A Conceptual Semi-Humanoid Wireless Robotic Lecturer for Distance Learning (DL)

Information and Communications Technology is causing a worldwide revolution in virtually all fields of human endeavor. The education sector is not left out as the delivery of course content is no longer limited to the traditional teacher-student classroom interaction but also via electronic media. This paper presents a novel approach to e-Learning by leveraging on advancements in Machine-to-Machine communications (M2M), Internet-of-Things (IoT) and robotics technologies to design and construct a semihumanoid class teaching robot that aids teachers, lecturers and other educational personnel in communicating effectively with the students irrespective of their location and the distance using a plastic mannequin. The implementation of the system is achieved through hardware (mannequin) and software designs. The authors successfully developed a plastic mannequin with embedded electronics systems to work as a telepresence lecturer, allowing the elimination of time and distance between a professional remote educator and the students. The device was tested and compared with existing remote teaching technologies such as teleconferencing, telepresence with tablet screens and found to be more reliable, cheaper, and easy to use than the existing ones. The paper therefore concludes that the semi-humanoid robotic lecturer is a disruptive innovation in the world of Distance Education Learning (DEL)

Система навігації самохідної техніки на базі Arduino

Пояснювальна записка дипломного проєкту складається з 3 розділів, містить 85 сторінок тексту, 59 рисунків, 3 таблиці, 4 додатки, 59 інформаційних посилань. Об`єкт дослідження: система навігації самохідної техніки на базі Arduino. Мета дипломного проєкту: створення системи управління мобільного колісного робота з використанням Arduino, розробка мобільного колісного робота. У дипломному проєкті створено та реалізовано апаратно-програмний комплекс мобільного робота-автомобіля здатного орієнтуватися у просторі у режимі реального часу та уникати перешкоди, спираючись на: мікроконтролерну плату Arduino UNO, шилд драйверу двигунів Adafruit Motor Shield; використовується код, написаний у програмному забезпеченні Arduino IDE із застосуванням бібліотек AF Motor та Servo. Отримані результати можуть бути корисними при подальших дослідженнях та розробках різних систем навігації мобільних роботів, завдання яких – пересуватися у невизначеному середовищі з численними перешкодами.The explanatory note of the diploma project consists of 3 sections, contains 84 pages of text, 59 drawings, 3 tables, 4 annexes, 59 information links. Object of research: Arduino-based navigation system of self-driving vehicles. The aim of the diploma project: creation of a control system for a mobile wheeled robot using Arduino, the development of a mobile wheeled robot. In this diploma project were created and implemented - a hardware and software complex mobile robot-car, able to navigate in its surroundings and avoid obstacles in real time, created with: Arduino UNO microcontroller board, Adafruit Motor Driver Shield, servomotor and DC motors; code was written in Arduino IDE software using AFMotor and Servo libraries. The results obtained can be useful for further research and development of various navigation systems of autonomous mobile robots, which task is to move in an uncertain environment with numerous obstacles

Mobile Robot Navigation in Static and Dynamic Environments using Various Soft Computing Techniques

The applications of the autonomous mobile robot in many fields such as industry, space, defence and transportation, and other social sectors are growing day by day. The mobile robot performs many tasks such as rescue operation, patrolling, disaster relief, planetary exploration, and material handling, etc. Therefore, an intelligent mobile robot is required that could travel autonomously in various static and dynamic environments. The present research focuses on the design and implementation of the intelligent navigation algorithms, which is capable of navigating a mobile robot autonomously in static as well as dynamic environments. Navigation and obstacle avoidance are one of the most important tasks for any mobile robots. The primary objective of this research work is to improve the navigation accuracy and efficiency of the mobile robot using various soft computing techniques. In this research work, Hybrid Fuzzy (H-Fuzzy) architecture, Cascade Neuro-Fuzzy (CN-Fuzzy) architecture, Fuzzy-Simulated Annealing (Fuzzy-SA) algorithm, Wind Driven Optimization (WDO) algorithm, and Fuzzy-Wind Driven Optimization (Fuzzy-WDO) algorithm have been designed and implemented to solve the navigation problems of a mobile robot in different static and dynamic environments. The performances of these proposed techniques are demonstrated through computer simulations using MATLAB software and implemented in real time by using experimental mobile robots. Furthermore, the performances of Wind Driven Optimization algorithm and Fuzzy-Wind Driven Optimization algorithm are found to be most efficient (in terms of path length and navigation time) as compared to rest of the techniques, which verifies the effectiveness and efficiency of these newly built techniques for mobile robot navigation. The results obtained from the proposed techniques are compared with other developed techniques such as Fuzzy Logics, Genetic algorithm (GA), Neural Network, and Particle Swarm Optimization (PSO) algorithm, etc. to prove the authenticity of the proposed developed techniques

Analysis and Development of Computational Intelligence based Navigational Controllers for Multiple Mobile Robots

Navigational path planning problems of the mobile robots have received considerable attention over the past few decades. The navigation problem of mobile robots are consisting of following three aspects i.e. locomotion, path planning and map building. Based on these three aspects path planning algorithm for a mobile robot is formulated, which is capable of finding an optimal collision free path from the start point to the target point in a given environment. The main objective of the dissertation is to investigate the advanced methodologies for both single and multiple mobile robots navigation in highly cluttered environments using computational intelligence approach. Firstly, three different standalone computational intelligence approaches based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), Cuckoo Search (CS) algorithm and Invasive Weed Optimization (IWO) are presented to address the problem of path planning in unknown environments. Next two different hybrid approaches are developed using CS-ANFIS and IWO-ANFIS to solve the mobile robot navigation problems. The performance of each intelligent navigational controller is demonstrated through simulation results using MATLAB. Experimental results are conducted in the laboratory, using real mobile robots to validate the versatility and effectiveness of the proposed navigation techniques. Comparison studies show, that there are good agreement between them. During the analysis of results, it is noticed that CS-ANFIS and IWO-ANFIS hybrid navigational controllers perform better compared to other discussed navigational controllers. The results obtained from the proposed navigation techniques are validated by comparison with the results from other intelligent techniques such as Fuzzy logic, Neural Network, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and other hybrid algorithms. By investigating the results, finally it is concluded that the proposed navigational methodologies are efficient and robust in the sense, that they can be effectively implemented to solve the path optimization problems of mobile robot in any complex environment