AIMC Topic: Adaptation, Physiological

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Locomotion Control With Frequency and Motor Pattern Adaptations.

Frontiers in neural circuits
Existing adaptive locomotion control mechanisms for legged robots are usually aimed at one specific type of adaptation and rarely combined with others. Adaptive mechanisms thus stay at a conceptual level without their coupling effect with other mecha...

Nonlinear time delay estimation based model reference adaptive impedance control for an upper-limb human-robot interaction.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
A nonlinear Time Delay Estimation (TDE) based model reference adaptive impedance controller was developed for Tarbiat Modares University Upper Limbs Rehabilitation Robot (TUERR). The proposed controller uses a stable reference impedance model, which ...

Brain oscillatory correlates of visuomotor adaptive learning.

NeuroImage
Sensorimotor adaptation involves the recalibration of the mapping between motor command and sensory feedback in response to movement errors. Although adaptation operates within individual movements on a trial-to-trial basis, it can also undergo learn...

How adaptation, training, and customization contribute to benefits from exoskeleton assistance.

Science robotics
Exoskeletons can enhance human mobility, but we still know little about why they are effective. For example, we do not know the relative importance of training, how much is required, or what type is most effective; how people adapt with the device; o...

A cerebellar-based solution to the nondeterministic time delay problem in robotic control.

Science robotics
The presence of computation and transmission-variable time delays within a robotic control loop is a major cause of instability, hindering safe human-robot interaction (HRI) under these circumstances. Classical control theory has been adapted to coun...

Modeling learner-controlled mental model learning processes by a second-order adaptive network model.

PloS one
Learning knowledge or skills usually is considered to be based on the formation of an adequate internal mental model as a specific type of mental network. The learning process for such a mental model conceptualised as a mental network, is a form of (...

Centered Multi-Task Generative Adversarial Network for Small Object Detection.

Sensors (Basel, Switzerland)
Despite the breakthroughs in accuracy and efficiency of object detection using deep neural networks, the performance of small object detection is far from satisfactory. Gaze estimation has developed significantly due to the development of visual sens...

Motor adaptation via distributional learning.

Journal of neural engineering
. Both artificial and biological controllers experience errors during learning that are probabilistically distributed. We develop a framework for modeling distributions of errors and relating deviations in these distributions to neural activity.. The...

On the Unfounded Enthusiasm for Soft Selective Sweeps III: The Supervised Machine Learning Algorithm That Isn't.

Genes
In the last 15 years or so, soft selective sweep mechanisms have been catapulted from a curiosity of little evolutionary importance to a ubiquitous mechanism claimed to explain most adaptive evolution and, in some cases, most evolution. This transfor...