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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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2015/837259 |
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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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