Obstacle Avoidance of Mobile Robot Based on Behavior Hierarchy by Fuzzy Logic

Jin, Tongdan

doi:10.5391/ijfis.2012.12.3.245

Cited by 23 publications

(10 citation statements)

References 9 publications

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“…The limitations of the autonomous planning methods has led researchers to study real-time planning, which is based on the knowledge gained from probing the local surroundings to handle unknown obstacles as far as the robot traverses a path in this environment [18][19][20][21]. Similar characteristics are possessed by the approach described in this section based on DWA.…”

Section: Dynamic Window Approachmentioning

confidence: 86%

3D Global Dynamic Window Approach for Navigation of Autonomous Underwater Vehicles

Tusseyeva¹,

Kim²,

Kim³

2013

International Journal of Fuzzy Logic and Intelligent Systems

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An autonomous unmanned underwater vehicle is a type of marine self-propelled robot that executes some specific mission and returns to base on completion of the task. In order to successfully execute the requested operations, the vehicle must be guided by an effective navigation algorithm that enables it to avoid obstacles and follow the best path. Architectures and principles for intelligent dynamic systems are being developed, not only in the underwater arena but also in related areas where the work does not fully justify the name. The problem of increasing the capacity of systems management is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has been implemented in indoor office robots. In this paper, the dynamic window approach is applied to the marine world by developing and extending it to manipulate vehicles in 3D marine environments. This algorithm is provided to enable efficient avoidance of obstacles and attainment of targets. Experiments conducted using the algorithm in MATLAB indicate that it is an effective obstacle avoidance approach for marine vehicles.

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Section: Dynamic Window Approachmentioning

confidence: 86%

3D Global Dynamic Window Approach for Navigation of Autonomous Underwater Vehicles

Tusseyeva¹,

Kim²,

Kim³

2013

International Journal of Fuzzy Logic and Intelligent Systems

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“…에 존재하는 장애물들의 위치 정보를 정확하게 인식하여야 한다 [1,2,3,11]. 이를 위해 이동 로봇은 초음파 센서 [4,5], 비전 센서 [6,7], 레이저 거리 측정기(레이저 레인지 파인더, Laser Range Finder) [8,9,10] (1) …”

Section: 서 론 이동 로봇의 자율 주행은 환경 내에 존재하는 장애물들 과의 충돌로부터 자유로워야 하며 이를 위해서는unclassified

Transparent Obstacle Detection Method based on Laser Range Finder

Park¹,

Jung²

2014

Journal of Korean Institute of Intelligent Systems

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Using only laser range finder to detect the obstacles in an environment that contains transparent obstacles can not guarantee autonomous mobile robot from collision problem. To solve this problem, a mobile robot using laser range finder must be used additional sensor device such as sonar sensor that can detect the transparent obstacle. In this paper, a method is addressed to deal with the problem to detect the transparent obstacles within environment only by using laser range finder for mobile robot. In case the recognized transparent obstacle, the proposed algorithm is to localize the transparent obstacle to extract and process the reflected noise. This algorithm ensures autonomous of mobile robot only using laser range finder. The effectiveness of the proposed algorithm is evaluated by the real mobile robot and real laser range finder experiments with three case studies.

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“…The dissertation [3] uses the Kinect sensor to obtain depth data and according to mobile robot and relative positions with respect to the obstacle, avoidance obstacle path planning is given. The method described in article [4] gets a more accurate localization by using a kind of local map updating method based on statistical theory. It is studied in this article [5] that the artificial potential field method applied to path planning problem for unmanned vehicles.…”

Section: Introductionmentioning

confidence: 99%

Obstacle Avoidance for AGV with Kinect Sensor

Han

Wang²

2016

IJSH

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This paper aims the development of autonomous obstacle avoidance algorithm for automated guided vehicle with a Kinect sensor. To do this task, the followings are executed. Firstly, depth data is obtained from the Kinect sensor, and the mean filter approach is developed to filter out noises. Secondly, Otsu and U-V parallax based method is designed to identify background and obstacles. Finally, According to barrier information, corresponding fuzzy control rules is generated for the path planning. Our experiments show that the proposed method is fast, and gives promising results.

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Obstacle Avoidance of Mobile Robot Based on Behavior Hierarchy by Fuzzy Logic

Cited by 23 publications

References 9 publications

3D Global Dynamic Window Approach for Navigation of Autonomous Underwater Vehicles

3D Global Dynamic Window Approach for Navigation of Autonomous Underwater Vehicles

Transparent Obstacle Detection Method based on Laser Range Finder

Obstacle Avoidance for AGV with Kinect Sensor

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