Maria Francesca Pia Cusimano
Papers
1
Total Citations
5
H-Index
1
About
Maria Francesca Pia Cusimano is a researcher at the intersection of robotics and neuromorphic computing, with a primary focus on developing intelligent, bio-inspired control and estimation systems for legged robots. Her most cited work, "Ground Reaction Force Estimation in a Quadruped Robot via Liquid State Networks" (2022, 5 citations), pioneers the use of Liquid State Machines (LSMs)—a form of reservoir computing—to estimate ground reaction forces from local proprioceptive data. This contribution is significant because it demonstrates how spiking neural networks can provide robust, efficient state estimation in complex, real-time robot-environment interactions, reducing reliance on expensive or fragile sensors. By mapping local feedback to global force estimates, Cusimano’s method enhances a robot’s ability to adapt to uncertain terrain, a critical challenge in autonomous locomotion. Her work bridges computational neuroscience and field robotics, offering a scalable, low-power solution for dynamic control. With a growing citation impact, Cusimano is establishing herself as a key voice in neuromorphic robotics, where her innovations promise to make quadrupedal robots more resilient and autonomous in unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1