• Journal of the Korean Society of Marine Environment & Safety
• /
• v.23 no.4
• /
• pp.415-420
• /
• 2017

In this paper, an algorithm for object counting via a conveyor system using machine vision is suggested. Object counting systems using image processing have been applied in a variety of industries for such purposes as measuring floating populations and traffic volume, etc. The methods of object counting mainly used involve template matching and machine learning for detecting and tracking. However, operational time for these methods should be short for detecting objects on quickly moving conveyor belts. To provide this characteristic, this algorithm for image processing is a region-based method. In this experiment, we counted young abalone shells that are similar in shape, size and color. We applied a characteristic conveyor system that operated in one direction. It obtained information on objects in the region of interest by comparing a second frame that continuously changed according to the information obtained with reference to objects in the first region. Objects were counted if the information between the first and second images matched. This count was exact when young shells were evenly spaced without overlap and missed objects were calculated using size information when objects moved without extra space. The proposed algorithm can be applied for various object counting controls on conveyor systems.

• Journal of Power System Engineering
• /
• v.21 no.4
• /
• pp.42-50
• /
• 2017

A velocity controller using a modified model reference adaptive controller (M-MRAC) and a projection operator for a fish sorting belt conveyor system with uncertainty parameters, input saturation and bounded disturbances is proposed in this paper. To improve the tracking performance and robustness of the proposed controller in the presence of bounded disturbances, the followings are done. Firstly, the reference model for the conventional model reference adaptive controller (CMRAC) is replaced by a modified reference model for a M-MRAC to reduce unexpected high frequency oscillation in control input signal when the adaptation rate is increased. Secondly, estimated parameters in an adaptive law are varied smoothly under bounded external disturbances and a projection operator is utilized in an adaptive law for the proposed M-MRAC controller to be robust. Thirdly, an auxiliary error vector is introduced for compensating the error dynamics of the system when the saturation input occurs. Finally, the experimental results are shown to verify the better effectiveness and performance of the proposed controller under the bounded disturbance and saturated input than that of a CMRAC.

• Annual Conference of KIPS
• /
• 2003.11b
• /
• pp.643-646
• /
• 2003

이 논문은 작업 대상물(object)을 최소 시간으로 interception 하기 위한 방법에 대하여 기술한다. 목표는 로봇이 world coordinate system을 기준으로 x축으로 이동하는 컨베이어 라인 상에서 이동되는 작업 대상물을 intercept 하는 것이다. 컨베이어 시스템이 최소의 시간으로 작업 대상물을 intercept하기 위해서는 다음의 주요 계획이 필요하다. 첫째는 최적의 object과 end effector의 meeting point 선택, 두 번째는 첫 번째 계획이 실효를 이루기 위한 로봇의 trajectory선택이다. 두 가지의 계획 중 여기서는 두 번째 계획이 최적이라고 가정하고 첫 번째 계획법 즉, 컨베이어 시스템 로봇을 이용한 작업 대상물의 gripping 동작을 행함에 있어서 최소 시간으로 작업대상물을 gripping 하기 위한 컨베이어 시스템과 minimum time gripping 알고리즘이 제시된다.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.826-829
• /
• 1995

In this paper, the problem of minimum-time trajectory planning of a robot manipulator with an arbitrary path is dealt. As for a straight path, the trajectory planning can be done without difficulty since the path is easily parameterized by its length. However, this is not the case for a non-straight path. In this paper, by noting that the others' joint angles and velocities are determined if one joint's angle and velocity are known, we reduce the problem of trajectory planning on a non-straight path to one in the 2-dimensional space of one joint's angle and velocity. Then, by applying the dynamic programming, we achieve the minimum-time trajectory planning. A simulation is done for verifying this.

• Annual Conference of KIPS
• /
• 2002.11a
• /
• pp.653-656
• /
• 2002

본 논문에서는 연속된 영상 정보를 이용하여 물체를 추적하는 시스템에 대하여 기술한다. 물체를 추적하는 시스템은 물체를 구별하는 단계에서 자동으로 물체를 추적하는 단계로 구성된다. 물체를 구별 하기 위해서는 영상에서 사용자가 원하는 물체를 추출해야 한다. 이를 위해서 여러 가지 전처리 과정을 거쳐서 물체를 추출하고, 물체에 대한 정보를 추출한다. 추출된 정보와 미리 입력된 물체에 대한 정보와 비교하여 사용자가 원하는 물체인지를 구별한다. 사용자가 원하는 물체라고 판단이 될 경우 추적 시스템은 추적 알고리즘을 이용하여 물체를 추적한다. 이 시스템을 평가하기 위해서 본 논문은 conveyor belt에서 물체를 추적, 추적된 물체를 잡는 실험을 하였고 성공적인 결과를 보였다.