• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.232-237
• /
• 1998

This paper describes a new method for estimating time-to-collision which exhibits high tolerance to noise contained in camera images. Time to collision (TTC) is one of the most important parameters available from a camera attached to a mobile machine. TTC indirectly stands far the translation speed of the camera and is usually calculated either from successive images or optical flow by using intimate relationship between TTC and flow divergence. In most cases, however, it is not easy to get accurate optical flow, which makes it difficult to calculate TTC. In this study it is proved that if the target has a smooth surface, the average of divergence over any point-symmetric region on the image is equal to the divergence of the center of the region. It means that required divergence can be calculated by integrating optical flow vectors over a symmetric region. It is expected that in the process of the integration, accidental noise is canceled if they are independent of optical flow and the motion of the camera. Experimental results show that TTC can be estimated regardless of the surface condition. It is also shown that influence of noise is eliminated as the area of integration increases.

• Advances in robotics research
• /
• v.1 no.1
• /
• pp.101-126
• /
• 2014

In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions are achieved by a phase switching network (PSN) module. The combination of these modules generates various locomotion patterns and a reactive obstacle avoidance behavior. The behavior is driven by sensor inputs, to which additional neural preprocessing networks are applied. The complete neural circuitry is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot's specific embodiment. We also believe that our neural modules can be important components for locomotion generation in other complex robotic systems or they can serve as useful modules for other module-based neural control applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.2
• /
• pp.55-60
• /
• 2021

As the smart factory progresses, the use of automation facilities and robots is increasing. Also, with the development of IT technology, the utilization of the system using voice recognition is also increasing. Voice recognition technology is a technology that stands out in smart home and various IoT technologies, but it is difficult to apply to factories due to the specificity of factories. Therefore, in this study, a method to control an industrial articulated robot was designed using voice recognition technology that considers the situation at the manufacturing site. It was confirmed that the robot could be controlled through network protocol and command conversion after receiving voice commands for robot operation through mobile.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1485-1490
• /
• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user, does face recognition and vital for many surveillance based systems. Advantage of face recognition when compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to decrease in dimension from of image acquisition step and various changes associated with face pose and background. Factors that deteriorate performance of face recognition are many such as distance from camera to face, lighting change, pose change, and change of facial expression. In this paper, we implement a new 3D active camera system to prevent various pose variation that influence face recognition performance and propose face recognition algorithm for intelligent surveillance system and mobile robot system.

• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.1
• /
• pp.125-133
• /
• 2010

A versatile micro-robotic platform for micro/nano scale assembly has been demanded in a variety of application areas such as micro-biology and nanotechnology. In the near future, a flexible and compact platform could be effectively used in a scanning electron microscope chamber. We are developing a platform that consists of miniature mobile robots and a compact positioning stage with multi degree-of-freedom. This paper presents the design and the implementation of a low-cost and compact multi degree of freedom position sensor that is capable of measuring absolute translational and rotational displacement. The proposed sensor is implemented by using a CMOS type image sensor and a target with specific hole patterns. Experimental design based on statistics was applied to finding optimal design of the target. Efficient algorithms for image processing and absolute position decoding are discussed. Simple calibration to eliminate the influence of inaccuracy of the fabricated target on the measuring performance also presented. The developed sensor was characterized by using a laser interferometer. It can be concluded that the sensor system has submicron resolution and accuracy of ${\pm}4{\mu}m$ over full travel range. The proposed vision-based sensor is cost-effective and used as a compact feedback device for implementation of a micro robotic platform.

• Journal of Broadcast Engineering
• /
• v.23 no.5
• /
• pp.622-627
• /
• 2018

In this paper, we introduce an integrated augmented reality system using a small camera and a projector. We extract three-dimensional information of an object with a small portable camera and a projector by using a structured light system. We develop the concept of the virtual camera to generalize the projection method so that the image can be projected at a desired position with only the mesh of the object to be projected without computing the mapping between specific point sets. Therefore, it is possible to project not only simple planes but also complex curved surfaces to desired positions without complicated geometric calculation. Based on a robot with a small camera and a projector, it will largely explain the projector-camera system calibration, the calculation of the position of the recognized object, and the image projection method using the virtual camera concept.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2568-2574
• /
• 2005

Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2243-2247
• /
• 2005

If a personal robot is popularized like a personal computer in the future, many kinds of robots will appear and the number of manufacturers will increase as a matter of course. In such circumstances, it can be inefficient, in case each manufacturer makes a whole platform individually. The solutions for this problem are to modularize a robot component (hardware and software) functionally and to standardize each module. Each module is developed and sold by each special maker and an end-product company purchases desired modules and integrates them. The standardization of a module includes the unification of the electrical, mechanical and software interface. In this paper, a few prototypes developed based on the concept of this study are introduced and possibility which can be standard platform is verified. Each prototype has merits and demerits, and a new structure of the hardware platform considered them is proposed Also the software architecture to develop the standardized and modularized platform is introduced and its detailed structure is described. The name of a method and the way to use that are defined dependently on the standard interfaces in order to use a module in other modules. Each module consists of a distributed object and that can be implemented in the random programming language and platform. It is necessary to study on the standardization of a personal robot after this steadily.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.1
• /
• pp.73-82
• /
• 2010

Door is an important object to understand given environment and it could be used to distinguish with corridors and rooms. Doors are widely used natural landmark in mobile robotics for localization and navigation. However, almost algorithm for door recognition with camera is difficult real-time application because feature extraction and matching have heavy computation complexity. This paper proposes a method to recognize a door in corridor. First, we extract distinguished lines which have high possibility to comprise of door using Hough transformation. Then, we detect candidate of door region by applying previously extracted lines to first-stage visual fuzzy system. Finally, door regions are determined by verifying knob region in candidate of door region suing second-stage visual fuzzy system.

• Electronics and Telecommunications Trends
• /
• v.34 no.5
• /
• pp.14-25
• /
• 2019

As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.