AIMC Topic: Motion

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Spatiotemporal Co-Attention Recurrent Neural Networks for Human-Skeleton Motion Prediction.

IEEE transactions on pattern analysis and machine intelligence
Human motion prediction aims to generate future motions based on the observed human motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling sequential data, recent works utilize RNNs to model human-skeleton motions on the obser...

A Learning-Based Approach to Sensorize Soft Robots.

Soft robotics
Soft actuators and their sensors have always been separate entities with two distinct roles. The omnidirectional compliance of soft robots thus means that multiple sensors have to be used to sense different modalities in the respective planes of moti...

Reconstruction of Dexterous 3D Motion Data From a Flexible Magnetic Sensor With Deep Learning and Structure-Aware Filtering.

IEEE transactions on visualization and computer graphics
We propose IM3D+, a novel approach to reconstructing 3D motion data from a flexible magnetic flux sensor array using deep learning and a structure-aware temporal bilateral filter. Computing the 3D configuration of markers (inductor-capacitor (LC) coi...

Deep Learning Based Joint PET Image Reconstruction and Motion Estimation.

IEEE transactions on medical imaging
Respiratory motion is one of the main sources of motion artifacts in positron emission tomography (PET) imaging. The emission image and patient motion can be estimated simultaneously from respiratory gated data through a joint estimation framework. H...

IMU Motion Capture Method with Adaptive Tremor Attenuation in Teleoperation Robot System.

Sensors (Basel, Switzerland)
Teleoperation robot systems can help humans perform tasks in unstructured environments. However, non-intuitive control interfaces using only a keyboard or joystick and physiological tremor reduce the performance of teleoperation. This paper presents ...

Research on Multicamera Photography Image Art in BERT Motion Based on Deep Learning Mode.

Computational intelligence and neuroscience
In order to improve the artistic expression effect of photographic images, this article combines the deep learning model to conduct multicamera photographic image art research in BERT motion. Moreover, this article analyzes the external parameter err...

When Bubbles Are Not Spherical: Artificial Intelligence Analysis of Ultrasonic Cavitation Bubbles in Solutions of Varying Concentrations.

The journal of physical chemistry. B
Ultrasonic irradiation of liquids, such as water-alcohol solutions, results in cavitation or the formation of small bubbles. Cavitation bubbles are generated in real solutions without the use of optical traps making our system as close to real condit...

A gecko-inspired robot with CPG-based neural control for locomotion and body height adaptation.

Bioinspiration & biomimetics
Today's gecko-inspired robots have shown the ability of omnidirectional climbing on slopes with a low centre of mass. However, such an ability cannot efficiently cope with bumpy terrains or terrains with obstacles. In this study, we developed a gecko...

Robotic system with programmable motion constraint for transurethral resection.

International journal of computer assisted radiology and surgery
PURPOSE: We propose a tele-operated transurethral robotic system with programmable motion constraint for tissue resection.

Programmable Morphing Hydrogels for Soft Actuators and Robots: From Structure Designs to Active Functions.

Accounts of chemical research
Nature provides abundant inspiration and elegant paradigms for the development of smart materials that can actuate, morph, and move on demand. One remarkable capacity of living organisms is to adapt their shapes or positions in response to stimuli. P...