• 제목/요약/키워드: Indoor Autonomous Navigation

검색결과 78건 처리시간 0.026초

구조화된 실내 환경에서 초음파센서를 이용한 모바일 로봇 실시간 localization 기법 (Real-time Localization of Mobile Robot Using Ultrasonic Sensor in Structured Indoor Environment)

  • 이만희;조황
    • 제어로봇시스템학회논문지
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    • 제11권12호
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    • pp.1068-1076
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    • 2005
  • In order to increase the autonomous navigation capability of a mobile robot, it is very crucial to develop a method for the robot to be able to recognize a priori hon structured environmental characteristics. This paper proposes an ultrasonic sensor based real-time method for recognizing a priori known structured indoor environmental characteristics like a wall and comer Unlike the methods reported in the literature the information obtained from the sensor can be processed in real-time by extended Kalman filter to update estimations of the position and orientation of robot with respect to known environmental characteristics.

Vision-Based Indoor Localization Using Artificial Landmarks and Natural Features on the Ceiling with Optical Flow and a Kalman Filter

  • Rusdinar, Angga;Kim, Sungshin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제13권2호
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    • pp.133-139
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    • 2013
  • This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.

단일 초음파센서를 이용한 자율 주행 로봇의 경로 계획용 지도작성 (Map-Building for Path-Planning of an Autonomous Mobile Robot Using a Single Ultrasonic Sensor)

  • 김영근;김학일
    • 대한전기학회논문지:시스템및제어부문D
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    • 제51권12호
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    • pp.577-582
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    • 2002
  • The objective of this paper is to produce a weighted graph map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor circumstance. The AMR navigates in th unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. Then, the occupancy grid map is converted to a weighted graph map suing morphological image processing and thinning algorithms. the path- planning for autonomous navigation of a mobile robot can be carried out based on the occupancy grid map. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

Mobile Robot Navigation using a Dynamic Multi-sensor Fusion

  • Kim, San-Ju;Jin, Tae-Seok;Lee, Oh-Keol;Lee, Jang-Myung
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.240-243
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    • 2003
  • In this study, as the preliminary step far developing a multi-purpose Autonomous robust carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as sonar, IR sensor for map-building mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. Smart sensory systems are crucial for successful autonomous systems. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions recognizing environments updated, obstacle detection and motion assessment, with the first results from the simulations run.

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실내 자율주행에 적합한 SLAM과 전역경로생성 방법을 적용한 휠체어로봇 구현 (Implementation of Wheelchair Robot Applying SLAM and Global Path Planning Methods Suitable for Indoor Autonomous Driving)

  • 백수진;김아현;김종욱
    • 대한임베디드공학회논문지
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    • 제16권6호
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    • pp.293-297
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    • 2021
  • This paper presents how to create a 3D map and solve problems related to generating a global path planning for navigation. Map creation and localization were performed using the RTAB-Map package to create a 3D map of the environment. In addition, when the target point is within the obstacle space, the problem of not generating a global path was solved using the asr_navfn package. The performance of the proposed system is validated through experiments with a wheelchair-type robot.

미지환경에서 무인이동체의 자율주행을 위한 확률기반 위치 인식과 추적 방법 (Approaches to Probabilistic Localization and Tracking for Autonomous Mobility Robot in Unknown Environment)

  • 진태석
    • 한국산업융합학회 논문집
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    • 제25권3호
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    • pp.341-347
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    • 2022
  • This paper presents a comparison result of two simultaneous localization and mapping (SLAM) algorithms for navigation that have been proposed in literature. The performances of Extended Kalman Filter (EKF) SLAM under Gaussian condition, FastSLAM algorithms using Rao-Blackwellised method for particle filtering are compared in terms of accuracy of state estimations for localization of a robot and mapping of its environment. The algorithms were run using the same type of robot on indoor environment. The results show that the Particle filter based FastSLAM has the better performance in terms of accuracy of localization and mapping. The experimental results are discussed and compared.

다수의 초음파 송수신기를 이용한 이동 로봇의 정밀 실내 위치인식 시스템의 개발 (Development of Precise Localization System for Autonomous Mobile Robots using Multiple Ultrasonic Transmitters and Receivers in Indoor Environments)

  • 김용휘;송의규;김병국
    • 제어로봇시스템학회논문지
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    • 제17권4호
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    • pp.353-361
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    • 2011
  • A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

라이다와 RGB-D 카메라를 이용하는 교육용 실내 자율 주행 로봇 시스템 (Educational Indoor Autonomous Mobile Robot System Using a LiDAR and a RGB-D Camera)

  • 이수영;김재영;조세형;신창용
    • 전기전자학회논문지
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    • 제23권1호
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    • pp.44-52
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    • 2019
  • 본 논문은 라이다 센싱 정보와 RGB-D 카메라 영상 정보를 융합하여 이용하는 교육용 실내 자율주행 로봇 시스템을 구현한다. 이 시스템은 라이다 센싱 정보를 획득하기 위해 기존의 소 채널 라이다 센싱 방식을 이용한다. 또한 소 채널 라이다 센싱 방식의 약점을 보완하기 위해, RGB-D 카메라 깊이 영상과 딥러닝 기반 객체인식 알고리즘을 이용하는 3차원 구조물 인식 방법을 제안하고 이 시스템에 적용한다.

Onboard dynamic RGB-D simultaneous localization and mapping for mobile robot navigation

  • Canovas, Bruce;Negre, Amaury;Rombaut, Michele
    • ETRI Journal
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    • 제43권4호
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    • pp.617-629
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    • 2021
  • Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.

퍼지제어기를 이용한 무인차 항법제어 (Fuzzy Logic Controller for a Mobile Robot Navigation)

  • 정학영;이장규
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.713-716
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    • 1991
  • This paper describes a methodology of mobile robot navigation which is designed to carry heavy payloads at high speeds to be used in FMS(Flexible Manufacturing System) without human control. Intelligent control scheme using fuzzy logic is applied to the navigation control. It analyzes sensor readings from multi-sensor system, which is composed of ultrasonic sensors, infrared sensors and odometer, for environment learning, planning, landmark detecting and system control. And it is implemented on a physical robot, AGV(Autonomous Guided Vehicle) which is a two-wheeled, indoor robot. An on-board control software is composed of two subsystems, i.e., AGV control subsystem and Sensor control subsystem. The results show that the navigation of the AGV is robust and flexible, and a real-time control is possible.

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