Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment

Obstacle avoidance is a key performance of mobile robots. However, its experimental verification is rather difficult, due to the probabilistic behaviors of both the robots and the obstacles. This paper presents the Markov Decision Process based probabilistic formal models for three obstacle-avoidanc...

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Main Authors: Rui Wang, Ming Wang, Yong Guan, Xiaojuan Li
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/837259
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spelling doaj-32128badf4674930b8fc9963a5ca54de2020-11-24T22:05:29ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/837259837259Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic EnvironmentRui Wang0Ming Wang1Yong Guan2Xiaojuan Li3College of Information Engineering, Capital Normal University, Beijing 100048, ChinaCollege of Information Engineering, Capital Normal University, Beijing 100048, ChinaCollege of Information Engineering, Capital Normal University, Beijing 100048, ChinaCollege of Information Engineering, Capital Normal University, Beijing 100048, ChinaObstacle avoidance is a key performance of mobile robots. However, its experimental verification is rather difficult, due to the probabilistic behaviors of both the robots and the obstacles. This paper presents the Markov Decision Process based probabilistic formal models for three obstacle-avoidance strategies of a mobile robot in an uncertain dynamic environment. The models are employed to make analyses in PRISM, and the correctness of the analysis results is verified by MATLAB simulations. Finally, the minimum time and the energy consumption are determined by further analyses in PRISM, which prove to be useful in finding the optimal strategy. The present work provides a foundation for the probabilistic formal verification of more complicated obstacle-avoidance strategies.http://dx.doi.org/10.1155/2015/837259
collection DOAJ
language English
format Article
sources DOAJ
author Rui Wang
Ming Wang
Yong Guan
Xiaojuan Li
spellingShingle Rui Wang
Ming Wang
Yong Guan
Xiaojuan Li
Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment
Mathematical Problems in Engineering
author_facet Rui Wang
Ming Wang
Yong Guan
Xiaojuan Li
author_sort Rui Wang
title Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment
title_short Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment
title_full Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment
title_fullStr Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment
title_full_unstemmed Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment
title_sort modeling and analysis of the obstacle-avoidance strategies for a mobile robot in a dynamic environment
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description Obstacle avoidance is a key performance of mobile robots. However, its experimental verification is rather difficult, due to the probabilistic behaviors of both the robots and the obstacles. This paper presents the Markov Decision Process based probabilistic formal models for three obstacle-avoidance strategies of a mobile robot in an uncertain dynamic environment. The models are employed to make analyses in PRISM, and the correctness of the analysis results is verified by MATLAB simulations. Finally, the minimum time and the energy consumption are determined by further analyses in PRISM, which prove to be useful in finding the optimal strategy. The present work provides a foundation for the probabilistic formal verification of more complicated obstacle-avoidance strategies.
url http://dx.doi.org/10.1155/2015/837259
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AT mingwang modelingandanalysisoftheobstacleavoidancestrategiesforamobilerobotinadynamicenvironment
AT yongguan modelingandanalysisoftheobstacleavoidancestrategiesforamobilerobotinadynamicenvironment
AT xiaojuanli modelingandanalysisoftheobstacleavoidancestrategiesforamobilerobotinadynamicenvironment
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