Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.https://doi.org/10.3390/s1601002

Fuzzy Logic Control for Autonomous Mobile Robots in Static and Dynamic Environments

Autonomous mobile robots have been widely used in many researches and applications. In this work, we develop collision avoidance and line following techniques for mobile robot navigation in static and dynamic environments with the integration of fuzzy logic fusion. Eight proximity sensors are used to detect different obstacles whereas three ground sensors are used to detect the line underneath the robot. The proposed method has been successfully tested in Webots Pro simulator and in in real time experiment

Energy-Efficient Dynamic Motion Control for Wheeled Mobile Robots Using Low Cost Resources

Mobile robotic systems have gained significant attention in human interest, where they represent such a complex interaction with challenging environments. Some applications require continuous operations, so the robots motions have to be optimized to reduce their energy consumption. In addition, total energy consumption in mobile robotic applications is one of the most important issues that has not been adequately considered. Mobile robots are limited by the amount of energy supplied by the batteries they carry where a new supply of energy while working is too expensive to be realistic. Thus, this work aiming to minimize the energy consumption of a wheeled mobile robot in dynamic environments

Analytical Study of Pre-Congestion Notification (PCN) Techniques

Maintaining the quality of service (QOS) and controlling the network congestion are quite complicated tasks. They cause degrading the performance of the network, and disturbing the continuous communication process. To overcome these issues, one step towards this dilemma has been taken in form of Pre-congestion notification (PCN) technique. PCN uses a packet marking technique within a PCN domain over IP networks. It is notified by egress node that works as guard at entry point of network. Egress node gives feedback to communicating servers whether rate on the link is exceeded than configured admissible threshold or within the limit. Based on this feedback, admission decisions are taken to determine whether to allow/block new coming flows or terminate already accepted. The actual question is about selection of right algorithm for PCN domain. In this paper, we investigate the analytical behavior of some known PCN algorithms. We make slide modifications in originality of PCN algorithms without disquieting working process in order to employ those within similar types of scenarios. Our goal is to simulate them either in highly congested or less congested realistic scenarios. On the basis of simulation done in ns2, we are able to recommend each PCN algorithm for specific conditions. Finally, we develop a benchmark that helps researchers and scientific communities to pick the right algorithm. Furthermore, the benchmark is designed to achieve specific objectives according to the users’ requirements without congesting the network

Digital Marketing sebagai Metoda Alternatif Wirausaha Bagi Mahasiswa di Universitas Negeri Padang

Digital technology and the internet have opened opportunities for people to develop social interaction through this technology, with the birth of web technology, media and social networks, which led to the industrial revolution 4.0. This technology presents a new trend in building a business called Digital Marketing (DM). DM provides new opportunities for anyone to do entrepreneurship without being limited by time, place and region. More than a decade of entrepreneurship has become the focus of attention of the government in Education, as one of the ways to reduce national unemployment. Universitas Negeri Padang (UNP) answers the entrepreneurship education policy by making Entrepreneurship as a compulsory subject, promoting entrepreneurial student programs and integrated service units for career guidance and entrepreneurship. This paper examines more deeply how DM can be used as an alternative method of entrepreneurship for UNP students, which has direct touching student life as a millennial generation. The experimental method is used to see of improvement the knowledge and skills of students in DM through DM Training and Development of DM eLearning Resources (DMLR). To measure the success of the program, instruments were developed before and after training, as well as a questionnaire to assess the results of the DMLR development. The results of this study showed an increase in student knowledge and skills in DM and a good assessment of the developed DMLR

TERP: A Trusted and Energy Efficient Routing Protocol for Wireless Sensor Networks (WSNs)

Recently, Wireless Sensor Networks (WSNs) have got researchers attention due to its various useful and helpful applications in the real world with low cost sensors. The task of the sensors is to collect data from the environment and send it to the central node (sink node). However, the power is limited in these sensors and therefore it has a limited lifetime which is a big deal in WSNs. Another important issue in WSNs is the level of security. Since these sensor nodes exchange and transmit data among the network, the security of the data can be at risk. Hence, In this poster, we propose a novel trusted and energy efficient routing protocol (TERP), which is based on the Destination Sequenced Distance Vector Protocol (DSDV). TERP can avoid any malicious nodes (untrusted nodes) and thus increase the security level in the network, and decrease the power consumption level

Google Play Apps energy rating model: multi-criteria evaluation model to generate tentative energy ratings for Google Play Store Apps

info:eu-repo/semantics/publishedVersio

Complex Analysis of Intelligent Systems

Logic gates can be written in terms of complex differential operators where the inputs and outputs are analytic functions with several variables. Using the polar representation of complex numbers, we arrive at an immediate connection between the oscillatory behavior of the system and logic gates. We explain the universal programming language (UPL) used by physical objects to process information. To assure the causality structure in UPL, we introduce the concept of layers that characterizes the computations for each time scale.Comment: 18 pages; comments are welcome

Multi-Valued Quantum Neurons

The multiple-valued quantum logic is formulated systematically such that the truth values are represented naturally as unique roots of unity placed on the unit circle. Consequently, multi-valued quantum neuron (MVQN) is based on the principles of multiple-valued threshold logic over the field of complex numbers. The training of MVQN is reduced to the movement along the unit circle. A quantum neural network (QNN) based on multi-valued quantum neurons can be constructed with complex weights, inputs, and outputs encoded by roots of unity and an activation function that maps the complex plane into the unit circle. Such neural networks enjoy fast convergence and higher functionalities compared with quantum neural networks based on binary input with the same number of neurons and layers. Our construction can be used in analyzing the energy spectrum of quantum systems. Possible practical applications can be found using the quantum neural networks built from orbital angular momentum (OAM) of light or multi-level systems such as molecular spin qudits.Comment: 14 pages, 3 figures, accepted for publicatio

The Bimetric Theory Of Quantized Fields

We introduce a special class of bimetric theories of quantized fields with preserved classical energy conditions. More precisely, we describe the missing anti-particles in our visible universe as being trapped in a spacetime patch with different metric such as the de-Sitter spacetime and negative energies. In order to stabilize these anti-states, time must go in the opposite direction to our visible universe, in agreement with the Feynman-St\"uckelberg interpretation of antiparticles. Since the energy scale of our observed universe is low, we do not need to worry about these highly energetic anti-particles except for compatibility issues regarding the restoration of classical energy conditions. However, at the quantum gravity scale, these anti-states play a crucial role in the cancellation of gravitational anomalies, along with other possible quantum anomalies that may emerge.Comment: Final version, 10 page