A deep learning framework for neuroscience
Abstract Systems neuroscience seeks explanations for how the brain implements a wide
variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to …
variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to …
A review of tactile information: Perception and action through touch
Tactile sensing is a key sensor modality for robots interacting with their surroundings. These
sensors provide a rich and diverse set of data signals that contain detailed information …
sensors provide a rich and diverse set of data signals that contain detailed information …
Learning the signatures of the human grasp using a scalable tactile glove
Humans can feel, weigh and grasp diverse objects, and simultaneously infer their material
properties while applying the right amount of force—a challenging set of tasks for a modern …
properties while applying the right amount of force—a challenging set of tasks for a modern …
Making sense of vision and touch: Self-supervised learning of multimodal representations for contact-rich tasks
Contact-rich manipulation tasks in unstructured environments often require both haptic and
visual feedback. However, it is non-trivial to manually design a robot controller that …
visual feedback. However, it is non-trivial to manually design a robot controller that …
Deep learning for time-series analysis
JCB Gamboa - arXiv preprint arXiv:1701.01887, 2017 - arxiv.org
In many real-world application, eg, speech recognition or sleep stage classification, data are
captured over the course of time, constituting a Time-Series. Time-Series often contain …
captured over the course of time, constituting a Time-Series. Time-Series often contain …
Robotic tactile perception of object properties: A review
Touch sensing can help robots understand their surrounding environment, and in particular
the objects they interact with. To this end, roboticists have, in the last few decades …
the objects they interact with. To this end, roboticists have, in the last few decades …
A review of robot learning for manipulation: Challenges, representations, and algorithms
A key challenge in intelligent robotics is creating robots that are capable of directly
interacting with the world around them to achieve their goals. The last decade has seen …
interacting with the world around them to achieve their goals. The last decade has seen …
Deep learning in robotics: a review of recent research
HA Pierson, MS Gashler - Advanced Robotics, 2017 - Taylor & Francis
Advances in deep learning over the last decade have led to a flurry of research in the
application of deep artificial neural networks to robotic systems, with at least 30 papers …
application of deep artificial neural networks to robotic systems, with at least 30 papers …
Recent advances of artificial intelligence in manufacturing industrial sectors: A review
The recent advances in artificial intelligence have already begun to penetrate our daily lives.
Even though the development is still in its infancy, it has been shown that it can outperform …
Even though the development is still in its infancy, it has been shown that it can outperform …
Making sense of vision and touch: Learning multimodal representations for contact-rich tasks
Contact-rich manipulation tasks in unstructured environments often require both haptic and
visual feedback. It is nontrivial to manually design a robot controller that combines these …
visual feedback. It is nontrivial to manually design a robot controller that combines these …