• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.92.2-92
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• 2002

Building autonomous robots have been a central objective of research in artificial intelligence. The development of techniques for autonomous navigation in real environment consist one of the main tendencies of the current researches about Robotics. An important problem in autonomous navigation is the necessity of dealing with a great amount of uncertainties inherent to the real environments. The paraconsistent logic has characteristics that make it become an adequate tool to solve this problem. In this work, it is proposed a technique of mapping the real world in the navigation of an autonomous robot using the paraconsistent logic.

• 융합신호처리학회논문지
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• 제4권1호
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• pp.56-63
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• 2003

본 논문은 실제 무인주행자동차에 적용할 수 있는 비전 기반의 소형 자율이동로봇 개발에 관한 연구를 제시한다. 이전의 자율주행차량은 하드웨어 설계의 복잡성, 실장의 어려움과 많은 계산량으로 인해 PC에 대한 의존도가 높았다. 본 논문에서는 고속에서 정확한 조향 및 빠른 이동을 할 수 있고, 단일 카메라를 사용한 독립형 시스템으로 지능적 인식을 할 수 있는 소형 자율이동로봇을 제안한다. 제안된 시스템은 폭 25~30cm, 총길이 200cm로 만들어진 트랙에서 실험하였다. 실험 로봇은 직선 트랙에서 평균 32.9km/h, 곡률반경 30~40m인 곡선트랙에서 평균 22.3km/h의 속도로 주행할 수 있었다 이 시스템은 실제 무인 자동차를 쉽게 만들기 위해 사용할 수 있는 차선 인식 알고리즘을 적용한 소형 자율이동로봇 시스템에 대한 하나의 모델을 제시할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3373-3389
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• 2022

Exploration of mobile robot without prior data about environments is a fundamental problem during the SLAM processes. In this work, we propose improved version of previous Rmap algorithm by modifying its Exploration submodule. Despite the previous Rmap's performance which significantly reduces the overhead of the grid map, its exploration module costs a lot because of its rectangle following algorithm. To prevent that, we propose a new Rmap+ algorithm for autonomous path planning of mobile robot to explore an unknown environment. The algorithm bases on paired frontiers. To navigate and extend an exploration area of mobile robot, the Rmap+ utilizes the inner and outer frontiers. In each exploration round, the mobile robot using the sensor range determines the frontiers. Then robot periodically changes the range of sensor and generates inner pairs of frontiers. After calculating the length of each frontiers' and its corresponding pairs, the Rmap+ selects the goal point to navigate the robot. The experimental results represent efficiency and applicability on exploration time and distance, i.e., to complete the whole exploration, the path distance decreased from 15% to 69%, as well as the robot decreased the time consumption from 12% to 86% than previous algorithms.

• 로봇학회논문지
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• 제3권3호
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• pp.245-254
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• 2008

Recently, many vision-based navigation methods have been introduced as an intelligent robot application. However, many of these methods mainly focus on finding an image in the database corresponding to a query image. Thus, if the environment changes, for example, objects moving in the environment, a robot is unlikely to find consistent corresponding points with one of the database images. To solve these problems, we propose a novel navigation strategy which uses fast motion estimation and a practical scene recognition scheme preparing the kidnapping problem, which is defined as the problem of re-localizing a mobile robot after it is undergone an unknown motion or visual occlusion. This algorithm is based on motion estimation by a camera to plan the next movement of a robot and an efficient outlier rejection algorithm for scene recognition. Experimental results demonstrate the capability of the vision-based autonomous navigation against dynamic environments.

• 제어로봇시스템학회논문지
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• 제5권3호
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• pp.297-305
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• 1999

Autonomous mobile robots are required to achieve multiple goals while responding quickly to the dynamic environments. An appropriate robot control architecture, which clearly and systematically defines the relationship among the inputs, the processing functions and the outputs, thus needs to be embedded in the robot controller. This paper proposes a kind of hybrid control architecture which combines the key features of the two well-known robot control architectures; hierarchical and behavioral- based. The overall control architecture consists of three layers, i.e. the highest planner, the middle plan executor, and the lowest monitor and behavior-based controller. In the planned situation, only one behavior module is chosen by the logical coordinator in the plan executor according to the way point bin. In the exceptional situation, the central controller in the plan executor issues an additional control command to reach the planned way point. Several simulations and experiments with autonomous mobile robot show that the proposed architecture enables the robot controller to achieve the multiple sequential goals even in dynamic and uncertain environments.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.113-117
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• 2005

This paper describes a visual control scheme, fuzzy logic system for visual servoing of an autonomous mobile robot. An existing communication autonomous mobile robot always needs to keep the object in image to detect the moving object. This is a problem in an autonomous mobile robot for spontaneous activity. To solve it, some features for an object are taken from an image and then use in the design of fuzzy logic system for decision of moving location and direction of visual servoing contrivance(apparatus). So continuous tracking is possible by moving the visual servoing contrivance. We present some simulation results and further studies in the Section of Simulation and Concluding Remarks.

• 전기학회논문지
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• 제67권8호
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• pp.1089-1098
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• 2018

In this paper, we propose an autonomous feeding robot and its obstacle classification system using ultrasonic sensors to secure the driving safety of the robot and efficient feeding operation. The developed feeding robot is verified by operation experiments in a cattle shed. In the proposed classification algorithm, not only the maximum amplitude of the ultrasonic echo signal but also two gradients of the signal and the variation of amplitude are considered as the feature parameters for object classification. The experimental results show the efficiency of the proposed classification method based on the Support Vector Machine, which is able to classify objects or obstacles such as a human, a cow, a fence and a wall.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.1044-1049
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• 2015

This paper proposes an autonomous navigation system of mobile robots for indoor corridor environment. The system uses a laser scanner but does not use reflectors. The laser scanner measures the distance between robot and structures such as wall, pillar, and fixtures. Adaptive breakpoint detector and modified IEPF (iterative endpoint fit) are developed to find mark points from the distance data. The robot path for corridor is then generated using the angle histogram of the mark points. The experimental results are finally presented to show the effectiveness of the proposed method.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권6호
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• pp.366-371
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• 2005

For an autonomous mobile robot localization, it is very important for the robot to be able to recognize indoor environment and match a detected object to an object defined within a map developed either online or of offline. Given the map defining the locations of geometric beacons like wall and corner existing in the robot operation environment, this paper presents a stereo ultrasonic sensor based method practically applicable in recognizing the geometric beacons in real-time. The stereo ultrasonic sensor used in the experiment consists of an ultrasonic transmitter and two ultrasonic receivers placed symmetrically about the transmitter Experimental results are provided to demonstrate that the proposed method is more efficient in recognizing wall and coner than the conventional method of using multiple number of transmitter-receiver pairs.

• 대한조선학회논문집
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• 제58권2호
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• pp.121-128
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• 2021

According to the increasing interest and demand for the Autonomous Surface Vessels (ASV), the autonomous navigation system is being developed such as obstacle detection, avoidance, and path planning. In general, autonomous navigation algorithm controls the ship by detecting the obstacles with various sensors and planning path for collision avoidance. This study aims to construct and prove autonomous algorithm with integrated various sensor using the Robot Operating System (ROS). In this study, the safety zone technique was used to avoid obstacles. The safety zone was selected by an algorithm to determine an obstacle-free area using 2D LiDAR. Then, drift angle of the ship was controlled by the propulsion difference of the port and starboard side that based on PID control. The algorithm performance was verified by participating in the 2020 Korea Autonomous BOAT (KABOAT).