Biologically Inspired Vision and Touch Sensing to Optimize 3D Object Representation and Recognition

Rouhafzay, Ghazal; Creţu, Ana-Maria; Payeur, Pierre

doi:10.1109/mim.2021.9436099

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…Deep learning is a very hot research field in recent years. Deep learning has good feature extraction ability, and can use multi-layer network to extract different levels of feature information [4]. Convolutional Neural Networks are one of the most commonly used network structures in deep learning models.…”

Section: Deep Learning Model -Convolutional Neural Networkmentioning

confidence: 99%

Object Recognition and Grasping Detection Method of Construction Machinery Robot Relying on Deep Learning

2021

KME

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At present, robots are widely used in the field of machinery manufacturing, which improves the production speed on the basis of ensuring the safety of workers. As a result, the traditional mode of enterprises based on manual operation has begun to be transformed into industrial robots as the main body. Construction machinery robots need to capture information about the surrounding environment in production operations. Traditional object recognition methods cannot adapt to complex working environments. Therefore, how to effectively identify target objects and successfully grasp objects has become a challenge for robots. In addition, the grasping detection(GD) method required by the robot to complete the task also relies on the known information of the target object and cannot effectively deal with the complex and changeable unknown environment. To this end, this paper designs a robot GD system based on deep learning, constructs a GD model and system framework through a convolutional neural network(CNN), and introduces a multi-target object grasping recognition algorithm to improve the grasping accuracy of the robot. The simulation experiment of the GD system proves that the accuracy rate of the system successfully grasping objects is over 95%.

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Section: Deep Learning Model -Convolutional Neural Networkmentioning

confidence: 99%

Object Recognition and Grasping Detection Method of Construction Machinery Robot Relying on Deep Learning

2021

KME

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Animation Video Production System Based on Three Dimensional Vision Sensor Network

Liu

2022

2022 4th International Academic Exchange Conference on Science and Technology Innovation (IAECST)

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Biologically Inspired Vision and Touch Sensing to Optimize 3D Object Representation and Recognition

Cited by 2 publications

References 11 publications

Object Recognition and Grasping Detection Method of Construction Machinery Robot Relying on Deep Learning

Object Recognition and Grasping Detection Method of Construction Machinery Robot Relying on Deep Learning

Animation Video Production System Based on Three Dimensional Vision Sensor Network

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