• 한국산업융합학회 논문집
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• 제17권2호
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• pp.35-41
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• 2014

This paper describes the obstacle avoidance architecture to walk safely around in factory and home environment, and presents methods for path planning and obstacle avoidance for the humanoid robot. Solving the problem of obstacle avoidance for a humanoid robot in an unstructured environment is a big challenge, because the robot can easily lose its stability or fall down if it hits or steps on an obstacle. We briefly overview the general software architecture composed of perception, short and long term memory, behavior control, and motion control, and emphasize on our methods for obstacle detection by plane extraction, occupancy grid mapping, and path planning. A main technological target is to autonomously explore and wander around in home environments as well as to communicate with humans.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.151-155
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbance and performance improvement with the on-line learning in the position control of excavator attachment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.516-519
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• 1996

Sub-assembly in ship manufacturing is a sequence of filet joint welding of stiffeners on metal panels and the process is different depending on companies. In this paper, we introduce a new intelligent robotic system of the sub-assembly process in Samsung Heavy Industry, where one shift of 22m * 9m workspace includes one to ten panels and each panel includes up to 10 stiffeners. The inherent problems such as several hundreds of different panels, unstructured task environment and the large scale do not allow a fixed automation, but needs highly intelligent versatile automation. The robotic system is composed of four 14DOF macro-mini robots and a task recognition system. Application of this system has verified the task specification such as low temperature environment(-10.deg. C) and productivity is satisfied successfully.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.804-809
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• 2007

Initialization problem is defined for indoor mobile robot as a whole process from arrival to normal operation in a new environment. The unstructured environment make the process much more difficult compared to industrial robot in structured environments. We propose a simple and efficient initialization process based on artificial stars on ceiling. Important task points and paths connecting task points are defined based on the corresponding artificial stars. This approach can be used for all kinds of indoor mobile robots with landmarks used for indoor localization.

• 대한가정학회지
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• 제40권9호
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• pp.191-205
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• 2002

The purpose of this study is to identify the homelike design characteristics of elderly housing facility. To investigate what the preference of physical design characteristics are, interview was done by unstructured questionnaire to 30 middle aged and middle income group housewives living in Seoul. It was identified that preferred homelike physical characteristics of the houses were composed of 4 themes, housing types, building appearences and garden, floor plan and natural and social environments of its location. Their desirable housing standard was amenity which is the highest level of home environment. In their later life, they wanted to live in vicinity of Seoul to enjoy cultural benefits of the city and active outdoor activities in sunny, natural suburban environment. They liked a spacious, clean and bright color with natural material furnishings. Each architectural design expression of 4 themes was suggested.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.29.1-29
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• 2001

Neuro-fuzzy systems are multi-layered connectionist networks that realize the elements and functions of traditional fuzzy logic control/decision systems. A trained neuro-fuzzy system is isomorphic to a fuzzy logic system, and fuzzy IF-THEN rule knowledge can be explicitly extracted from the network. This talk presents a brief introduction to self-adaptive neuro-fuzzy systems and addresses some recent research results and applications. Most of the existing neuro-fuzzy systems exhibit several major drawbacks that lead to performance degradation. These drawbacks are the curse of dimensionality (i.e., fuzzy rule explosion), inability to re-structure their internal nodes in a changing environment, and their lack of ability to extract knowledge from a given set of training data. This talk focuses on our investigation of network architectures, self-adaptation algorithms, and efficient learning algorithms that will enable existing neuro-fuzzy systems to self-adapt themselves in an unstructured and uncertain environment.

• 로봇학회논문지
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• 제18권3호
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• pp.352-357
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• 2023

Since robotic assembly in an unstructured environment is very difficult with existing control methods, studies using artificial intelligence such as reinforcement learning have been conducted. However, since long-time operation of a robot for learning in the real environment adversely affects the robot, so a method to shorten the learning time is needed. To this end, a method based on a pre-trained neural network was proposed in this study. This method showed a learning speed about 3 times than the existing methods, and the stability of reward during learning was also increased. Furthermore, it can generate a more optimal policy than not using a pre-trained neural network. Using the proposed reinforcement learning-based assembly trajectory generator, 100 attempts were made to assemble the power connector within a random error of 4.53 mm in width and 3.13 mm in length, resulting in 100 successes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1448-1451
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• 2004

Position estimation is one of the most important functions for the mobile robot navigating in the unstructured environment. Most of previous localization schemes estimate current position and pose of mobile robot by applying various localization algorithms with the information obtained from sensors which are set on the mobile robot, or by recognizing an artificial landmark attached on the wall, or objects of the environment as natural landmark in the indoor environment. Several drawbacks about them have been brought up. To compensate the drawbacks, a new localization method that estimates the absolute position of the mobile robot by using a fixed camera on the ceiling in the corridor is proposed. And also, it can improve the success rate for position estimation using the proposed method, which calculates the real size of an object. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data, but a kind of absolute localization. The effectiveness of the proposed localization scheme is demonstrated through the experiments.

• 농촌계획
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• 제29권4호
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• pp.35-53
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• 2023

This study attempts to identify the flow of key topics and issues of research trends related to environment-friendly agriculture conducted around the 2000s in South Korea and compare them with the environment-friendly agriculture promotion plan to seek the level of consistency and the direction of future development of environment-friendly agriculture. For the analysis of environment-friendly agriculture research trends and policy consistency, 'topic modeling', which is suitable for subject classification of large amounts of unstructured data, and 'text network analysis', which visualizes the relationship between keywords as a network and interprets its characteristics, were utilized. Overall, active discussions were held on 'technical discussions for the production and cultivation of environment-friendly agricultural products' and 'food safety & consumer awareness', and keywords such as production, cultivation, consumption, and safety were consistently linked to other keywords regardless of time. In addition, it was found that the issue of environment-friendly agriculture was partially consistent with the policy direction of the period. Considering the fact that the ongoing '5th Environment-Friendly Agriculture Promotion Phase' emphasizes the strengthening of rural environment management and aims to ensure the continuous quantitative and qualitative development of environment-friendly agriculture, active discussions and research on its environmental contributions and management methods are needed.

• 센서학회지
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• 제27권4호
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• pp.209-215
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• 2018

Recent research in animal behavior has shown that gradient information plays an important role in finding food and home. It is also important in optimization of performance because it indicates how the inputs should be adjusted for maximization/minimization of a performance index. We introduce perturbation as an additional input to obtain gradient information. Unlike the typical approach of calculating the gradient from the derivative, the proposed processing is very robust to noise since it is performed as a summation. Experimental results prove the validity of the process of spatial gradient acquisition. Quantitative indices for measuring the effect of the amplitude and the frequency are developed based on linear regression analysis. Drones are very useful for environmental monitoring and an autonomous path planning is required for unstructured environment. Guiding the drone for finding the origin of the interested physical property is done by estimating the gradient of the sensed value and generating the drone trajectories in the direction which maximizes the sensed value. Simulation results show that the proposed method can be successfully applied to identify the source of the physical quantity of interest by utilizing it for path planning of an autonomous drone in 3D environment.