Implementasi Prilaku Berkelompok pada Swarm Robots Menggunakan Teknik Logika Fuzzy-Particle Swarm Optimization

Dalam paper ini dijelaskan teknik komunikasi swarm robot untuk mencapai suatu target yang telah ditentukan. Pada percobaan ini digunakan 3 robot sederhana yang identik dengan 3 sensor infra-red, sensor kompas dan X-Bee. Untuk mencapai target dan menentukan posisi dari masing-masing robot digunakan sebuah sensor kamera dengan metode deteksi perbedaan warna. Swarm robot dan sensor kamera terhubung dengan komputer yang berfungsi sebagai pusat informasi dan penyimpan data. Untuk menghasilkan kinerja yang baik maka teknik Logika Fuzzy-Particle Swarm Optimization (PSO) digunakan dalam penelitian ini. Dari pengujian yang telah dilakukan diperoleh hasil yaitu ketiga robot dapat menemukan posisi terbaik, menghasilkan pergerakan yang halus dan mampu mencapai target yang telah ditentukan

Target Localization With Fuzzy-Swarm Behavior

In this paper describes target localization using deliberates fuzzy and swarm behavior. Localization is the process of determining the positions of robots or targets in whole swarms environment. To localize the target in real environment, experiment is conducted utilize three identical robots with different color. Every robot has three infrared sensors, two gas sensors, 1 compass sensor and one X-Bee. A camera in the roof of robot arena is utilized to determine the position of each robot with color detection methods. Swarm robots are connected to a computer which serves as an information center. Fuzzy and swarm behavior are keeping the swarm robots position and direction with a certain distance to the target position. From the experimental results the proposed algorithm is able to control swarm robots, produce smooth trajectory without collision and have the ability to localize the target in unknown environmen

PERAN DINAS PERHUBUNGAN KOTA BANDA ACEH DALAM MENANGANI KONFLIK ANTARA TRANSPORTASI ONLINE DAN TRANSPORTASI KONVENSIONAL

Public service is a responsibility that governments must render to their people, as efforts of the state to meet the needs of its citizens and the rights of their citizens. One form of public service required by governments in services is the provision of public transportation. But with the rapid advance in information technology in the globalization, transport services have emerged from many types, one of which is online-based transportation. However, the high interest the city of Banda Aceh on online transportation has led to a conflict between online transportation and conventional transport, using this type of qualitative research using descriptive methods. The results of this study suggest that the role of the ministry of decommissioning today in addressing the conflict between transportation online and conventional transport has not yet been established by the city Dinas Perhubungan Banda Aceh in regulating the smooth operation of both transports and the lack of the same facilities provided for them. As for the mediation strategy, the negotiations between the two transport groups have also not been carried out by the city's Banda Aceh Dinas Perhubungan which is aimed at resolving the conflict between the two

Data Optimization on Multi Robot Sensing System with RAM based Neural Network Method

Monitoring the environment activities is an attractive Abstract— Monitoring the environment activities is an attractive thing for development. That is because the human life would affect the surrounding environtment. There’s a lot of research of environment has been done, one of those is the changes of air quality in urban areas.  To measure the level of air quality, the data and information from field measurements and laboratory analysis result was needed. This paper review the research result that focus on sensor data processing in multi robot using RAM based neural network. There are 11 pattern input data were processed by temperature data optimization from 250C until 350C, humadity data from 20% until 60% and gas data from 350ppm until 450ppm. The obtained result is from 8 bits and 9 bits become 6 bits in certain level with optimazion percentage is25% and 33,3%. This result effect to the computationan load, it’s become more simple, the execution time and data communication becomes faster.   

Cooperative Avoidance Control-based Interval Fuzzy Kohonen Networks Algorithm in Simple Swarm Robots

A novel technique to control swarm robot’s movement is presented and analyzed in this paper. It allows a group of robots to move as a unique entity performing the following function such as obstacle avoidance at group level. The control strategy enhances the mobile robot’s performance whereby their forthcoming decisions are impacted by its previous experiences during the navigation apart from the current range inputs. Interval Fuzzy-Kohonen Network (IFKN) algorithm is utilized in this strategy. By employing a small number of rules, the IFKN algorithms can be adapted to swarms reactive control. The control strategy provides much faster response compare to Fuzzy Kohonen Network (FKN) algorithm to expected events. The effectiveness of the proposed technique is also demonstrated in a series of practical test on our experimental by using five low cost robots with limited sensor abilities and low computational effort on each single robot in the swarm. The results show that swarm robots based on proposed technique have the ability to perform cooperative behavior, produces minimum collision and capable to navigate around square shapes obstacles

Swarm Robots Communication-base Mobile Ad-Hoc Network (MANET)

This paper describes the swarm robots communication and control base Mobile ad-hoc network (MANET). MANET is a source of codes which migrate the network, collects and exchanges information of network nodes. In this work, the communication networks, which do not rely on fixed, preinstalled communication devices like base stations or predefine communication cells. Communications standards are considered in this work use the ad-hoc network such as Wireless LAN, X-Bee/Zig-Bee and Internet platform. All standards are integrated on swarm robots for real experiments. For finding the target, Particle swarm optimization (PSO) algorithm is proposed to control the real swarm robots communication in unknown experiment. As a results swarm robots-base MANET use PSO algorithm produce past response to find the target and swarm robots can move in the group without collision

A New Classification Technique in Mobile Robot Navigation

This paper presents a novel pattern recognition algorithm that use weightless neural network (WNNs) technique.This technique plays a role of situation classifier to judge the situation around the mobile robot environment and makes control decision in mobile robot navigation. The WNNs technique is choosen due to significant advantages over conventional neural network, such as they can be easily implemented in hardware using standard RAM, faster in training phase and work with small resources. Using a simple classification algorithm, the similar data will be grouped with each other and it will be possible to attach similar data classes to specific local areas in the mobile robot environment. This strategy is demonstrated in simple mobile robot powered by low cost microcontrollers with 512 bytes of RAM and low cost sensors. Experimental result shows, when number of neuron increases the average environmental recognition ratehas risen from 87.6% to 98.5%.The WNNs technique allows the mobile robot to recognize many and different environmental patterns and avoid obstacles in real time. Moreover, by using proposed WNNstechnique mobile robot has successfully reached the goal in dynamic environment compare to fuzzy logic technique and logic function, capable of dealing with uncertainty in sensor reading, achieving good performance in performing control actions with 0.56% error rate in mobile robot speed

Intelligent Robotics Navigation System: Problems, Methods, and Algorithm

This paper set out to supplement new studies with a brief and comprehensible review of the advanced development in the area of the navigation system, starting from a single robot, multi-robot, and swarm robots from a particular perspective by taking insights from these biological systems. The inspiration is taken from nature by observing the human and the social animal that is believed to be very beneficial for this purpose. The intelligent navigation system is developed based on an individual characteristic or a social animal biological structure. The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding. The combination of the navigation system and biologically inspired approach has attracted considerable attention, which makes it an important research area in the intelligent robotic system. Overall, this paper explores the implementation, which is resulted from the simulation performed by the embodiment of robots operating in real environments

Swarm Robots Control System based Fuzzy-PSO

In this paper describes swarm robots control design using combination Fuzzy logic and Particle swarm optimization algorithm. They can communicate with each other to achieve the target. Fuzzy Logic technique is used for navigating swarm robots in unknown environment and Particle Swarm Optimization (PSO) is used for searching and finding the best position of target. In this experiment utilize three identical robots with different color. Every robot has three infrared sensors, two gas sensors, 1 compass sensor and one X-Bee. A camera in the roof of robot arena is utilized to determine the position of each robot with color detection methods. Swarm robots and camera are connected to a computer which serves as an information center. From the experimental results the Fuzzy-PSO algorithm is able to control swarm robots, achieves the best target position in short time and produce smooth trajector