• Title/Summary/Keyword: ROS(Robot Operating System)

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Motor Control via Ethernet Communication and ROS2 (ROS2 를 활용한 모터와 이더넷 통신 및 제어)

  • Dong-Jun Kim;Sung-Jun Park;Jin-Hyeok Wee;Young-Soo Do;Jae-Wook Jeon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.1137-1138
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    • 2023
  • 로봇 운영 체제인 Robot Operating System (ROS)은 다양한 로봇 프로젝트와 연구에서 광범위하게 활용되며 국제적인 활발한 커뮤니티가 형성되어 있다. 많은 로봇 기능들이 ROS 를 활용하여 개발되어왔고, 이중에서도 Fastech 사의 Ezi-SERVO II PLUS E motor driver 를 ROS 환경에서 사용할 수 있도록 개발 작업이 진행되었다. ROS 는 Linux 기반이므로, 개발 환경으로는 초보자도 다루기 쉬우면서 비교적 저렴한 소형 컴퓨터인 Raspberry Pi 를 선택하였다. 또, Raspberry Pi 는 Linux 기반의 작은 컴퓨터로, 다양한 개별 프로젝트를 수행하기 위해 많은 사람들이 활용하고 있다. 이로 인해 Raspberry Pi 로 소규모 프로젝트를 진행하는 개발자들도 해당 모터 드라이버를 Raspberry Pi 와 ROS 를 통해 쉽게 사용할 수 있게 되었다.

Development of autonomous driving route guidance robot using SLAM technology (SLAM 기술을 이용한 자율주행 경로 안내 로봇 개발)

  • Seung, Sang-jun;Lee, Ji-hwan;Jo, Min-je;Shin, Chun-ho;Kim, Do-yeon;Park, Yang-woo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.01a
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    • pp.153-154
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    • 2021
  • 본 논문에서는 ROS(Robot Operating System)를 기반으로 한 로봇(Robot)에 LiDAR 센서를 설치하여 SLAM(Simultaneous Localization and Mapping) 기술인 동시적 위치 추적 지도 작성 기법을 이용하여 실내 맵 정보를 습득하고, 이를 기반으로 장애물과 건물 실내를 안전하고 정확하게 이동할 수 있도록 하였다. 또한 로봇에 자바에서 제공하는 개발 툴킷 Swing 및 AWT 라이브러리를 이용하여 GUI(Graphical User Interface)를 구현하였고 터치스크린을 장착하여 사용자가 원하는 제품을 선택하고 선택한 제품의 목적지를 습득한 맵을 토대로 좌표 값을 설정하여 ROS에서 지원하는 이동 프로세스를 실행시켜 목적지까지 경로를 설정하고 자율 주행하게 된다.

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ROS2 공격 기술 동향 분석

  • Jaewoong Heo;Lee Yeji;Hyo Jin Jo
    • Review of KIISC
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    • v.33 no.4
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    • pp.57-63
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    • 2023
  • Industry 4.0의 진행으로 이기종의 IoT 장비들 간의 통신을 위해 다양한 산업용 통신 미들웨어들이 등장했다. 그 중 Robotics 분야에서 활발히 사용되는 Robot Operating System (ROS)는 개발자 커뮤니티와 로봇 개발 도구들을 기반으로 지속적인 시장 점유율 증가세를 보이고 있다. 초기 발표된 ROS1의 경우 보안이 전혀 고려되지 않은 설계로 Packet Injection 공격등의 사이버 보안 위협에 취약했지만, ROS2의 경우 통신 미들웨어인 Data Distribution Service (DDS) 통신규격을 전송 계층에 적용하여 메시지 전송에 대한 보안 기능을 제공하고 있다. 그러나 최근 연구에서는 DDS와 관련된 ROS2 취약점이 발표되고 있다. 따라서 본 논문에서는 DDS와 관련된 ROS2의 공격 기술 동향을 소개한다.

Development of Drone Cluster Flight Simulation using Gazebo (Gazebo를 이용한 드론 군집 비행 시뮬레이션 개발)

  • Choi, Hyo Hyun;Kim, Hyung Gyu
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.01a
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    • pp.205-206
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    • 2021
  • 본 논문에서는 ROS를 이용한 드론 군집 비행 시뮬레이션을 구현한 결과를 보인다. ROS 환경에서 Gazebo 시뮬레이션 툴과 ArduPilot을 이용하여 모델링된 드론을 Gazebo에 적용한 뒤, 프로그래밍된 명령을 적용하여 각각의 드론이 명령에 따라 제어되는 군집비행을 보인다. 시뮬레이션은 12대의 드론이 각각 cpp 파일에 따라 제어되도록 설정한 launch 파일을 roslaunch하여 설정한 모든 드론이 Gazebo에서 각각 제어되는 군집비행 시뮬레이션을 구현하였다.

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Variable Impedance Control for Industrial Manipulators Based on Sensor-Less External Force Estimator for CPPS (CPPS를 위한 산업용 매니플레이터의 힘 센서리스 외력 추정기 기반 적응 임피던스 제어)

  • Park, Jongcheon;Han, Seungyong;Jin, Yongsik;Lee, Sangmoon
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.5
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    • pp.259-267
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    • 2019
  • This paper proposes a structure of a variable impedance control system based on sensor-less external force estimator of industrial manipulators for cyber physical production systems (CPPS). To implement CPPS, a feedback system is constructed by using the robot operating system (ROS) and an external force estimator which is designed to measure the external force applied to the manipulator without a force sensor. Based on the robot dynamics, the robot-human cooperating system for the cyber physics production system is implemented through a controller that changes the impedance characteristics of the manipulator according to the situation using the external force estimator. Simulation and experimental results verify the effectiveness of the proposed control system.

Integrated System of Mobile Manipulator with Speech Recognition and Deep Learning-based Object Detection (음성인식과 딥러닝 기반 객체 인식 기술이 접목된 모바일 매니퓰레이터 통합 시스템)

  • Jang, Dongyeol;Yoo, Seungryeol
    • The Journal of Korea Robotics Society
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    • v.16 no.3
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    • pp.270-275
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    • 2021
  • Most of the initial forms of cooperative robots were intended to repeat simple tasks in a given space. So, they showed no significant difference from industrial robots. However, research for improving worker's productivity and supplementing human's limited working hours is expanding. Also, there have been active attempts to use it as a service robot by applying AI technology. In line with these social changes, we produced a mobile manipulator that can improve the worker's efficiency and completely replace one person. First, we combined cooperative robot with mobile robot. Second, we applied speech recognition technology and deep learning based object detection. Finally, we integrated all the systems by ROS (robot operating system). This system can communicate with workers by voice and drive autonomously and perform the Pick & Place task.

Development of Simulation Environment for Autonomous Driving Algorithm Validation based on ROS (ROS 기반 자율주행 알고리즘 성능 검증을 위한 시뮬레이션 환경 개발)

  • Kwak, Jisub;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.1
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    • pp.20-25
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    • 2022
  • This paper presents a development of simulation environment for validation of autonomous driving (AD) algorithm based on Robot Operating System (ROS). ROS is one of the commonly-used frameworks utilized to control autonomous vehicles. For the evaluation of AD algorithm, a 3D autonomous driving simulator has been developed based on LGSVL. Two additional sensors are implemented in the simulation vehicle. First, Lidar sensor is mounted on the ego vehicle for real-time driving environment perception. Second, GPS sensor is equipped to estimate ego vehicle's position. With the vehicle sensor configuration in the simulation, the AD algorithm can predict the local environment and determine control commands with motion planning. The simulation environment has been evaluated with lane changing and keeping scenarios. The simulation results show that the proposed 3D simulator can successfully imitate the operation of a real-world vehicle.

LiDAR based Real-time Ground Segmentation Algorithm for Autonomous Driving (자율주행을 위한 라이다 기반의 실시간 그라운드 세그멘테이션 알고리즘)

  • Lee, Ayoung;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.2
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    • pp.51-56
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    • 2022
  • This paper presents an Ground Segmentation algorithm to eliminate unnecessary Lidar Point Cloud Data (PCD) in an autonomous driving system. We consider Random Sample Consensus (Ransac) Algorithm to process lidar ground data. Ransac designates inlier and outlier to erase ground point cloud and classified PCD into two parts. Test results show removal of PCD from ground area by distinguishing inlier and outlier. The paper validates ground rejection algorithm in real time calculating the number of objects recognized by ground data compared to lidar raw data and ground segmented data based on the z-axis. Ground Segmentation is simulated by Robot Operating System (ROS) and an analysis of autonomous driving data is constructed by Matlab. The proposed algorithm can enhance performance of autonomous driving as misrecognizing circumstances are reduced.

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

  • Min-ho Lee;Kun-woo Na;Seungoh Han
    • Journal of Sensor Science and Technology
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    • v.32 no.2
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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.

Path Tracking with Nonlinear Model Predictive Control for Differential Drive Wheeled Robot (비선형 모델 예측 제어를 이용한 차동 구동 로봇의 경로 추종)

  • Choi, Jaewan;Lee, Geonhee;Lee, Chibum
    • The Journal of Korea Robotics Society
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    • v.15 no.3
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    • pp.277-285
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    • 2020
  • A differential drive wheeled robot is a kind of mobile robot suitable for indoor navigation. Model predictive control is an optimal control technique with various advantages and can achieve excellent performance. One of the main advantages of model predictive control is that it can easily handle constraints. Therefore, it deals with realistic constraints of the mobile robot and achieves admirable performance for trajectory tracking. In addition, the intention of the robot can be properly realized by adjusting the weight of the cost function component. This control technique is applied to the local planner of the navigation component so that the mobile robot can operate in real environment. Using the Robot Operating System (ROS), which has transcendent advantages in robot development, we have ensured that the algorithm works in the simulation and real experiment.