most cited contribution, a 2020 review on AM for soft robots (171 citations), established a comprehensive foundation for the field, while subsequent work demonstrated practical breakthroughs in 3D-printed airtight pneumatic actuators and embedded sensing and actuation systems. Stano's research consistently tackles one of soft robotics' most persistent challenges: reducing manual assembly by enabling single-step, monolithic fabrication of complex structures. His innovative approaches span fused filament fabrication of piezoresistive strain sensors with temperature compensation, multimaterial adhesion strategies inspired by biological structures, and electromagnetic-assisted 3D printing of ultra-thin silicone constructs. More recently, he has extended into learning-based control, applying deep reinforcement learning to soft robotic manipulation tasks. Collectively, Stano's publications have amassed nearly 400 citations, reflecting substantial influence across robotics, materials science, and biomedical engineering communities. His trajectory marks him as a key figure shaping the next generation of intelligent, manufacturable soft robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Additive manufacturing aimed to soft robots fabrication: A review171 citations · 2020
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- 7Pushing with Soft Robotic Arms via Deep Reinforcement Learning20 citations · 2024
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