• Title/Summary/Keyword: 자율주행 로봇

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A Method of Collision Avoidance for Autonomous Mobile Robot using the antenna, IR and ultrasonic (로봇의 자율 주행을 위한 더듬이, IR 및 초음파 센서를 이용한 충돌 회피 방법)

  • Shin, Seung-A;No, In-Ho;Hwang, Taehyun;Shin, Seok Hoon;Shim, Joobo;Oh, Mi Sun;Ko, Jooyoung;Shim, Jaechang
    • Journal of Korea Multimedia Society
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    • v.15 no.10
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    • pp.1236-1246
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    • 2012
  • Autonomous mobile robot has ability to move itself so it can access to danger area or narrow place, and send acquired data by sensors at the same time. In order to drive to directed place, it should progress to the destination without any collision to other robot. In this study, we built and realized the collision avoidance system for autonomous mobile robot. By using antenna, IR and ultrasonic Sensors for collision avoidance, we made it possible to sense the attached and long-distance obstacle, and can avoid. Also, we used wired and wireless network to send the data after the mission.

Implementation of autonomous driving algorithm and monitoring application for terrain navigation (지형 탐색 자율주행 알고리즘과 모니터링 애플리케이션 구현)

  • Kang, Jongwon;Jeon, Il-Soo;Kim, Myung-Sik;Lim, Wansu
    • Journal of IKEEE
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    • v.25 no.3
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    • pp.437-444
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    • 2021
  • In this paper, we propose an autonomous driving algorithm that allows a robot to explore various terrains, and implement an application that can monitor the robot's movement path during terrain search. The implemented application consists of a status unit that indicates the position, direction, speed, and motion of the mobile robot, a map unit that displays terrain information obtained through terrain search, and a control unit that controls the movement of the mobile robot. In order to control the movement of the robot, only the start and stop of the search/return is commanded by the application, and all driving for the search is performed autonomously. The basic algorithm for terrain search uses an infrared sensor to check for obstacles in the order of left, front, right, and rear, and if there is no obstacle and the path traveled is a dead end, it returns to the previous position and moves in the other direction to continue the search. Repeat the process to explore the terrain.

A Navigation Algorithm for Mobile Robots in Unknown Environments (미지 환경에서 이동로봇의 주행 알고리즘)

  • Yi Hyun-Jae;Choi Young-Kiu
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.3
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    • pp.275-284
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    • 2006
  • This paper deals with problems of safe and efficient navigation algorithm for autonomous mobile robots in unknown environments. Since the obstacle avoidance algorithms are very important in mobile robot navigation, two obstacle avoidance algorithms: VFH(vector field histogram) algorithm and a fuzzy algorithm are combined to have optimal performance in various environments. And a upper-level supervisor is to select the proper one from VFH algorithm and the fuzzy algorithm according to the situations the robot faces. Computer simulation results show the effectiveness of the proposed navigation algorithm for autonomous mobile robots.

Multiple Objects Detection using Super-Resolution Method with Two Discriminators (두 개의 구분자 기반의 초해상화 기법을 이용한 다중객체 검출 방법)

  • Kim, Jin-Seo;Jung, Young-Min;Hwang, Seong-Bin;Kwon, Oh-Seol
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.11a
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    • pp.82-84
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    • 2022
  • 최근 자율주행에서 안전한 주행을 위해 영상 기반 다중객체 검출 기술이 활발히 연구되고 있다. 이때, 저해상도 영상은 객체 검출 단계에서 정확도가 떨어지는 한계가 있다. 본 논문에서는 이러한 문제점을 해결하기 위해 초해상화와 객체 검출을 위한 방법을 함께 사용하는 기법을 제안한다. 더 나아가 초해상화 단계에서 하나의 구분자만 사용하는 기존의 방법과 다르게 이미지 생성 과정 중간에서 추가의 구분자를 사용하여 총 두 개의 구분자를 사용하여 성능을 향상하고자 하였다. 본 논문은 한국 고속도로 교통 데이터를 사용하여 실험하였으며, 그 결과 제안된 방법의 성능이 mAP@0.5 및 F1 점수 측면에서 기존 방법보다 우수하다는 것을 확인하였다.

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Evaluation of a Deblur Deep Learning Model for Image Registration Collected from Robots and Drones (로봇 및 드론 센서로 수집한 이미지 정합을 위한 Deblur 딥러닝 모델 평가)

  • Lee, Hye-min;Kwon, Hye-min;Moon, Hansol;Lee, Chang-kyo;Seo, Jeongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.153-155
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    • 2022
  • Recently, we are using robots and drones to collect images. However, as the robot or drone is shaken by external influences, pre-processing technology to register images is required. Therefore, in this paper, we use autonomous robots, drones dataset and improve the quality of shaken image data through the Deblur deep learning model. We confirmed through the experimental results that the shaken images were registered and evaluated the model.

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Development of Hand-Controlled Transportation Robot (손동작으로 제어 가능한 운송 로봇 개발)

  • Lee, In-kyu;Cho, Young-jun;Kang, Jeong-seok;Lee, Yun-jae;Yoo, Hongseok
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.481-482
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    • 2022
  • 본 논문에서는 손동작으로 제어 가능한 운송 로봇을 제안한다. 제안한 시스템에서 로봇은 MediaPipe를 이용하여 실시간으로 사람의 손동작을 인식한다. 또한, 동시적 위치 추적 지도 작성 기법인 SLAM(Simultaneous Localization and Mapping) 기술을 이용하여 로봇이 실내 공간에서 길을 찾고 자율적으로 이동할 수 있게 한다. 개발된 로봇실험을 통하여 로봇이 실시간으로 손동작을 인식하고 동작을 제어하는 것을 확인하였다. 또한, 사전에 작성된 지도를 바탕으로 실내에서 로봇이 자율주행을 하는 것을 확인하였다.

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Development of a RLS based Adaptive Sliding Mode Observer for Unknown Fault Reconstruction of Longitudinal Autonomous Driving (종방향 자율주행의 미지 고장 재건을 위한 순환 최소 자승 기반 적응형 슬라이딩 모드 관측기 개발)

  • Oh, Sechan;Song, Taejun;Lee, Jongmin;Oh, Kwangseok;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.1
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    • pp.14-25
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    • 2021
  • This paper presents a RLS based adaptive sliding mode observer (A-SMO) for unknown fault reconstruction in longitudinal autonomous driving. Securing the functional safety of autonomous vehicles from unexpected faults of sensors is essential for avoidance of fatal accidents. Because the magnitude and type of the faults cannot be known exactly, the RLS based A-SMO for unknown acceleration fault reconstruction has been designed with relationship function in this study. It is assumed that longitudinal acceleration of preceding vehicle can be obtained by using the V2V (Vehicle to Vehicle) communication. The kinematic model that represents relative relation between subject and preceding vehicles has been used for fault reconstruction. In order to reconstruct fault signal in acceleration, the magnitude of the injection term has been adjusted by adaptation rule designed based on MIT rule. The proposed A-SMO in this study was developed in Matlab/Simulink environment. Performance evaluation has been conducted using the commercial software (CarMaker) with car-following scenario and evaluation results show that maximum reconstruction error ratios exist within range of ±10%.

Development of Interior Self-driving Service Robot Using Embedded Board Based on Reinforcement Learning (강화학습 기반 임베디드 보드를 활용한 실내자율 주행 서비스 로봇 개발)

  • Oh, Hyeon-Tack;Baek, Ji-Hoon;Lee, Seung-Jin;Kim, Sang-Hoon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.537-540
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    • 2018
  • 본 논문은 Jetson_TX2(임베디드 보드)의 ROS(Robot Operating System)기반으로 맵 지도를 작성하고, SLAM 및 DQN(Deep Q-Network)을 이용한 목적지까지의 이동명령(목표 선속도, 목표 각속도)을 자이로센서로 측정한 현재 각속도를 이용하여 Cortex-M3의 기반의 MCU(Micro Controllor Unit)에 하달하여 엔코더(encoder) 모터에서 측정한 현재 선속도와 자이로센서에서 측정한 각속도 값을 이용하여 PID제어를 통한 실내 자율주행 서비스 로봇.