Outputs (38)

Feeling the pressure: The influence of vibrotactile patterns on feedback perception (2022)
Presentation / Conference Contribution

Tactile feedback is necessary for closing the sen-sorimotor loop in prosthetic and tele-operable control, which would allow for more precise manipulation and increased acceptance of use of such devices. Pressure stimuli are commonly presented to user... Read More about Feeling the pressure: The influence of vibrotactile patterns on feedback perception.

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.

Evaluating multi-channel vibrational feedback arrays in a digit discrimination task (2022)
Presentation / Conference Contribution

In recent years manipulators and grippers have become more advanced., allowing for more nuanced interactions with the environment. In order to take advantage of the benefits that this can provide in teleoperation., methods for providing closed-loop t... Read More about Evaluating multi-channel vibrational feedback arrays in a digit discrimination task.

Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding (2021)
Journal Article

Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place recogniti... Read More about Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding.

WhiskEye: A biomimetic model of multisensory spatial memory based on sensory reconstruction (2021)
Presentation / Conference Contribution

We present WhiskEye, a visual tactile robot supporting a neurorobotic investigation of spatial memory as a multisensory reconstructive process. This article outlines the motivation for building WhiskEye; the technical details of the physical robot, a... Read More about WhiskEye: A biomimetic model of multisensory spatial memory based on sensory reconstruction.

A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing (2021)
Journal Article

The cerebellum is a neural structure essential for learning, which is connected via multiple zones to many different regions of the brain, and is thought to improve human performance in a large range of sensory, motor and even cognitive processing ta... Read More about A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing.

Active whisker placement and exploration for rapid object recognition (2020)
Presentation / Conference Contribution

© 2019 IEEE. Identifying objects using sparse tactile sensor arrays requires movement across the surface and the integration of sensory information to support hypotheses. In this study we demonstrate a surface placement control strategy to orient and... Read More about Active whisker placement and exploration for rapid object recognition.

Fast, flexible closed-loop feedback: Tracking movement in “real-millisecond-time” (2019)
Journal Article

© 2019 Sehara et al. One of the principal functions of the brain is to control movement and rapidly adapt behavior to a changing external environment. Over the last decades our ability to monitor activity in the brain, manipulate it while also manipu... Read More about Fast, flexible closed-loop feedback: Tracking movement in “real-millisecond-time”.

Feed-forward selection of cerebellar models for calibration of robot sound source localization (2019)
Presentation / Conference Contribution

© 2019, Springer Nature Switzerland AG. We present a responsibility predictor, based on the adaptive filter model of the cerebellum, to provide feed-forward selection of cerebellar calibration models for robot Sound Source Localization (SSL), based o... Read More about Feed-forward selection of cerebellar models for calibration of robot sound source localization.