most citedVision-Based Control for Robots by a Fully Spiking Neural System Relying on Cerebellar Predictive Learning

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2021

Adaptive Variable Impedance Control for a Modular Soft Robot Manipulator in Configuration Space

Mahmood Mazare, Silvia Tolu, Mostafa Taghizadeh

Compliance is a strong requirement for human-robot interactions. Soft-robots provide an opportunity to cover the lack of compliance in conventional actuation mechanisms, however, t…

eess.IV2021

RetinaNet Object Detector based on Analog-to-Spiking Neural Network Conversion

Joaquin Royo-Miquel, Silvia Tolu, Frederik E. T. Schöller +1

The paper proposes a method to convert a deep learning object detector into an equivalent spiking neural network. The aim is to provide a conversion framework that is not constrain…

cs.RO2021

A Neurorobotic Embodiment for Exploring the Dynamical Interactions of a Spiking Cerebellar Model and a Robot Arm During Vision-based Manipulation Tasks

Omar Zahra, David Navarro-Alarcon, Silvia Tolu

While the original goal for developing robots is replacing humans in dangerous and tedious tasks, the final target shall be completely mimicking the human cognitive and motor behav…

cs.RO20201 cited

Vision-Based Control for Robots by a Fully Spiking Neural System Relying on Cerebellar Predictive Learning

Omar Zahra, David Navarro-Alarcon, Silvia Tolu

The cerebellum plays a distinctive role within our motor control system to achieve fine and coordinated motions. While cerebellar lesions do not lead to a complete loss of motor fu…

q-bio.NC2020

Adaptive control for hindlimb locomotion in a simulated mouse through temporal cerebellar learning

T. P. Jensen, S. Tata, A. J. Ijspeert +1

Human beings and other vertebrates show remarkable performance and efficiency in locomotion, but the functioning of their biological control systems for locomotion is still only pa…