• Title/Summary/Keyword: Map-Based Control

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A Study on Visual Saliency Detection in Infrared Images Using Boolean Map Approach

  • Truong, Mai Thanh Nhat;Kim, Sanghoon
    • Journal of Information Processing Systems
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    • v.16 no.5
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    • pp.1183-1195
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    • 2020
  • Visual saliency detection is an essential task because it is an important part of various vision-based applications. There are many techniques for saliency detection in color images. However, the number of methods for saliency detection in infrared images is limited. In this paper, we introduce a simple approach for saliency detection in infrared images based on the thresholding technique. The input image is thresholded into several Boolean maps, and an initial saliency map is calculated as a weighted sum of the created Boolean maps. The initial map is further refined by using thresholding, morphology operation, and a Gaussian filter to produce the final, high-quality saliency map. The experiment showed that the proposed method has high performance when applied to real-life data.

Motion Planning and Control for Mobile Robot with SOFM

  • Yun, Seok-Min;Choi, Jin-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1039-1043
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    • 2005
  • Despite the many significant advances made in robot architecture, the basic approaches are deliberative and reactive methods. They are quite different in recognizing outer environment and inner operating mechanism. For this reason, they have almost opposite characteristics. Later, researchers integrate these two approaches into hybrid architecture. In such architecture, Reactive module also called low-level motion control module have advantage in real-time reacting and sensing outer environment; Deliberative module also called high-level task planning module is good at planning task using world knowledge, reasoning and intelligent computing. This paper presents a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provide real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework is verified by simulation.

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SLAM of a Mobile Robot using Thinning-based Topological Information

  • Lee, Yong-Ju;Kwon, Tae-Bum;Song, Jae-Bok
    • International Journal of Control, Automation, and Systems
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    • v.5 no.5
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    • pp.577-583
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    • 2007
  • Simultaneous Localization and Mapping (SLAM) is the process of building a map of an unknown environment and simultaneously localizing a robot relative to this map. SLAM is very important for the indoor navigation of a mobile robot and much research has been conducted on this subject. Although feature-based SLAM using an Extended Kalman Filter (EKF) is widely used, it has shortcomings in that the computational complexity grows in proportion to the square of the number of features. This prohibits EKF-SLAM from operating in real time and makes it unfeasible in large environments where many features exist. This paper presents an algorithm which reduces the computational complexity of EKF-SLAM by using topological information (TI) extracted through a thinning process. The global map can be divided into local areas using the nodes of a thinning-based topological map. SLAM is then performed in local instead of global areas. Experimental results for various environments show that the performance and efficiency of the proposed EKF-SLAM/TI scheme are excellent.

Design and Implementation of a Framework for Automatically Generating Control and Monitoring Software

  • Yoo, Dae-Sung;Sim, Min-Suck;Park, Sung-Ghue;Kim, Jong-Hwan;Yi, Myeong-Jae
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.932-935
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    • 2004
  • In this paper, we present a framework that is easy to develop, modify, maintain and extend a control and monitoring software for any kinds of instruments. The presented framework is composed of three XML documents (IID, MAP, and CMIML) and two tools (Virtual Instrument Wizard, Generator). Interface information about behaviors and states of instruments is written on IID. Mapping information between the interface information in IID and API of a real instrument driver is written on MAP. Finally information about control and monitoring software is written on CMIML. IID, MAP and CMIML are written with XML format to provide common usage and platform independence of the suggested framework. VI Wizard generates CMIML (platform independent intermediate document) using IID and existing CMIML, and Generator generates source code of a control and monitoring software (platform dependent code) automatically using CMIML and MAP. The suggested framework that automatically generates control and monitoring software based on GUI provides easy development and maintenance. Also, reusability can be increased by reusing platform independent software description documents.

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2D Grid Map Compensation using an ICP Algorithm (ICP 알고리즘을 이용한 2차원 격자지도 보정)

  • Lee, Dong-Ju;Hwang, Yu-Seop;Yun, Yeol-Min;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.11
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    • pp.1170-1174
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    • 2014
  • This paper suggests using the ICP (Iterative Closet Point) algorithm to compensate a two-dimensional map. ICP algorithm is a typical algorithm method using matching distance data. When building a two-dimensional map, using data through the value of a laser scanner, it occurred warping and distortion of a two-dimensional map because of the difference of distance from the value of the sensor. It uses the ICP algorithm in order to reduce any error of line. It validated the proposed method through experiment involving matching a two-dimensional map based reference data and measured the two-dimensional map.

Localization of a Monocular Camera using a Feature-based Probabilistic Map (특징점 기반 확률 맵을 이용한 단일 카메라의 위치 추정방법)

  • Kim, Hyungjin;Lee, Donghwa;Oh, Taekjun;Myung, Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.4
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    • pp.367-371
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    • 2015
  • In this paper, a novel localization method for a monocular camera is proposed by using a feature-based probabilistic map. The localization of a camera is generally estimated from 3D-to-2D correspondences between a 3D map and an image plane through the PnP algorithm. In the computer vision communities, an accurate 3D map is generated by optimization using a large number of image dataset for camera pose estimation. In robotics communities, a camera pose is estimated by probabilistic approaches with lack of feature. Thus, it needs an extra system because the camera system cannot estimate a full state of the robot pose. Therefore, we propose an accurate localization method for a monocular camera using a probabilistic approach in the case of an insufficient image dataset without any extra system. In our system, features from a probabilistic map are projected into an image plane using linear approximation. By minimizing Mahalanobis distance between the projected features from the probabilistic map and extracted features from a query image, the accurate pose of the monocular camera is estimated from an initial pose obtained by the PnP algorithm. The proposed algorithm is demonstrated through simulations in a 3D space.

A Study on the Real-Time Map Building of Mobile Robot Using Stereo Came (스테레오 비전을 이용한 이동로봇의 실시간 지도 작성을 위한 연구)

  • Sung, Yong-Won;Kim, Tae-Min;Lee, Min-Ki;Yoon, Tae-Sung
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2729-2731
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    • 2001
  • In this paper, we studied on the real-time environment map building for the mobile robot navigation using the stereo camera system. Distance measurement are necessary to build the environment map. We used a area-based stereo matching for the distance measurement with the stereo camera system. To reduce the computation time, we used DSP processor on the vision board, took a suitable area size for stereo matching, and used hierarchical search method. Using the fast acquired distance values, the environment map was built.

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dynamic localization of a mobile robot using a rotating sonar and a map (회전 초음파 센서와 지도를 이용한 이동 로보트의 동적 절대 위치 추정)

  • 양해용;정학영;이장규
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.544-547
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    • 1997
  • In this paper, we propose a dynamic localization method using a rotating sonar and a map. The proposed method is implemented by using extended Kalman filter. The state equation is based on the encoder propagation model and the encoder error model, and the measurement equation is a map-based measurement equation using a rotating sonar sensor. By utilizing sonar beam characteristics, map-based measurements are updated while AMR is moving continuously. By modeling and estimating systematic errors of a differential encoder, the position is successfully estimated even the interval of the map-based measurement. Monte-Carlo simulation shows that the proposed global position estimator has the performance of a few millimeter order in position error and of a few tenth degrees in heading error and of compensating systematic errors of the differential encoder well.

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Intensity Local Map Generation Using Data Accumulation and Precise Vehicle Localization Based on Intensity Map (데이터 누적을 이용한 반사도 지역 지도 생성과 반사도 지도 기반 정밀 차량 위치 추정)

  • Kim, Kyu-Won;Lee, Byung-Hyun;Im, Jun-Hyuck;Jee, Gyu-In
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.12
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    • pp.1046-1052
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    • 2016
  • For the safe driving of autonomous vehicles, accurate position estimation is required. Generally, position error must be less than 1m because of lane keeping. However, GPS positioning error is more than 1m. Therefore, we must correct this error and a map matching algorithm is generally used. Especially, road marking intensity map have been used in many studies. In previous work, 3D LIDAR with many vertical layers was used to generate a local intensity map. Because it can be obtained sufficient longitudinal information for map matching. However, it is expensive and sufficient road marking information cannot be obtained in rush hour situations. In this paper, we propose a localization algorithm using an accumulated intensity local map. An accumulated intensity local map can be generated with sufficient longitudinal information using 3D LIDAR with a few vertical layers. Using this algorithm, we can also obtain sufficient intensity information in rush hour situations. Thus, it is possible to increase the reliability of the map matching and get accurate position estimation result. In the experimental result, the lateral RMS position error is about 0.12m and the longitudinal RMS error is about 0.19m.

Chip Load Control Using a NC Verification Model Based on Z-Map (Z-map 기반 가공 검증모델을 이용한 칩부하 제어기)

  • Baek Dae Kyun;Ko Tae Jo;Park Jung Whan;Kim Hee Sool
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.4
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    • pp.68-75
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    • 2005
  • This paper presents a new method for the optimization of feed rate in sculptured surface machining. A NC verification model based on Z-map was utilized to obtain chip load according to feed per tooth. This optimization method can regenerate a new NC program with respect to the commanded cutting conditions and the NC program that was generated from CAM system. The regenerated NC program has not only the same data of the ex-NC program but also the updated feed rate in every block. The new NC data can reduce the cutting time and produce precision products with almost even chip load to the feed per tooth. This method can also reduce tool chipping and make constant tool wear.