Implementation of Fuzzy Decision Based Mobile Robot Navigation Using Stereo Vision

AbstractIn this article, we discuss implementation phases for an autonomous navigation of a mobile robotic system using SLAM data, while relying on the features of learned navigation maps. The adopted SLAM based learned maps, was relying entirely on an active stereo vision for observing features of the navigation environment. We show the framework for the adopted lower-level software coding, that was necessary once a vision is used for multiple purposes, distance measurements, and obstacle discovery. In addition, the article describes the adopted upper-level of system intelligence using fuzzy based decision system. The proposed map based fuzzy autonomous navigation was trained from data patterns gathered during numerous navigation tasks. Autonomous navigation was further validated and verified on a mobile robot platform

Towards Software Engineering Process for C4I Systems

Abstract — Command Control, Communication Computer and Intelligence (C4I) systems enables modern military forces to achieve information superiority in the battlefield. C4I are complex System of systems (SOS) where individual systems interact locally to achieve global SOS behaviors. To build software for C4I systems conventional software engineering SwE process and practices have shortcomings and are not capable to support certain aspect of these systems. If C4I systems fail to operate as required due to the fact that SwE process was unable to fulfill its requirements, the consequences may not be tolerated because of the criticality of the mission of these systems in information warfare (IW). This paper highlights the distinguished characteristics and operational requirements of C4I systems which poses challenges to SwE process and practices. This paper also discuss the possible future research areas in order to enhance SwE process so that better software could drive these complex systems as required

Bio-inspired Transputer Based-Fuzzy Mobile Robot

Mobile robots have been used widely in large number of intelligent based applications, where a random manoeuvring is an essential part of such systems, [1,2]. In this regards, experience has shown that mobile robots do require advanced parallel intelligent based control mechanisms. In this article, it is shown how a mobile robot can be controlled in movement via some rule based system. In this sense, the design, construction and testing of an autonomous mobile robot have already been defined in the literature. A Transputer Embedded Real-Time Controller has been widely used for industrial applications due to their advances. Here, a Fuzzy based Transputer System is used (on board the robot) to meet some intelligence requirements for the navigation and obstacle avoidance. A parallel fuzzy controller is implemented for a mobile robot guidance and obstacle avoidance. This is based on parallel processing of sonar data that do come from the mobile sensory system

Media Content Adaptation Framework for Technology Enhanced Mobile e-Learning

The increasing demand for ubiquitous access to technology enhanced learning environment has faced a challenge of heterogeneity in terms of networks, mobile device, platforms and finally, the learning content in various formats. In order to alleviate the challenge of the said diversity, content adaptation is essential. However, because of the diversity of the mobile users, networks and the rich media learning content, it is a major challenge for the access of learning content by the desired devices in the mobile learning environment. In order to alleviate the challenge of learning content mismatch, content adaptation is essential. This paper describes a content adaptation framework for mobile e-learning

Self-learning Mobile Robot Navigation in Unknown Environment Using Evolutionary Learning

An autonomous mobile robot operating in an unstructured environment must be able to learn with dynamic changes to that environment. Learning navigation and control of mobile robot in an unstructured environment is one of the most challenging problems. Fuzzy logic control is a useful tool in the field of navigation of mobile robot. In this research, we optimized a performance of fuzzy logic controller by evolutionary learning technique. Two proposed approaches have been designed and implemented: Fuzzy Logic Controller (FLC) and Genetic-Fuzzy Controller (GA-FLC). The Genetic Algorithm is used for automatically learning to tune the membership function parameters for mobile robot motion control. Moreover, the performance of these approaches are compared through simulation

LightCert4IoTs: Blockchain-Based Lightweight Certificates Authentication for IoT Applications

The proliferation of the internet of things (IoT) within the emergence of five-generation (5G) networks has received a huge attention in both industrial and academic domains. A 5G network is a cornerstone of realizing the full potential of the IoT, which interconnects billions of devices wirelessly. However, wireless communication in IoT devices reveals tremendous security risks in different dimensions and precisely in the distribution of the user certificates. The existing X.509 PKI, or the proposed decentralized PKI based on blockchain solutions have lacked practicality, and continue to have security flaws, or have not yet gained widespread acceptance owing to complexity and deployment issues. We present a lightweight certificate in size (LightCert4IoTs) that is not issued by Certification Authorities (CAs) due to the cost and complexity of the assignment of a signed certificate. In LightCert4IoTs first, an end-user (i.e., mobile and IoT devices) issues a self-signed certificate and lets Local Registration Authorities (LRAs)/EDGE nodes to verify and validate the binding identity-self signed certificate of the users through the Ethereum blockchain where The Ethereum network is used as the global notary for the IoT light certificates by saving them in the blockchain immutable ledger. The LightCert4IoTs leverages the advantages of blockchain technology and smart contracts to address the existing challenges of PKI certificates in IoT devices, which neatly achieve certificate issuance, update, and revocation more securely and efficiently. Finally, the LightCert4IoTs experimental results show that LightCert, as compared to relevant solutions/baselines, achieves reasonable overheads and is suitable for use in low- constrained IoT devices where the memory and processor power are optimized