• Title/Summary/Keyword: 3D autonomous system

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Intelligent 3-D Obstacle Avoidance Algorithm for Autonomous Control of Underwater Flight Vehicle (수중비행체의 자율제어를 위한 지능형 3-D 장애물회피 알고리즘)

  • Kim, Hyun-Sik;Jin, Tae-Seok;Sur, Joo-No
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.3
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    • pp.323-328
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    • 2011
  • In real system application, the 3-D obstacle avoidance system for the autonomous control of the underwater flight vehicle (UFV) operates with the following problems: the sonar offers the range/bearing information of obstacles in a local detection area, it requires the system that has reduced acoustic noise and power consumption in terms of the autonomous underwater vehicle (AUV), it has the UFV operation constraints such as maximum pitch and depth, and it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent 3-D obstacle avoidance algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance of the proposed algorithm, the 3-D obstacle avoidance of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application.

The Development of Sensor System and 3D World Modeling for Autonomous Vehicle (무인 차량을 위한 센서 시스템 개발 및 3차원 월드 모델링)

  • Kim, Si-Jong;Kang, Jung-Won;Choe, Yun-Geun;Park, Sang-Un;Shim, In-Wook;Ahn, Seung-Uk;Chung, Myung-Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.6
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    • pp.531-538
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    • 2011
  • This paper describes a novel sensor system for 3D world modeling of an autonomous vehicle in large-scale outdoor environments. When an autonomous vehicle performs path planning and path following, well-constructed 3D world model of target environment is very important for analyze the environment and track the determined path. To generate well-construct 3D world model, we develop a novel sensor system. The proposed novel sensor system consists of two 2D laser scanners, two single cameras, a DGPS (Differential Global Positioning System) and an IMU (Inertial Measurement System). We verify the effectiveness of the proposed sensor system through experiment in large-scale outdoor environment.

HOPF BIFURCATION OF CODIMENSION ONE AND DYNAMICAL SIMULATION FOR A 3D AUTONOMOUS CHAOTIC SYSTEM

  • Li, Xianyi;Zhou, Zhengxin
    • Bulletin of the Korean Mathematical Society
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    • v.51 no.2
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    • pp.457-478
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    • 2014
  • In this paper, a 3D autonomous system, which has only stable or non-hyperbolic equilibria but still generates chaos, is presented. This system is topologically non-equivalent to the original Lorenz system and all Lorenz-type systems. This motivates us to further study some of its dynamical behaviors, such as the local stability of equilibrium points, the Lyapunov exponent, the dissipativity, the chaotic waveform in time domain, the continuous frequency spectrum, the Poincar$\acute{e}$ map and the forming mechanism for compound structure of its special cases. Especially, with the help of the Project Method, its Hopf bifurcation of codimension one is in detailed formulated. Numerical simulation results not only examine the corresponding theoretical analytical results, but also show that this system possesses abundant and complex dynamical properties not solved theoretically, which need further attention.

Positioning Accuracy on Robot Self-localization by Real-time Indoor Positioning System with SS Ultrasonic Waves

  • Suzuki, Akimasa;Kumakura, Ken;Tomizuka, Daisuke;Hagiwara, Yoshinobu;Kim, Youngbok;Choi, Yongwoon
    • Journal of Power System Engineering
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    • v.17 no.5
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    • pp.100-111
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    • 2013
  • Indoor real-time positioning for multiple targets is required to realize human-robot symbiosis. This study firstly presents positioning accuracy on an autonomous mobile robot controlled by 3-D coordinates that is obtained by a real-time indoor positioning system with spread spectrum (SS) ultrasonic signals communicated by code-division multiple access. Although many positioning systems have been investigated, the positioning system with the SS ultrasonic signals can measure identified multiple 3-D positions in every 70 ms with noise tolerance and error within 100 mm. This system is also robust to occlusion and environmental changes. However, thus far, the positioning errors in an autonomous mobile robot, controlled by these systems using the SS ultrasonic signals, have not been evaluated as an experimental study. Therefore, a positioning experiment for trajectory control is conducted using an autonomous mobile robot and our positioning system. The effectiveness of this positioning method for robot self-localization is shown, from this experiment, because the average control error between the target position and the robot's position at 29 mm is obtained.

3D Map Generation System for Indoor Autonomous Navigation (실내 자율 주행을 위한 3D Map 생성 시스템)

  • Moon, SungTae;Han, Sang-Hyuck;Eom, Wesub;Kim, Youn-Kyu
    • Aerospace Engineering and Technology
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    • v.11 no.2
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    • pp.140-148
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    • 2012
  • For autonomous navigation, map, pose tracking, and finding the shortest path are required. Because there is no GPS signal in indoor environment, the current position should be recognized in the 3D map by using image processing or something. In this paper, we explain 3D map creation technology by using depth camera like Kinect and pose tracking in 3D map by using 2D image taking from camera. In addition, the mechanism of avoiding obstacles is discussed.

Map Building Based on Sensor Fusion for Autonomous Vehicle (자율주행을 위한 센서 데이터 융합 기반의 맵 생성)

  • Kang, Minsung;Hur, Soojung;Park, Ikhyun;Park, Yongwan
    • Transactions of the Korean Society of Automotive Engineers
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    • v.22 no.6
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    • pp.14-22
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    • 2014
  • An autonomous vehicle requires a technology of generating maps by recognizing surrounding environment. The recognition of the vehicle's environment can be achieved by using distance information from a 2D laser scanner and color information from a camera. Such sensor information is used to generate 2D or 3D maps. A 2D map is used mostly for generating routs, because it contains information only about a section. In contrast, a 3D map involves height values also, and therefore can be used not only for generating routs but also for finding out vehicle accessible space. Nevertheless, an autonomous vehicle using 3D maps has difficulty in recognizing environment in real time. Accordingly, this paper proposes the technology for generating 2D maps that guarantee real-time recognition. The proposed technology uses only the color information obtained by removing height values from 3D maps generated based on the fusion of 2D laser scanner and camera data.

Autonomous Flight System of UAV through Global and Local Path Generation (전역 및 지역 경로 생성을 통한 무인항공기 자율비행 시스템 연구)

  • Ko, Ha-Yoon;Baek, Joong-Hwan;Choi, Hyung-Sik
    • Journal of Aerospace System Engineering
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    • v.13 no.3
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    • pp.15-22
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    • 2019
  • In this paper, a global and local flight path system for autonomous flight of the UAV is proposed. The overall system is based on the ROS robot operating system. The UAV in-built computer detects obstacles through 2-D Lidar and generates real-time local path and global path based on VFH and Modified $RRT^*$-Smart, respectively. Additionally, a movement command is issued based on the generated path on the UAV flight controller. The ground station computer receives the obstacle information and generates a 2-D SLAM map, transmits the destination point to the embedded computer, and manages the state of the UAV. The autonomous UAV flight system of the is verified through a simulator and actual flight.

Image-based Localization Recognition System for Indoor Autonomous Navigation (실내 자율 비행을 위한 영상 기반의 위치 인식 시스템)

  • Moon, SungTae;Cho, Dong-Hyun;Han, Sang-Hyuck
    • Aerospace Engineering and Technology
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    • v.12 no.1
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    • pp.128-136
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    • 2013
  • Recently, the localization recognition system research has been studied using various sensors according to increased interest in autonomous navigation flight. In case of indoor environment which cannot support GPS information, we have to look for another way to recognize current position. The Image-based localization recognition system has been interested although there are lots of way to know current pose. In this paper, we explain the localization recognition system based on mark and implementation of autonomous navigation flight. In order to apply to real environment which cannot support marks, localization based on real-time 3D map building is discussed.

A Study on Real-time Autonomous Driving Simulation System Construction based on Digital Twin - Focused on Busan EDC - (디지털트윈 기반 실시간 자율주행 시뮬레이션 시스템 구축 방안 연구 - 부산 EDC 중심으로 -)

  • Kim, Min-Soo;Park, Jong-Hyun;Sim, Min-Seok
    • Journal of Cadastre & Land InformatiX
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    • v.53 no.2
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    • pp.53-66
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    • 2023
  • Recently, there has been a significant interest in the development of autonomous driving simulation environment based on digital twin. In the development of such digital twin-based simulation environment, many researches has been conducted not only performance and functionality validation of autonomous driving, but also generation of virtual training data for deep learning. However, such digital twin-based autonomous driving simulation system has the problem of requiring a significant amount of time and cost for the system development and the data construction. Therefore, in this research, we aim to propose a method for rapidly designing and implementing a digital twin-based autonomous driving simulation system, using only the existing 3D models and high-definition map. Specifically, we propose a method for integrating 3D model of FBX and NGII HD Map for the Busan EDC area into CARLA, and a method for adding and modifying CARLA functions. The results of this research show that it is possible to rapidly design and implement the simulation system at a low cost by using the existing 3D models and NGII HD map. Also, the results show that our system can support various functions such as simulation scenario configuration, user-defined driving, and real-time simulation of traffic light states. We expect that usability of the system will be significantly improved when it is applied to broader geographical area in the future.

Development of Low Cost Autonomous-Driving Delivery Robot System Using SLAM Technology (SLAM 기술을 활용한 저가형 자율주행 배달 로봇 시스템 개발)

  • Donghoon Lee;Jehyun Park;Kyunghoon Jung
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.5
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    • pp.249-257
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    • 2023
  • This paper discusses the increasing need for autonomous delivery robots due to the current growth in the delivery market, rising delivery fees, high costs of hiring delivery personnel, and the need for contactless services. Additionally, the cost of hardware and complex software systems required to build and operate autonomous delivery robots is high. To provide a low-cost alternative to this, this paper proposes a autonomous delivery robot platform using a low-cost sensor combination of 2D LIDAR, depth camera and tracking camera to replace the existing expensive 3D LIDAR. The proposed robot was developed using the RTAB-Map SLAM open source package for 2D mapping and overcomes the limitations of low-cost sensors by using the convex hull algorithm. The paper details the hardware and software configuration of the robot and presents the results of driving experiments. The proposed platform has significant potential for various industries, including the delivery and other industries.