• Title/Summary/Keyword: Cluttered Environment

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The Improvement of the Highest Probability Data Association algorithm with Limited Measurement Numbers(HPDA-LIMN) in the Validation Gate (측정치 개수 제한기법을 이용한 HPDA 알고리즘 성능향상 연구)

  • Lim, Young-Taek;Hong, Young-Ki
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.5
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    • pp.812-817
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    • 2011
  • In this paper, we propose new data association method called the Highest Probability Data Association with Limited Measurement Numbers(HPDA-LIMN) using a Signal Itensity Ordering method applied to tracking in clutter environment. The performance of HPDA-LIMN algorithm is tested in a series of Monte Carlo simulations runs and is compared with the exiting data association method in cluttered environment.

Real-time obstacle avoidance for mobile robot (이동 로봇을 위한 실시간 충돌 회피)

  • 범희락;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.658-662
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    • 1991
  • In this paper, a real-time obstacle avoidance for mobile robot based on the readings of the ultrasonic sensors is presented. The twenty eight ultrasonic sensors are arranged in ring and controlled by microprocessor. The readings of the ultrasonic sensor is converted into the virtual forces called repulsive forces, which are the elastic and damping forces. Then, the direction and speed of mobile robot in the cluttered environment are determined by the virtual forces. The effectiveness of the proposed method is verified from a series of simulation studies.

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Integration of Condensation and Mean-shift algorithms for real-time object tracking (실시간 객체 추적을 위한 Condensation 알고리즘과 Mean-shift 알고리즘의 결합)

  • Cho Sang-Hyun;Kang Hang-Bong
    • The KIPS Transactions:PartB
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    • v.12B no.3 s.99
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    • pp.273-282
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    • 2005
  • Real-time Object tracking is an important field in developing vision applications such as surveillance systems and vision based navigation. mean-shift algerian and Condensation algorithm are widely used in robust object tracking systems. Since the mean-shift algorithm is easy to implement and is effective in object tracking computation, it is widely used, especially in real-time tracking systems. One of the drawbacks is that it always converges to a local maximum which may not be a global maximum. Therefore, in a cluttered environment, the Mean-shift algorithm does not perform well. On the other hand, since it uses multiple hypotheses, the Condensation algorithm is useful in tracking in a cluttered background. Since it requires a complex object model and many hypotheses, it contains a high computational complexity. Therefore, it is not easy to apply a Condensation algorithm in real-time systems. In this paper, by combining the merits of the Condensation algorithm and the mean-shift algorithm we propose a new model which is suitable for real-time tracking. Although it uses only a few hypotheses, the proposed method use a high-likelihood hypotheses using mean-shift algorithm. As a result, we can obtain a better result than either the result produced by the Condensation algorithm or the result produced by the mean-shift algorithm.

Kinodynamic Motion Planning with Artificial Wavefront Propagation

  • Ogay, Dmitriy;Kim, Eun-Gyung
    • Journal of information and communication convergence engineering
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    • v.11 no.4
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    • pp.274-281
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    • 2013
  • In this study, we consider the challenges in motion planning for automated driving systems. Most of the existing online motion-planning algorithms, which take dynamics into account, find it difficult to operate in an environment with narrow passages. Some of the existing algorithms overcome this by offline preprocessing if environment is known. In this work an online algorithm for motion planning with dynamics in an unknown cluttered environment with narrow passages is presented. It utilizes an idea of hybrid planning with sampling- and discretization-based motion planners, which run simultaneously in a full configuration space and a derived reduced space. The proposed algorithm has been implemented and tested with a real autonomous vehicle. It provides significant improvements in computational time performance over basic planning algorithms and allows the generation of smoother paths than those generated by the recently developed hybrid motion planners.

A Study on the Zen Style in Interior Architect - Focused on the Image of Space - (실내 건축 디자인에 있어서 '선'(Zen) 스타일에 관한 연구 - 공간이미지를 중심으로-)

  • 김미옥
    • Korean Institute of Interior Design Journal
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    • no.38
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    • pp.91-99
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    • 2003
  • In the philosophical sense, aZen teacher would probably say there is no answer to the Question. Whatnis Zen\ulcorner Zen is an approach to life, a way of being , rather then a philisophy or set doctrine. Modern living people quest for peace and tranquility has led designers and decorators to look to East to the natural harmony and blance of Asian home and to the simpicity of their art and design. Zen style interiors are simplicity and serenity. These imply the paring down of a cluttered environment and concentration on creating harmony. balance, touch, and texture. By achieving these things you can create a place where the spiritual or inner needs can be addressed and where you can indulge in calming or stimulating the senses with light, space, and free flow of energy In Zen interior we approach 'Homoㆍaesthetcus' by feeling and' Homoㆍreligious' by mind. "Less is more", this phrase has made the pared down environment an interior form.

A Study of Automatic Multi-Target Detection and Tracking Algorithm using Highest Probability Data Association in a Cluttered Environment (클러터가 존재하는 환경에서의 HPDA를 이용한 다중 표적 자동 탐지 및 추적 알고리듬 연구)

  • Kim, Da-Soul;Song, Taek-Lyul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.10
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    • pp.1826-1835
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    • 2007
  • In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

A Study of Image Target Tracking Using ITS in an Occluding Environment (표적이 일시적으로 가려지는 환경에서 ITS 기법을 이용한 영상 표적 추적 알고리듬 연구)

  • Kim, Yong;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.4
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    • pp.306-314
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    • 2013
  • Automatic tracking in cluttered environment requires the initiation and maintenance of tracks, and track existence probability of true track is kept by Markov Chain Two model of target existence propagation. Unlike Markov Chain One model for target existence propagation, Markov Chain Two model is made up three hypotheses about target existence event which are that the target exist and is detectable, the target exists and is non-detectable through occlusion, and the target does not exist and is non-detectable according to non-existing target. In this paper we present multi-scan single target tracking algorithm based on the target existence, which call the Integrated Track Splitting algorithm with Markov Chain Two model in imaging sensor.

2D Planar Object Tracking using Improved Chamfer Matching Likelihood (개선된 챔퍼매칭 우도기반 2차원 평면 객체 추적)

  • Oh, Chi-Min;Jeong, Mun-Ho;You, Bum-Jae;Lee, Chil-Woo
    • The KIPS Transactions:PartB
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    • v.17B no.1
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    • pp.37-46
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    • 2010
  • In this paper we have presented a two dimensional model based tracking system using improved chamfer matching. Conventional chamfer matching could not calculate similarity well between the object and image when there is very cluttered background. Then we have improved chamfer matching to calculate similarity well even in very cluttered background with edge and corner feature points. Improved chamfer matching is used as likelihood function of particle filter which tracks the geometric object. Geometric model which uses edge and corner feature points, is a discriminant descriptor in color changes. Particle Filter is more non-linear tracking system than Kalman Filter. Then the presented method uses geometric model, particle filter and improved chamfer matching for tracking object in complex environment. In experimental result, the robustness of our system is proved by comparing other methods.

Track Initiation and Target Tracking Filter Using LiDAR for Ship Tracking in Marine Environment (해양환경에서 선박 추적을 위한 라이다를 이용한 궤적 초기화 및 표적 추적 필터)

  • Fang, Tae Hyun;Han, Jungwook;Son, Nam-Sun;Kim, Sun Young
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.2
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    • pp.133-138
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    • 2016
  • This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.

Reliable Navigation of a Mobile Robot in Cluttered Environment by Combining Evidential Theory and Fuzzy Controller (추론 이론과 퍼지 컨트롤러 결합에 의한 이동 로봇의 자유로운 주변 환경 인식)

  • 김영철;조성배;오상록
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.136-139
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    • 2001
  • This paper develops a sensor based navigation method that utilizes fuzzy logic and the Dempster-Shafer evidence theory for mobile robot in uncertain environment. The proposed navigator consists of two behaviors: obstacle avoidance and goal seeking. To navigate reliably in the environment, we make a map building process before the robot finds a goal position and create a robust fuzzy controller. In this paper, the map is constructed on a two-dimensional occupancy grid. The sensor readings are fused into the map using D-S inference rule. Whenever the robot moves, it catches new information about the environment and replaces the old map with new one. With that process the robot can go wandering and finding the goal position. The usefulness of the proposed method is verified by a series of simulations. This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper.

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