AIMC Topic: Computer Simulation

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Learning robust perceptive locomotion for quadrupedal robots in the wild.

Science robotics
Legged robots that can operate autonomously in remote and hazardous environments will greatly increase opportunities for exploration into underexplored areas. Exteroceptive perception is crucial for fast and energy-efficient locomotion: Perceiving th...

Novel Big Data-Driven Machine Learning Models for Drug Discovery Application.

Molecules (Basel, Switzerland)
Most contemporary drug discovery projects start with a 'hit discovery' phase where small chemicals are identified that have the capacity to interact, in a chemical sense, with a protein target involved in a given disease. To assist and accelerate thi...

LPI Radar Waveform Recognition Based on Neural Architecture Search.

Computational intelligence and neuroscience
In order to reach the intelligent recognition, the deep learning classifiers adopted by radar waveform are normally trained with transfer learning, where the pretrained convolutional neural network on an external large-scale classification dataset (e...

Research on Music Style Classification Based on Deep Learning.

Computational and mathematical methods in medicine
Music style is one of the important labels for music classification, and the current music style classification methods extract features such as rhythm and timbre of music and use classifiers to achieve classification. The classification accuracy is ...

Review on generic methods for mechanical modeling, simulation and control of soft robots.

PloS one
In this review paper, we are interested in the models and algorithms that allow generic simulation and control of a soft robot. First, we start with a quick overview of modeling approaches for soft robots and available methods for calculating the mec...

Ensemble deep learning for the prediction of proficiency at a virtual simulator for robot-assisted surgery.

Surgical endoscopy
BACKGROUND: Artificial intelligence (AI) has the potential to enhance patient safety in surgery, and all its aspects, including education and training, will derive considerable benefit from AI. In the present study, deep-learning models were used to ...

Adaptive Finite-Time Containment Control of Uncertain Multiple Manipulator Systems.

IEEE transactions on cybernetics
This article is concerned with the containment control of multiple manipulators with uncertain parameters. A novel distributed adaptive backstepping strategy is given in the finite-time control framework. The finite-time command filters (FTCFs) used ...

Design of Fuzzy State Observer and Mobile Sensor Guidance for Semilinear Parabolic PDE Systems.

IEEE transactions on cybernetics
This article investigates the issue of the fuzzy observer design for the semilinear parabolic partial differential equation (PDE) systems with mobile sensing measurements. Initially, we employ a Takagi-Sugeno (T-S) fuzzy PDE model to represent the se...

Learning Cognitive Map Representations for Navigation by Sensory-Motor Integration.

IEEE transactions on cybernetics
How to transform a mixed flow of sensory and motor information into memory state of self-location and to build map representations of the environment are central questions in the navigation research. Studies in neuroscience have shown that place cell...

Dissipativity-Based Disturbance Attenuation Control for T-S Fuzzy Markov Jumping Systems With Nonlinear Multisource Uncertainties and Partly Unknown Transition Probabilities.

IEEE transactions on cybernetics
This article is concerned with the dissipativity-based disturbance attenuation control for a class of Takagi-Sugeno (T-S) fuzzy Markov jump systems (FMJSs) suffering from nonlinear multisource disturbances. The considered system possesses nonlinear a...