Outputs (3)

A vision-guided deep learning framework for dexterous robotic grasping using Gaussian processes and transformers (2025)
Journal Article

Robotic manipulation of objects with diverse shapes, sizes, and properties, especially deformable ones, remains a significant challenge in automation, necessitating human-like dexterity through the integration of perception, learning, and control. Th... Read More about A vision-guided deep learning framework for dexterous robotic grasping using Gaussian processes and transformers.

Integrating spiking neural networks and deep learning algorithms on the neurorobotics platform (2022)
Presentation / Conference Contribution

We present a neurorobotic model that can associate self motion (odometry) with vision to correct for drift in a spiking neural network model of head direction based closely on known rodent neurophys-iology. We use a deep predictive coding network to... Read More about Integrating spiking neural networks and deep learning algorithms on the neurorobotics platform.

A spiking neural network model of rodent head direction calibrated with landmark free learning (2022)
Journal Article

Maintaining a stable estimate of head direction requires both self-motion (idiothetic) information and environmental (allothetic) anchoring. In unfamiliar or dark environments idiothetic drive can maintain a rough estimate of heading but is subject t... Read More about A spiking neural network model of rodent head direction calibrated with landmark free learning.