Sang Seung Kang

Object Recognition Method for Industrial Intelligent Robot

The introduction of industrial intelligent robot using vision sensor has been interested in automated factory. 2D and 3D vision sensors have used to recognize object and to estimate object pose, which is for packaging parts onto a complete whole. But it is not trivial task due to illumination and various types of objects. Object image has distorted due to illumination that has caused low reliability in recognition. In this paper, recognition method of complex shape object has been proposed. An accurate object region has detected from combined binary image, which has achieved using DoG filter and local adaptive binarization. The object has recognized using neural network, which is trained with sub-divided object class according to object type and rotation angle. Predefined shape model of object and maximal slope have used to estimate the pose of object. The performance has evaluated on ETRI database and recognition rate of 96% has obtained.

Recognition of walking intention using multiple bio/kinesthetic sensors for lower limb exoskeletons

In order to assist the lower limb disabled people to walk, walking-support exoskeletons with bio/kinesthetic sensors such as EMG (Electromyography), gyroscope, and FSR (Force Sensing Resistor) have been developed. It is important to implicitly recognize the walking intention and control the walking-support mechanism. The objective of this work is to examine the walking intention while a person is walking with Lofstrand crutches by analyzing multiple bio/kinesthetic sensor signals. We developed watch/glove and shoe-insoles sensor modules using FSR sensors to recognize the users walking states as well as intention to walk. The FSR signals measuring force at the palm and Gyro sensor signals reflecting the pose of the upper limb were used as clues for recognizing walking intention. While seventeen normal subjects walked for five gate cycles based on the triped walking (i.e., placing crutches in forward and then moving one step) with crutches, the FSR and Gyro signals were acquired from their palms and area of vertebrae lumbales. The result showed that the combination of FSR and Gyro signals could recognize users implicit intention to walk - start walking, keep walking, and stop walking.

Dual-arm Robot for Cell Production of Cellular Phone

Recently, the requirement of automation in the cell production system is increasing due to a decrease of skilled workers who are the key point of a cell production system. This paper proposes a dual-arm robot designed and implemented with consideration of being applied to a cell production line of cellular phone. A specification was derived from the analysis of production process and the consideration of configuration for human-robot cooperation. Design and implementation results of the proposed dual-arm robot were suggested and the feasibility was verified through the demonstration of the proposed robot in some of packaging job of cellular phone.