Home /Research /Dynamic Object Recognition Using Precise Location Detection and ANN for Robot Manipulator
MANIPULATION

Dynamic Object Recognition Using Precise Location Detection and ANN for Robot Manipulator

Kyekyung Kim, Jaemin Cho, Jihyeong Pyo, Sangseung Kang, Jin Ho Kim

Year
2017
Citations
18

Abstract

This paper presents vision based dynamic object recognition system for robot manipulation tasks by increasing the needs of automation machine vision. Object recognition or localization technology is used for pick and place task using robot. The dynamic object recognition system detects landmark features using neural network and provides grasping points of randomly located object, bin-picking object, visual servoing object to robot. The characteristic of dynamic object is free of posture, location, shape, distance, stacked form and is not restricted in illumination condition. This paper uses neural network based feature extractor and object classifier to recognize dynamic object. Dynamic object recognition system goes through image processing less impact to illumination effect, landmark feature extraction according to an object, coupled NN based object detection and recognition. We have evaluated performance of dynamic object recognition by testing detection of location, estimation of posture, distance to object and by identifying object type. And the other performance has evaluated by processing pick and place task using robot manipulator.

Keywords

Artificial intelligenceComputer visionComputer scienceCognitive neuroscience of visual object recognition3D single-object recognitionObject (grammar)RobotObject detectionLandmarkFeature extraction

Related papers

Browse all MANIPULATION papers