JISE


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Journal of Information Science and Engineering, Vol. 33 No. 6, pp. 1531-1546


A Comparative Study on Context Assessment Approaches in Mobile Robots


MUHAMMAD AWAIS1, MUHAMMAD SHERAZ ARSHAD MALIK2,
FAZAL-E-AMIN3 AND SAMREEN NAWAZ4
1,4Department of Software Engineering
2Department of Information Technology
Government College University
Faisalabad, 33000 Pakistan
3Department of Software Engineering, Computer and Information Sciences
King Saud University
Riyadh, 11543 Saudi Arabia
Government College University Faisalabad, Pakistan
E-mail: {1muhammadawais; 2sheraz_awan}@gcuf.edu.pk; 3famin@ksu.edu.sa;
4samreennawaz1@gmail.com


    A mobile robot is an autonomous machine that is not fixed to one physical area. It has ability to move around in the environment to give versatile kind of services to user. The environmental knowledge (context assessment) is important for the successful navigation of robot in current environment. This survey aims to define clearly the meanings of context and context-aware system. We contribute a structure for the categorization of context-aware approaches within each viewpoint by studying, analyzing and comparing the existing approaches. The satisfactory characteristics of mobile robots related to context awareness are proposed in this paper. In this paper, contextual awareness approaches are grouped into several categories such as context acquisition, context modeling, service oriented architecture (SOA) and their frameworks, user perception approaches and others. These categories are further subcategorized and compared regarding several general characteristics. Each category is populated with old as well as current literature by discussing merits and demerits of the models. According to current literature there is not such model that fully satisfied all the requirement of context modeling e.g., context representation from heterogeneous sources, context reasoning, context management of distributed systems, dynamic service composition and service discovery etc. The open areas for further research are described as well in this paper. 


Keywords: autonomous machine, context-aware system, environmental knowledge, context modeling, categorization

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