• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.407-418
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• 2023

The Multi-Object Goal Visual Navigation(MultiOn) is a visual navigation task in which an agent must visit to multiple object goals in an unknown indoor environment in a given order. Existing models for the MultiOn task suffer from the limitation that they cannot utilize an integrated view of multimodal context because use only a unimodal context map. To overcome this limitation, in this paper, we propose a novel deep neural network-based agent model for MultiOn task. The proposed model, MCFMO, uses a multimodal context map, containing visual appearance features, semantic features of environmental objects, and goal object features. Moreover, the proposed model effectively fuses these three heterogeneous features into a global multimodal context map by using a point-wise convolutional neural network module. Lastly, the proposed model adopts an auxiliary task learning module to predict the observation status, goal direction and the goal distance, which can guide to learn the navigational policy efficiently. Conducting various quantitative and qualitative experiments using the Habitat-Matterport3D simulation environment and scene dataset, we demonstrate the superiority of the proposed model.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.211-216
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• 2005

In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically, the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1589-1592
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• 1997

Among the prerequisite abilities (perception of environment, path planning and position estimation) of an autonomous mobile robot, position estimation has been seldom studied by mobile robot researchers. In most cases, conventional positioin estimation has been performed by placing landmarks or giving the entrire environmental information in advance. Unlikely to the conventional ones, the study addresses a new method that the robot itself can select distinctive features in the environment and save them as landmarks without any a priori knowledge, which can maximize the autonomous behavior of the robot. First, an orjentaion probaility model is applied to construct a lcoal map of robot's surrounding. The feature of the object in the map is then extracted and the map is saved as landmark. Also, presented is the position estimation method that utilizes the correspondence between landmarks and current local map. In dong this, the uncertainty of the robot's current positioin is estimated in order to select the corresponding landmark stored in the previous steps. The usefulness of all these approaches are illustrated with the results porduced by a real robot equipped with ultrasonic sensors.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.396-401
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• 2003

Electrical impedance tomography(EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents and measured voltages on the surface of the object. In this paper, an effective dynamic EIT imaging scheme is presented based on the projection filtering to estimate the unknown resistivity distribution. In particular, pre-integration (pre-grouping) technique is employed to stabilize the inverse algorithm. We carried out computer simulations with synthetic data to illustrate the reconstruction performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1093-1098
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• 2003

In this paper, a practical methodology of hand-manipulator motion coordination for indoor service robot is introduced. This paper describes the procedures of opening door performed by service robot as a noticeable example of motion coordination. This paper presents well-structured framework for hand-manipulator motion coordination, which includes intelligent sensor data interpretation, object shape estimation, optimal grasping, on-line motion planning and behavior-based task execution. This proposed approach is focused on how to integrate the respective functions in harmony and enable the robot to complete its operation under the limitation of usable resources. As a practical example of implementation, the successful experimental results in opening door whose geometric parameters are unknown beforehand are provided.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.159-164
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• 2004

In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simultaneous perturbation method as an image reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

• Journal of Korean Institute of Industrial Engineers
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• v.7 no.2
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• pp.55-59
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• 1981

An Application of Experimental Designs to Improve the quality of Industrial product : optimization Methodology of statistical model. The primary object of this paper is to aid scientists and Engineers, in applying response surface procedures to obtain operating conditions for many technical fields, particularly for industrial manufacturing processes. The problem considered in this paper is to select technically and scientifically some important factors affecting the quality of products through the experimental design and analysis of response surface. Even though the mathematical model is unknown these statistical analysis can be applicable to control the quality of industrial products and to determine optimum operating conditions for many technical fields, particularly, for industrial manufacturing processes. This paper proposes a method to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1203-1210
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• 2007

Robots have begun to perform various tasks on replacing the human in the daily life such as cleaning, entertainments etc. In order to accomplish the effective performance of intricate and precise tasks, robot hand must have special capabilities, such as decision making in given condition, autonomy in unknown situation and stable manipulation of object. In this study, we addresses the development of a 3-fingered humanoid robot hand system. We execute static analysis, vibration analysis and flexible dynamics to reserve stability at the design. Grasp motion of the finger uses a linear actuator and gears. Motion can be distinguished into four parts depending on the grasping thin paper, sphere, and column. In each motion, we compare the displacement of the case to be rigid with the case to be flexible. As a result, manufactured and feasibility of the robot hand is validated through preliminary experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.611-618
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• 2000

This paper presents a shape classification method of dynamic image based on adaptive fuzzy inference. It describes the design scheme of fuzzy inference algorithm which makes it suitable for low speed systems such as conveyor, uninhabited transportation. In the first Discrete Wavelet Transform(DWT) is utilized to extract the motion vector in a sequential images. This approach provides a mechanism to simple but robust information which is desirable when dealing with an unknown environment. By using feature parameters of moving object, fuzzy if - then rule which can be able to adapt the variation of circumstances is devised. Then applying the implication function, shape classification processes are performed. Experimental results are presented to testify the performance and applicability of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.67-76
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• 2005

In this paper, An analysis on the intelligence system for a biped walking robot(BWR) was made and its results were applied to the BWR. Various sensors were applied to the developed BWR for autonomous and intelligent walk in unknown environments. To measure the distance between the object and BWR, ultrasonic sensor and infrared-rays sensor were used. To identity surrounding environments, vision system was used. Gyro sensor was used to control the posture of BWR. Also, piezoelectricity sensor was used to identity the pressure of foot landing on the surface. Sensors applied to the robot have measurement errors according to noises or walking environments. To improve the function of these sensors, influences of noise or sensing errors were minimized using a sensor fusion scheme. A gait test using the sensor fusion system was performed, and its results are presented.