• Title/Summary/Keyword: 로봇차량

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Improvement of odometry accuracy and Parking Control for a Car-Like Mobile Robot (차량형 이동로봇의 위치 추정 정밀도 향상 기법 및 자동 주차 제어)

  • Lee, Kook-Tae;Chung, Woo-Jin;Chang, Hyo-Whan
    • The Journal of Korea Robotics Society
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    • v.3 no.1
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    • pp.16-22
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    • 2008
  • Recently, automatic parking assist systems are commercially available in some cars. In order to improve the reliability and the accuracy of parking control, pose uncertainty of a vehicle and some experimental issues should be solved. In this paper, following three schemes are proposed. (1) Odometry calibration scheme for the Car-Like Mobile Robot.(CLMR) (2) Accurate localization using Extended Kalman Filter(EKF) based redundant odometry fusion. (3) Trajectory tracking controller to compensate the tracking error of the CLMR. The proposed schemes are experimentally verified using a miniature Car-Like Mobile Robot. This paper shows that odometry accuracy and trajectory tracking performance can be dramatically improved by using the proposed schemes.

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Comparisonal Analysis of Path Planning Methods for Automatic Parking Control of a Car-Like Mobile Robot (자동주차를 위한 차량형 자율주행 로봇에 적합한 경로계획법의 비교분석)

  • Kwon, Hyun-Ki;Chung, Woo-Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.3
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    • pp.267-274
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    • 2012
  • We proposed the KPP (Korea university Path Planner) in our previous works. The KPP is the path planning scheme of a car-like mobile robot in parking environment. The objective of this paper is to investigate the advantage of the KPP through the quantitative and qualitative analysis compared with conventional RRT. For comparison, we proposed travel time for performance index. This paper shows that the KPP shows outstanding performances from the viewpoint of travel time and computational efficiency compared with RRT.

Development Based on Signal Processing Platform for Automotive UWB Radar System (차량용 UWB 레이다를 위한 DSP 기반의 신호처리 모듈 플랫폼 개발)

  • Ju, Yeonghwan;Kim, Sang-Dong;Lee, Jong-Hun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.6 no.5
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    • pp.319-325
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    • 2011
  • Recently, collision avoidance systems are under development to reduce the traffic accidents and driver comfort for automotive radar. Pulse radar can detect their range and velocities of moving vehicles using range gate and FFT(Fast Fourier Transform) of the doppler frequency. We designed the real time DSP(Digital Signal Processing) based automotive UWB(Ultra Wideband) radar, and implemented DSP to detect the range and velocity within 100ms for real time system of the automotive UWB radar. We also measured the range and velocity of a moving vehicle using designed automotive UWB radar in a real road environment.

Lane Map-based Vehicle Localization for Robust Lateral Control of an Automated Vehicle (자율주행 차량의 강건한 횡 방향 제어를 위한 차선 지도 기반 차량 위치추정)

  • Kim, Dongwook;Jung, Taeyoung;Yi, Kyong-Su
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.2
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    • pp.108-114
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    • 2015
  • Automated driving systems require a high level of performance regarding environmental perception, especially in urban environments. Today's on-board sensors such as radars or cameras do not reach a satisfying level of development from the point of view of robustness and availability. Thus, map data is often used as an additional data input to support these systems. An accurate digital map is used as a powerful additional sensor. In this paper, we propose a new approach for vehicle localization using a lane map and a single-layer LiDAR. The maps are created beforehand using a highly accurate DGPS and a single-layer LiDAR. A pose estimation of the vehicle was derived from an iterative closest point (ICP) match of LiDAR's intensity data to the lane map, and the estimated pose was used as an observation inside a Kalmanfilter framework. The achieved accuracy of the proposed localization algorithm is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control.

Accurate Parked Vehicle Detection using GMM-based 3D Vehicle Model in Complex Urban Environments (가우시안 혼합모델 기반 3차원 차량 모델을 이용한 복잡한 도시환경에서의 정확한 주차 차량 검출 방법)

  • Cho, Younggun;Roh, Hyun Chul;Chung, Myung Jin
    • The Journal of Korea Robotics Society
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    • v.10 no.1
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    • pp.33-41
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    • 2015
  • Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

Improvement of Washout Algorithm for Vehicle Driving Simulator Using Vehicle Tilt Data and Its Evaluation (차량 기울기값을 이용한 차량 시a레이터용 워시아웃 알고리즘에 대한 개선 및 평가)

  • Moon, Young-Geun;Kim, Moon-Sik;Kim, Kyung-Dal;Lee, Min-Cheol
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.8
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    • pp.823-830
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    • 2009
  • For developing automotive parts and telematics devices the real car test often shows limitation because it needs high cost, much time and has the possibility of the accident. Therefore, a Vehicle Driving Simulator (VDS) instead of the real-car test has been used by some automotive manufactures, research centers, and universities. The VDS is a virtual reality device which makes a human being feel as if one drives a vehicle actually. Unlike actual vehicle, the simulator has limited kinematic workspace and bounded dynamic characteristics. So it is difficult to simulate dynamic motions of a multi-body vehicle model fully. In order to overcome these problems, a washout algorithm which restricts workspace of the simulator within the kinematic limits is needed, and analysis of dynamic characteristics is required also. However, a classical washout algorithm contains several problems such as time delay and generation of wrong motion signal caused by characteristics of filters. Specially, the classical washout algorithm has the simulator sickness when driver hardly turns brakes and accelerates the VDS. In this paper, a new washout algorithm is developed to enhance the motion sensitivity and improve the simulator sickness by using the vehicle tilt signal which is generated in the real time vehicle dynamic model.

A Study on Vehicle Ego-motion Estimation by Optimizing a Vehicle Platform (차량 플랫폼에 최적화한 자차량 에고 모션 추정에 관한 연구)

  • Song, Moon-Hyung;Shin, Dong-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.9
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    • pp.818-826
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    • 2015
  • This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

Research of Vehicles Longitudinal Adaptive Control using V2I Situated Cognition based on LiDAR for Accident Prone Areas (LiDAR 기반 차량-인프라 연계 상황인지를 통한 사고다발지역에서의 차량 종방향 능동제어 시스템 연구)

  • Kim, Jae-Hwan;Lee, Je-Wook;Yoon, Bok-Joong;Park, Jae-Ung;Kim, Jung-Ha
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.5
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    • pp.453-464
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    • 2012
  • This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.

Experimental Studies of Controller Design for a Car-like Balancing Robot with a Variable Mass (무게 변화에 따른 차륜형 밸런싱 로봇의 제어기 설계 및 실험연구)

  • Kim, Hyun-Wook;Jung, Seul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.4
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    • pp.469-475
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    • 2010
  • This paper presents controller design of a two wheeled mobile inverted pendulum robot for one man transportation vehicle. Since the overall mass is varying with different drivers, suitable controller gains are obtained through experimental studies. Variation of the center of gravity due to different masses also affects stable balancing control. Thus, the desired balancing angle si required to be modified with respect to different masses. To measure masses for different drivers, a weight scale is used and those data are used for balancing control through communication. The gain scheduling method of using data obtained from experimental studies allows the robot to have stable balancing performances.

Navigation of Unmanned Vehicle Using Relative Localization and Magnetic Guidance (상대위치인식과 자계안내를 이용한 무인주행차량의 주행기법)

  • Lee, Yong-Jun;Ryoo, Young-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.4
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    • pp.430-435
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    • 2011
  • In this paper, a navigation technology of an unmanned vehicle using relative localization and magnetic guidance is proposed. Magnetic guidance system had been developed as a robust autonomous driving technology as long as magnetic fields on the path are detected. Otherwise, if magnetic fields were not detected due to some reasons, the vehicle could not drive. Therefore, in order to overcome the drawback, we propose that relative localization would be combined to magnetic guidance system. To validate the usefulness of the proposed method, a robotic vehicle was set up with the magnetic guidance system and the relative localization. In addition, the unmanned driving test was realized on the road without the magnetic fields so that the proposed method is verified by the experiment.