Modular Design of an Educational Robotics Platform

The goal of this thesis is to design a modular educational robotics platform to improve the limitation of current educational robotics platforms, such as limited pins, single programming language, and single programming device. This platform uses an SPI bus for modularity and to solve the problem of limited pins on current educational robot platforms. A Raspberry Pi, which runs a 32bit Embedded Linux System, has been used to build the central control for this educational robotics platform to enable it to use different programming languages and to be programmed by different devices. The modules and libraries for stepper motors and IR sensors have been built for this robot, and the example projects, basic control, obstacle avoidance, and wall following, show that this educational robotics platform can be used as a platform for basic artificial intelligence design. This thesis also shows how to design a custom module, which enables users to design their own modules and put them into their robot projects

A Robust Platform for Mobile Robotics Teaching and Developing Using Arduino’s Integrated Development Environment (IDE) for Programming the Arduino MEGA 2560

In light of the rapid pace at which development happens with modern technology, mobile robots play an important role in our daily lives. This is due to their great importance in facilitating the affairs of life in various economic, commercial, industrial, scientific, and many other fields. In this research and project, we have restructured the microcontroller and system for one of the mobile robots (CEENBOT) that was designed by the University of Nebraska and replaced it with an Arduino Mega 2560. The purpose of using the Arduino Mega 2560 robot is to provide alternative programming for the CEENBOT platform to support an Arduino programming option. It is an open-source program which makes it easily accessible for developers and programmers. The Arduino Mega 2560 is an open-source electronics platform built on easy-to-use hardware and software. The Arduino Mega 2560 robot provides one of the most accessible ways to install different sensors and can be used in different aspects or applications that can be useful for mobile robotics teaching and development. Following the completion of this research and project, the electrical and computer engineering department at the University of Nebraska - Lincoln will be able to enhance its existing robotics course offerings using this robot. New laboratories have been created for teaching and development in this research. The laboratories include Simulink Getting Started, Simulink with Arduino Mega 2560, Integrated development environment IDE Getting Started with Arduino Mega 2560, Getting to Know the Robot Hardware, Getting Started on Moving the Robot, Obstacle Avoidance, Wireless Communication, and Create Your Own Lab Adventure. Advisors: Alisa Gilmore and Bing Che

Collision Free Navigation of a Multi-Robot Team for Intruder Interception

In this report, we propose a decentralised motion control algorithm for the mobile robots to intercept an intruder entering (k-intercepting) or escaping (e-intercepting) a protected region. In continuation, we propose a decentralized navigation strategy (dynamic-intercepting) for a multi-robot team known as predators to intercept the intruders or in the other words, preys, from escaping a siege ring which is created by the predators. A necessary and sufficient condition for the existence of a solution of this problem is obtained. Furthermore, we propose an intelligent game-based decision-making algorithm (IGD) for a fleet of mobile robots to maximize the probability of detection in a bounded region. We prove that the proposed decentralised cooperative and non-cooperative game-based decision-making algorithm enables each robot to make the best decision to choose the shortest path with minimum local information. Then we propose a leader-follower based collision-free navigation control method for a fleet of mobile robots to traverse an unknown cluttered environment where is occupied by multiple obstacles to trap a target. We prove that each individual team member is able to traverse safely in the region, which is cluttered by many obstacles with any shapes to trap the target while using the sensors in some indefinite switching points and not continuously, which leads to saving energy consumption and increasing the battery life of the robots consequently. And finally, we propose a novel navigation strategy for a unicycle mobile robot in a cluttered area with moving obstacles based on virtual field force algorithm. The mathematical proof of the navigation laws and the computer simulations are provided to confirm the validity, robustness, and reliability of the proposed methods

Autonomous navigation strategy for a robot vehicle based on LIDAR sensor acting in cultivar environments

Orientador: Ely Carneiro de PaivaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia MecânicaResumo: Este trabalho apresenta um Sistema de Navegação Autônoma (SNA) voltado para ambientes de pomares plantados em linha e que tem como plataforma alvo um veículo robótico de exterior em configuração Ackermann. Calcado em uma solução sensorial de baixo custo, o sistema utiliza as informações de um único sensor laser de varredura bidimensional para coordenar a navegação da plataforma alvo pelos corredores de cultivares. Para tal, ele se vale de dois subsistemas, os quais são: Sistema de Obtenção de Caminhos (SOC) e Sistema de Controle de Guiamento (SCG). Com uma versão do método RANSAC modificada e com o filtro de Kalman, o SOC gera caminhos de referência a partir das informações disponibilizadas pelo sensor laser. Tais caminhos são sequencialmente utilizados pelo SCG para o guiamento da plataforma que se dá por meio de um controlador PI que atua sobre o erro de trajetória com relação a um caminho a ser seguido. Dados reais coletados em um experimento realizado entre fileiras de um cafezal são utilizados para uma validação do SOC. Também são realizadas algumas comparações de desempenho desse sistema em diferentes configurações. A pré-validação do SCG é feita a partir de um ambiente simulado, assim como uma determinação inicial de seus ganhos de controleAbstract: This project presents an Autonomous Navigation System (ANS) focused on orchards planted in line that has as a target platform an outdoor robotic vehicle in Ackermann configuration. Based on a low cost sensorial solution, the system utilized the information from a single two-dimensional scanning laser sensor to coordinate the platform navigation by the cultivar corridors. It uses two subsystems, which are: Path Generation System (PGS) and Guidance Control System (GCS). With a modified version of the RANSAC method and with the Kaman filter, the PGS generates reference paths from information provided by the laser sensor. These paths are sequentially used by the GCS in order to guide the platform, which is done via a PI controller that acts on the trajectory error related to the path to be followed. Real data, collected in an experiment conducted between rows of coffee plantation, were used for a validation of the PGS. Some performance comparisons was also performed for different configurations of this system. The pre-validation of the GCS was done with a simulated environment as well as an initial determination of its control gainsMestradoMecanica dos Sólidos e Projeto MecanicoMestre em Engenharia Mecânica30003017CAPE