• Title/Summary/Keyword: Multi-Object Control

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Development of Real-Time Image Processing Algorithm on the Positions of Multi-Object in an Image Plane (한 이미지 평면에서 다물체 위치의 실시간 화상처리 알고리즘 개발)

  • Jang, W.S.;Kim, K.S.;Lee, S.M.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.22 no.5
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    • pp.523-531
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    • 2002
  • This study is concentrated on the development of high speed multi-object image processing algorithm in real time. Recently, the use of vision system is rapidly increasing in inspection and robot's position control. To apply the vision system, it is necessary to transform the physical coordinate of object into the image information acquired by CCD camera. Thus, to use the application of the vision system to the inspection and robot's position control in real time, we have to know the position of object in the image plane. Particularly, in case of rigid body using multi-cue to identify its shape, the each position of multi-cue must be calculated in an image plane at the same time. To solve these problems, the image processing algorithm on the position of multi-cue is developed.

A Study on Model and Control of Pinching Motion for Multi-Fingered Robot (다관절 핑거 로봇의 파지 운동 모델과 제어에 관한 연구)

  • Um H.;Choi J.H.;Kim Y.S.;Yang S.S.;Lee J.G.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.1060-1067
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    • 2005
  • This paper attempts to derive and analyze the dynamic system of pinching a rigid object by means of two multi-degrees-of-freedom robot fingers with soft and deformable tips. It is shown firstly that a set of differential equation describing dynamics system of the manipulators and object together with geometric constraint of tight area-contacts is formulated by Lagrange's equation. It is shown secondly that the problems of controlling both the forces of pressing object and the rotation angle of the object under the geometric constraints are discussed. In this paper, the control method for dynamic stable grasping and enhancing dexterity in manipulating things is proposed. It is illustrated by computer simulation that the control system gives the performance improvement in the dynamic stable grasping of the dual fingers robot with soft tips.

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OnBoard Vision Based Object Tracking Control Stabilization Using PID Controller

  • Mariappan, Vinayagam;Lee, Minwoo;Cho, Juphil;Cha, Jaesang
    • International Journal of Advanced Culture Technology
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    • v.4 no.4
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    • pp.81-86
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    • 2016
  • In this paper, we propose a simple and effective vision-based tracking controller design for autonomous object tracking using multicopter. The multicopter based automatic tracking system usually unstable when the object moved so the tracking process can't define the object position location exactly that means when the object moves, the system can't track object suddenly along to the direction of objects movement. The system will always looking for the object from the first point or its home position. In this paper, PID control used to improve the stability of tracking system, so that the result object tracking became more stable than before, it can be seen from error of tracking. A computer vision and control strategy is applied to detect a diverse set of moving objects on Raspberry Pi based platform and Software defined PID controller design to control Yaw, Throttle, Pitch of the multicopter in real time. Finally based series of experiment results and concluded that the PID control make the tracking system become more stable in real time.

An Object Recognition Method Based on Depth Information for an Indoor Mobile Robot (실내 이동로봇을 위한 거리 정보 기반 물체 인식 방법)

  • Park, Jungkil;Park, Jaebyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.10
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    • pp.958-964
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    • 2015
  • In this paper, an object recognition method based on the depth information from the RGB-D camera, Xtion, is proposed for an indoor mobile robot. First, the RANdom SAmple Consensus (RANSAC) algorithm is applied to the point cloud obtained from the RGB-D camera to detect and remove the floor points. Next, the removed point cloud is classified by the k-means clustering method as each object's point cloud, and the normal vector of each point is obtained by using the k-d tree search. The obtained normal vectors are classified by the trained multi-layer perceptron as 18 classes and used as features for object recognition. To distinguish an object from another object, the similarity between them is measured by using Levenshtein distance. To verify the effectiveness and feasibility of the proposed object recognition method, the experiments are carried out with several similar boxes.

Object Tracking Framework of Video Surveillance System based on Non-overlapping Multi-camera (비겹침 다중 IP 카메라 기반 영상감시시스템의 객체추적 프레임워크)

  • Han, Min-Ho;Park, Su-Wan;Han, Jong-Wook
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.6
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    • pp.141-152
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    • 2011
  • Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.

robust independant controller for position, motion-inducing force, internal force of multi-robot system) (다중 로보트 시스템의 위치, 운동야기힘, 내부힘의 강건 독립 제어기)

  • 김종수;박세승;박종국
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.539-542
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    • 1996
  • The forces exerted on an object by the end-effectors of multi-manipulators are decomposed into the motion-inducing force and the internal force. Motion-inducing force effects the motion of an object and internal force can't effect it. The motion of an object can't track exactly the desired motion because of internal force component, therefore internal force component must be considered. In this paper using the resolved acceleration control method and the fact that internal force lies in the null space of jacobian matrix, we construct independently the position, motion-inducing force and internal force controller. Secondly we construct the robust controller to preserve the robustness with respect to the uncertainty of manipulator parameters.

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Object-Oriented Petri Net Model for Representation of Flexible Process Plan (유연공정계획 표현을 위한 객체지향형 페트리네트 모델)

  • Lee, Kyung-Huy
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.4
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    • pp.669-686
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    • 1997
  • In this research, an object-oriented Petri net model for representing a flexible process plan is proposed, which is hierarchically multi-faceted for supporting planning, scheduling, and shop floor control functions. The multi-faceted process plan model consists of the following: a) an object model which represents on object-oriented data model, b) a static model which represents a process flow model with process alternatives, and c) a dynamic model which represents a process activity model with resources alternatives, of a flexible process plan. Petri nets allow the static and the dynamic process plan models to be represented in a unified formalism with an ease of model transformation. The multi-faceted process plan model suggested in this paper, is illustrated with a prismatic port in comprehensive detail.

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Analysis on Stable Grasping based on Three-dimensional Acceleration Convex Polytope for Multi-fingered Robot (3차원 Acceleration Convex Polytope를 기반으로 한 로봇 손의 안정한 파지 분석)

  • Jang, Myeong-Eon;Lee, Ji-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.1
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    • pp.99-104
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    • 2009
  • This article describes the analysis of stable grasping for multi-fingered robot. An analysis method of stable grasping, which is based on the three-dimensional acceleration convex polytope, is proposed. This method is derived from combining dynamic equations governing object motion and robot motion, force relationship and acceleration relationship between robot fingers and object's gravity center through contact condition, and constraint equations for satisfying no-slip conditions at every contact points. After mapping no-slip condition to torque space, we derived intersected region of given torque bounds and the mapped region in torque space so that the intersected region in torque space guarantees no excessive torque as well as no-slip at the contact points. The intersected region in torque space is mapped to an acceleration convex polytope corresponding to the maximum acceleration boundaries which can be exerted by the robot fingers under the given individual bounds of each joints torque and without causing slip at the contacts. As will be shown through the analysis and examples, the stable grasping depends on the joint driving torque limits, the posture and the mass of robot fingers, the configuration and the mass of an object, the grasp position, the friction coefficients between the object surface and finger end-effectors.

Visual servoing of robot manipulators using the neural network with optimal structure (최적화된 신경회로망을 이용한 동적물체의 비주얼 서보잉)

  • 김대준;전효병;심귀보
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.302-305
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    • 1996
  • This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

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