• 제목/요약/키워드: autonomous robot localization

검색결과 131건 처리시간 0.021초

이동로봇의 위치추정 성능개선을 위한 센서융합기법에 관한 연구 (A Study on the Sensor Fusion Method to Improve Localization of a Mobile Robot)

  • 장철웅;정기호;공정식;장문석;권오상;이응혁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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    • pp.317-318
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    • 2007
  • One of the important factors of the autonomous mobile robot is to build a map for surround environment and estimate its localization. This paper suggests a sensor fusion method of laser range finder and monocular vision sensor for the simultaneous localization and map building. The robot observes the comer points in the environment as features using the laser range finder, and extracts the SIFT algorithm with the monocular vision sensor. We verify the improved localization performance of the mobile robot from the experiment.

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영상 및 거리정보 융합을 이용한 이동로봇의 위치 인식 및 오차 보정에 관한 연구 (A study on localization and compensation of mobile robot using fusion of vision and ultrasound)

  • 장철웅;정기호;정대섭;류제군;심재홍;이응혁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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    • pp.554-556
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    • 2006
  • A key component for autonomous mobile robot is to localize ifself. In this paper we suggest a vision-based localization and compensation of robot's location using ultrasound. Mobile robot travels along wall and searches each feature in indoor environment and transformed absolute coordinates of actuality environment using these points and builds a map. And we obtain information of the environment because mobile robot travels along wall. Localzation search robot's location candidate point by ultrasound and decide position among candidate point by features matching.

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실내 물류 환경에서 라이다-카메라 약결합 기반 맵핑 및 위치인식과 네비게이션 방법 (Loosely Coupled LiDAR-visual Mapping and Navigation of AMR in Logistic Environments)

  • 최병희;강경수;노예진;조영근
    • 로봇학회논문지
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    • 제17권4호
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    • pp.397-406
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    • 2022
  • This paper presents an autonomous mobile robot (AMR) system and operation algorithms for logistic and factory facilities without magnet-lines installation. Unlike widely used AMR systems, we propose an EKF-based loosely coupled fusion of LiDAR measurements and visual markers. Our method first constructs occupancy grid and visual marker map in the mapping process and utilizes prebuilt maps for precise localization. Also, we developed a waypoint-based navigation pipeline for robust autonomous operation in unconstrained environments. The proposed system estimates the robot pose using by updating the state with the fusion of visual marker and LiDAR measurements. Finally, we tested the proposed method in indoor environments and existing factory facilities for evaluation. In experimental results, this paper represents the performance of our system compared to the well-known LiDAR-based localization and navigation system.

가정용 지능형 경비 로봇 시스템 개발 (Development of an Intelligent Security Robot System for Home Surveillance)

  • 박정호;신동관;우춘규;김형철;권용관;최병욱
    • 제어로봇시스템학회논문지
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    • 제13권8호
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    • pp.810-816
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    • 2007
  • A security robot system named EGIS-SR is a mobile security robot through one of the new growth engine project in robotic industries. It allows home surveillance through an autonomous mobile platform using onboard cameras and wireless security sensors. EGIS-SR has many sensors to allow autonomous navigation, hierarchical control architecture to handle lots of situations in monitoring home surveillance and mighty networks to achieve unmanned security services. EGIS-SR is tightly coupled with a networked security environment, where the information of the robot is remotely connected with the remote cockpit and patrol man. It achieved an intelligent unmanned security service. The robot is a two-wheeled mobile robot and has casters and suspension to overcome a doorsill. The dynamic motion is verified through $ADAMS^{TM}$ simulation. For the main controller, PXA270 based hardware platform based on linux kernel 2.6 is developed. In the linux platform, data handling for various sensors and the localization algorithm are performed. Also, a local path planning algorithm for object avoidance with ultrasonic sensors and localization using $StarGazer^{TM}$ is developed. Finally, for the automatic charging, a docking algorithm with infrared ray system is implemented.

실내 자율주행 로봇을 위한 3차원 다층 정밀 지도 구축 및 위치 추정 알고리즘 (3D Multi-floor Precision Mapping and Localization for Indoor Autonomous Robots)

  • 강규리;이대규;심현철
    • 로봇학회논문지
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    • 제17권1호
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    • pp.25-31
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    • 2022
  • Moving among multiple floors is one of the most challenging tasks for indoor autonomous robots. Most of the previous researches for indoor mapping and localization have focused on singular floor environment. In this paper, we present an algorithm that creates a multi-floor map using 3D point cloud. We implement localization within the multi-floor map using a LiDAR and an IMU. Our algorithm builds a multi-floor map by constructing a single-floor map using a LOAM-based algorithm, and stacking them through global registration that aligns the common sections in the map of each floor. The localization in the multi-floor map was performed by adding the height information to the NDT (Normal Distribution Transform)-based registration method. The mean error of the multi-floor map showed 0.29 m and 0.43 m errors in the x, and y-axis, respectively. In addition, the mean error of yaw was 1.00°, and the error rate of height was 0.063. The real-world test for localization was performed on the third floor. It showed the mean square error of 0.116 m, and the average differential time of 0.01 sec. This study will be able to help indoor autonomous robots to operate on multiple floors.

Localization Requirements for Safe Road Driving of Autonomous Vehicles

  • Ahn, Sang-Hoon;Won, Jong-Hoon
    • Journal of Positioning, Navigation, and Timing
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    • 제11권4호
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    • pp.389-395
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    • 2022
  • In order to ensure reliability the high-level automated driving such as Advanced Driver Assistance System (ADAS) and universal robot taxi provided by autonomous driving systems, the operation with high integrity must be generated within the defined Operation Design Domain (ODD). For this, the position and posture accuracy requirements of autonomous driving systems based on the safety driving requirements for autonomous vehicles and domestic road geometry standard are necessarily demanded. This paper presents localization requirements for safe road driving of autonomous ground vehicles based on the requirements of the positioning system installed on autonomous vehicle systems, the domestic road geometry standard and the dimensions of the vehicle to be designed. Based on this, 4 Protection Levels (PLs) such as longitudinal, lateral, vertical PLs, and attitude PL are calculated. The calculated results reveal that the PLs are more strict to urban roads than highways. The defined requirements can be used as a basis for guaranteeing the minimum reliability of the designed autonomous driving system on roads.

광 마우스 센서를 이용한 이동로봇 좌표추정 (Coordinate Estimation of Mobile Robot Using Optical Mouse Sensors)

  • 박상형;이수영
    • 제어로봇시스템학회논문지
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    • 제22권9호
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    • pp.716-722
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    • 2016
  • Coordinate estimation is an essential function for autonomous navigation of a mobile robot. The optical mouse sensor is convenient and cost-effective for the coordinate estimation problem. It is possible to overcome the position estimation error caused by the slip and the model mismatch of robot's motion equation using the optical mouse sensor. One of the simple methods for the position estimation using the optical mouse sensor is integration of the velocity data from the sensor with time. However, the unavoidable noise in the sensor data may deteriorate the position estimation in case of the simple integration method. In general, a mobile robot has ready-to-use motion information from the encoder sensors of driving motors. By combining the velocity data from the optical mouse sensor and the motion information of a mobile robot, it is possible to improve the coordinate estimation performance. In this paper, a coordinate estimation algorithm for an autonomous mobile robot is presented based on the well-known Kalman filter that is useful to combine the different types of sensors. Computer simulation results show the performance of the proposed localization algorithm for several types of trajectories in comparison with the simple integration method.

엘리베이터를 통한 층간 이동이 가능한 실내 자율주행 로봇용 센서 시스템 (Sensor System for Autonomous Mobile Robot Capable of Floor-to-floor Self-navigation by Taking On/off an Elevator)

  • 이민호;나건우;한승오
    • 센서학회지
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    • 제32권2호
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    • pp.118-123
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    • 2023
  • This study presents sensor system for autonomous mobile robot capable of floor-to-floor self-navigation. The robot was modified using the Turtlebot3 hardware platform and ROS2 (robot operating system 2). The robot utilized the Navigation2 package to estimate and calibrate the moving path acquiring a map with SLAM (simultaneous localization and mapping). For elevator boarding, ultrasonic sensor data and threshold distance are compared to determine whether the elevator door is open. The current floor information of the elevator is determined using image processing results of the ceiling-fixed camera capturing the elevator LCD (liquid crystal display)/LED (light emitting diode). To realize seamless communication at any spot in the building, the LoRa (long-range) communication module was installed on the self-navigating autonomous mobile robot to support the robot in deciding if the elevator door is open, when to get off the elevator, and how to reach at the destination.

전개형 생체모방로봇을 위한 안전한 자율주행시스템 설계 (Design of Safe Autonomous Navigation System for Deployable Bio-inspired Robot)

  • 최근하;한상권;이진이;이진우;안정도;김경수;김수현
    • 제어로봇시스템학회논문지
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    • 제20권4호
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    • pp.456-462
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    • 2014
  • In this paper, we present a deployable bio-inspired robot called the Pillbot-light, which utilizes a safe autonomous navigation system. The Pillbot-light is mounted the station robot, and can be operated in a disaster relief operation or military operation. However, the Pilbot-light has a challenge to navigate autonomously because the Pilbot-light cannot be equipped with various sensors. As a result, we propose a new robot system for autonomous navigation that the station robot controls Pillbot-light equipped with vision camera and CPU of high performance. This system detects obstacles based on the edge extraction using vision camera. Also, it cannot only achieve path planning using the hazard cost function, but also localization using the Particle Filter. And this system is verified by simulation and experiment.

동기 구동형 이동로봇의 자율주행을 위한 위치측정과 경로계획에 관한 연구 (A Study on the Localization Method for the Autonomous Navigation of Synchro Drive Mobile Robot)

  • 구자일;홍준표;이원석
    • 전자공학회논문지 IE
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    • 제43권1호
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    • pp.59-66
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    • 2006
  • 본 연구에서는 동기 구동형 이동 로봇의 제어를 위한 운동 방정식, 주어진 지도 내의 목표 지점으로의 최적 경로 생성과 경로 추적을 위한 경로 계획, 그리고 이동 로봇의 위치를 측정하기 위한 균등 군집 몬테카를로 위치 측정 기법을 제안하였다. 이동 로봇의 위치 측정 실험을 통해 총 73회 반복된 위치 측정에서 기존의 몬테카를로 위치 측정의 평균 수행 속도가 12.8ms로 측정된 반면, 균등 군집 관리 몬테카를로 위치 측정의 평균 수행 속도는 9.3ms로 측정되었다. 또한 기존의 몬테카를로 위치 측정 기법이 위치 측정에 실패하는 동일 환경에서 균등 군집 몬테카를로 기법은 올바른 일치 측정의 결과를 보임을 확인하였다.