AIMC Topic: Hand Strength

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Research on the Industrial Robot Grasping Method Based on Multisensor Data Fusion and Binocular Vision.

Computational intelligence and neuroscience
At present, most of the handling industrial robots working on the production line are operated by teaching or preprogramming, which makes the flexibility of the production line poor and does not meet the flexible production requirements of the materi...

Deep Learning Method for Grasping Novel Objects Using Dexterous Hands.

IEEE transactions on cybernetics
Robotic grasping ability lags far behind human skills and poses a significant challenge in the robotics research area. According to the grasping part of an object, humans can select the appropriate grasping postures of their fingers. When humans gras...

Teleoperation of High-Speed Robot Hand with High-Speed Finger Position Recognition and High-Accuracy Grasp Type Estimation.

Sensors (Basel, Switzerland)
This paper focuses on the teleoperation of a robot hand on the basis of finger position recognition and grasp type estimation. For the finger position recognition, we propose a new method that fuses machine learning and high-speed image-processing te...

Deformation Modeling and Simulation of a Novel Bionic Software Robotics Gripping Terminal Driven by Negative Pressure Based on Classical Differential Algorithm.

Computational intelligence and neuroscience
A general pneumatic soft gripper is proposed in this paper. Combined with the torque balance theory, the mathematical theoretical model of bending deformation of soft gripper is established based on Yeoh constitutive model and classical differential ...

Glowing Sucker Octopus (Stauroteuthis syrtensis)-Inspired Soft Robotic Gripper for Underwater Self-Adaptive Grasping and Sensing.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
A soft gripper inspired by the glowing sucker octopus (Stauroteuthis syrtensis)' highly evolved grasping capability enabled by the umbrella-shaped dorsal and ventral membrane between each arm is presented here, comprising of a 3D-printed linkage mech...

Effective grasping enables successful robot-assisted dressing.

Science robotics
Advances in computer vision and robotic manipulation are enabling assisted dressing.

Pump Up the Jam: Granular Media as a Quasi-Hydraulic Fluid for Independent Control Over Isometric and Isotonic Actuation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Elastomer-granule composites have been used to switch between soft and stiff states by applying negative pressure differentials that cause the membrane to squeeze the internal grains, inducing dilation and jamming. Applications of this phenomenon hav...

Grasping learning, optimization, and knowledge transfer in the robotics field.

Scientific reports
Service robotics is a fast-developing sector, requiring embedded intelligence into robotic platforms to interact with the humans and the surrounding environment. One of the main challenges in the field is robust and versatile manipulation in everyday...

A 3D Printed Soft Robotic Hand With Embedded Soft Sensors for Direct Transition Between Hand Gestures and Improved Grasping Quality and Diversity.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In this study, a three-dimensional (3D) printed soft robotic hand with embedded soft sensors, intended for prosthetic applications is designed and developed to efficiently operate with new-generation myoelectric control systems, e.g., pattern recogni...

Reliable Vision-Based Grasping Target Recognition for Upper Limb Prostheses.

IEEE transactions on cybernetics
Computer vision has shown promising potential in wearable robotics applications (e.g., human grasping target prediction and context understanding). However, in practice, the performance of computer vision algorithms is challenged by insufficient or b...