• 제목/요약/키워드: Autonomous Systems

검색결과 1,590건 처리시간 0.018초

자율섭취기능을 갖는 생체 모방형 4족 보행로봇 (Bio-mimetic Quadruped Walking Robot with Autonomous Eating Function)

  • 박세훈;김경호;정길웅;김관훈;이연정
    • 제어로봇시스템학회논문지
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    • 제12권4호
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    • pp.320-327
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    • 2006
  • This paper introduces a new entertainment robot called ELIRO-II(Eating Lizard RObot version 2)which is a bio-mimetic quadruped walking robot with autonomous eating function. We focus on the realization of the behavior of an animal, i.e., wandering around to find food and eating food. The ELIRO-II is modeled after a lizard, which has four legs, 2-DOF waist-joint, an eye part, a mouth part and a stomach part. The effectiveness of the developed robot is shown through real experiments.

도로 환경에서 자율주행을 위한 독립 관찰자 기반 주행 상황 인지 방법 (Independent Object based Situation Awareness for Autonomous Driving in On-Road Environment)

  • 노삼열;한우용
    • 제어로봇시스템학회논문지
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    • 제21권2호
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    • pp.87-94
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    • 2015
  • This paper proposes a situation awareness method based on data fusion and independent objects for autonomous driving in on-road environment. The proposed method, designed to achieve an accurate analysis of driving situations in on-road environment, executes preprocessing tasks that include coordinate transformations, data filtering, and data fusion and independent object based situation assessment to evaluate the collision risks of driving situations and calculate a desired velocity. The method was implemented in an open-source robot operating system called ROS and tested on a closed road with other vehicles. It performed successfully in several scenarios similar to a real road environment.

실외 도로 환경에서의 자율주행 로봇 개발 (Development of Autonomous Navigation Robot in Outdoor Road Environments)

  • 노치원;강연식;강성철
    • 제어로봇시스템학회논문지
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    • 제15권3호
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    • pp.293-299
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    • 2009
  • This paper discusses an autonomous navigation system for urban environments. For the localization of the robot, EKF (Extended Kalman Filter) algorithm is used with odometry, angle sensor, and DGPS (Differential Global Positioning System) measurement. Especially in an urban environment, DGPS is often blocked by buildings and trees and the resulting inaccurate positioning prevents the robot from safe and reliable navigation. In addition to the global information from DGPS, the local information of the curb on the roadway is used to track a route when the global DGPS information is inaccurate. For this purpose, curb detection algorithm is developed and implemented in the developed navigation algorithm. Four different types of navigation strategies are developed and they are switched to adapt to different localization conditions according to the availability of DGPS and the existence of the curbs on the roadway. The experimental results show that the designed switching strategy improves the navigation performance adapting to the environment conditions.

퍼지논리에 의한 후방주차 시스템 설계 (Design of Backward Parking System using Fuzzy Logic)

  • 학양화;김태균;최병재;류석환
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.337-340
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    • 2007
  • 무인자동차에 관한 연구가 활성화되면서 무인 주차 또한 중요한 과제로 대두되고 있다. 본 논문에서는 무인 차량을 위한 주차 편의 시스템 설계를 위하여 퍼지논리시스템에 의한 주차 알고리즘을 설계하고자 한다. 기존의 논문들이 제시한 장단점을 분석하여 새로운 단순 구조 형태의 규칙표를 통한 주차 알고리즘을 설계, 구현하고, 시뮬레이션을 통하여 그 효용성을 확인하고자 한다.

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스마트 매뉴팩처링을 위한 자율화 (Autonomy for Smart Manufacturing)

  • 박홍석
    • 한국정밀공학회지
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    • 제31권4호
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    • pp.287-295
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    • 2014
  • Smart manufacturing (SM) considered as a new trend of modern manufacturing helps to meet objectives associated with the productivity, quality, cost and competiveness. It is characterized by decentralized, distributed, networked compositions of autonomous systems. The model of SM is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee's foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To prove this concept, a cloud machining system is considered as research object in which internet of things and cloud computing are used to integrate, organize and allocate the machining resources. Artificial life tools are used for cooperation among autonomous elements in the cloud machining system.

이동로봇 자율주행을 위한 행위모듈의 실행순서 조정기법 (Sequencing Strategy for Autonomous Mobile Robots in Real Environments)

  • 송인섭;박정민;오상록;조영조;박귀태
    • 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.

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자율 주행 헬리콥터의 위치 추종 제어를 위한 LQR 제어 및 신경회로망 보상 방식 (Position Tracking Control of an Autonomous Helicopter by an LQR with Neural Network Compensation)

  • 엄일용;석진영;정슬
    • 제어로봇시스템학회논문지
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    • 제11권11호
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    • pp.930-935
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    • 2005
  • In this paper, position tracking control of an autonomous helicopter is presented. Combining an LQR method and a proportional control forms a simple PD control. Since LQR control gains are set for the velocity control of the helicopter, a position tracking error occurs. To minimize a position tracking error, neural network is introduced. Specially, in the frame of the reference compensation technique for teaming neural network compensator, a position tracking error of an autonomous helicopter can be compensated by neural network installed in the remotely located ground station. Considering time delay between an auto-helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network performs better than that of LQR itself.

외란 관측기를 이용한 모형 자율 주행 자동차의 강인 속도 제어 (Robust Speed Control of an Autonomous Vehicle Using Disturbance Observer)

  • 고영준;김영준;김정수
    • 제어로봇시스템학회논문지
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    • 제22권5호
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    • pp.339-345
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    • 2016
  • This paper presents a robust speed control of an autonomous vehicle using a disturbance observer. For the purpose, the transfer function of speed dynamics of an autonomous vehicle is identified using step response data. Based on the identified transfer function, model based PID (Proportional-Integral-Derivative) control is designed. In order to design a robust control against load variations on the vehicle, a disturbance observer (DOB) based control is devised. The performance of the designed DOB based control is demonstrated by real experiments.

수중 자율 운동체의 방향 제어를 위한 자기회귀 웨이블릿 신경회로망 기반 적응 백스테핑 제어 (Self-Recurrent Wavelet Neural Network Based Adaptive Backstepping Control for Steering Control of an Autonomous Underwater Vehicle)

  • 서경철;유성진;박진배;최윤호
    • 제어로봇시스템학회논문지
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    • 제13권5호
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    • pp.406-413
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    • 2007
  • This paper proposes a self-recurrent wavelet neural network(SRWNN) based adaptive backstepping control technique for the robust steering control of autonomous underwater vehicles(AUVs) with unknown model uncertainties and external disturbance. The SRWNN, which has the properties such as fast convergence and simple structure, is used as the uncertainty observer of the steering model of AUV. The adaptation laws for the weights of SRWNN and reconstruction error compensator are induced from the Lyapunov stability theorem, which are used for the on-line control of AUV. Finally, simulation results for steering control of an AUV with unknown model uncertainties and external disturbance are included to illustrate the effectiveness of the proposed method.

퍼지 게인 스케쥴링을 이용한 자율 무인 잠수정의 자세 제어 (Motion Control of an AUV (Autonomous Underwater Vehicle) Using Fuzzy Gain Scheduling)

  • 박랑은;황은주;이희진;박민용
    • 제어로봇시스템학회논문지
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    • 제16권6호
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    • pp.592-600
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    • 2010
  • The problem of motion control for AUV (Autonomous Underwater Vehicles) is addressed. The utilization of such robotic vehicles has gained an increasing importance in many marine activities. In this paper the objective is to describe how to design and apply FGS (Fuzzy Gain Scheduling) PD (Proportional Derivative) controller for an AUV (Autonomous Underwater Vehicle) to control the yaw and depth of the vehicle by keeping the path of the navigation to a desired point, and/or changing the path according to a set point.