Recent advances in technology have enabled the development of truly autonomous ground vehicles capable of performing complex navigation tasks. As a result, the demand for practical unmanned ground vehicle (UGV) systems has increased dramatically in recent years. Central to these developments is maturation of emerging mobile robotic intelligent and autonomous capability. While the progress UGV technology has been substantial, there are many challenges that still face unmanned vehicle system developers. Foremost is the improvement of perception hardware and intelligent software that supports the evolution of UGV capability. The development of a Next-generation Experimentation Robotic Vehicle (NERV) serves to provide a small UGV baseline platform supporting experimentation focused on progression of the state-of-the-art in unmanned systems. Supporting research and user feedback highlight the needs that provide justification for an advanced small UGV research platform. Primarily, such a vehicle must be based upon open and technology independent system architecture while exhibiting improved mobility over relatively structured terrain. To this end, a theoretical kinematic model is presented for a novel two-body multi degree-of-freedom, four-wheel drive, small UGV platform. The efficacy of the theoretical kinematic model was validated through computer simulation and experimentation on a full-scale proof-of-concept mobile robotic platform. The kinematic model provides the foundation for autonomous multi-body control. Further, a modular system level design based upon the concepts of the Joint Architecture for Unmanned Systems (JAUS) is offered as an open architecture model providing a scalable system integration solution. Together these elements provide a blueprint for the development of a small UGV capable of supporting the needs of a wide range of leading-edge intelligent system research initiatives. / Master of Science

This diploma thesis deals with the problem of mobile robot localisation in the environment based on current 2D and 3D sensor data and previous records. Work is focused on detecting previously visited places by robot. The implemented system is suitable for loop detection, using the Gestalt 3D descriptors. The output of the system provides corresponding positions on which the robot was already located. The functionality of the system has been tested and evaluated on LiDAR data.

For this thesis, smart spraying robot was designed, constructed and tested to validate the concept of smart pest control. Electrostatic charging of sprayed pesticide was realized in a spray nozzle design that improved plant coverage and reduced wasted pesticide as well as soil pollution. A thorough investigation into electrostatic spraying was conducted, which was accompanied by extensive simulations and experimentation. The results obtained from the simulation experimentation on industry standard electrostatic spray system (ESS) nozzles along with laboratory testing of these nozzles, detecting spray coverage using water sensitive paper and additional optical spray visualization methods gave the necessary insight and experience required to develop a new spray nozzle. Additional COMSOL simulation and experimentation were carried out on a Fan Hydraulic Spray Nozzle (FHSN), the results of which allowed for the effective addition of electrostatic induction capabilities, thereby transforming the (FHSN) into Electrostatic Induction Spray Nozzle (EISN) which is one of the prime parts of the smart spraying system. SOLIDWORKS software was used in the designing parts of this nozzle which were then manufactured using a 3D printer. An AL05D robotic manipulator and a TTRK tracked platform from Lynxmotion ™ were the mini mobile robot components selected for the feasibility study of the smart electrostatic crop spraying system. This mobile robot was equipped with a CCD digital camera, a range detector, and path mark detector to provide the necessary sensors required by the smart electrostatic spray system. A Windows™ based mobile computer in addition to an ARDUINO™ based orksmicrocontroller system were chosen to provide the computational power required by the system. These were arranged in a master – slave configuration, with the main processing for images and motion being conducted inside the master computer using programs created by Matlab smart ™ software. The execution of motion commands and the operation of the range and path mark detection along with operating the spray nozzle were performed on the slave computer using C as the programming language. The manufactured smart electrostatic spray system moves along cotton crop rows with a camera that scans the selected plant for pest infestation on the upper and lower surfaces of plant leaves. When a pest is detected, the spray nozzle is targeted on it at the appropriate distance, and a burst of pesticide destroys it. The results of experiments have shown that using the electrostatic induction system improves coverage 3 to 4 fold and reduces soil contamination by 2 to 4 fold. The system has plenty of room for performance improvement, and future development will make it adaptable for application to other crops and applications.

Made available in DSpace on 2017-07-21T14:19:26Z (GMT). No. of bitstreams: 1 Roberson Junior Fernandes Alves.pdf: 17901245 bytes, checksum: 170e17bbccf0e54fa9b0dab204aca2e4 (MD5) Previous issue date: 2015-09-17 / Developing mobile and autonomous agrobots for greenhouses requires the use of procedures which allow robot autolocalization and tracking. The tracking problem can be modeled as finding the most likely sequence of states in a hidden Markov model„ whose states indicate the positions of an occupancy grid. This sequence can be estimated with Viterbi’s algorithm. However, the processing time and consumed memory, of this algorithm, grows with the dimensions of the grid and tracking duration, and, this can constraint its use for tracking agrobots. Considering it, this work presents a tracking procedure which uses two approximated implementations of Viterbi’s algorithm called Viterbi-JD(Viterbi’s algorithm with a sliding window) and Viterbi-JD-MTE(Viterbi’s algorithm with a sliding window over an hidden Markov model with sparse transition matrix). The experimental results show that the time and memory performance of tracking with this two approximated implementations are significantly higher than the Viterbi’s based tracking. The reported tracking hypothesis is suboptimal, when compared to the hypothesis generated by Viterbi, but the error does not grows substantially. Th experimentos was performed using RSSI(Received Signal Strength Indicator) simulated data. / O desenvolvimento de agrobots móveis e autônomos para operar em estufas agrícolas depende da implementação de procedimentos que permitam o rastreamento do robô no ambiente. O problema do rastreamento pode ser modelado como a determinação da sequência de estados mais prováveis de um modelo oculto de Markov cujos estados indicam posições de uma grade de ocupação. Esta sequência pode ser estimada pelo algoritmo de Viterbi. No entanto, o tempo de processamento e a memória consumida, por esse algoritmo, crescem com as dimensões da grade e com a duração do rastreamento, e isto pode limitar seu uso no rastreamento de agrobots em estufas. Considerando o exposto, este trabalho apresenta um procedimento de rastreamento que utiliza mplementações aproximadas do algoritmo de Viterbi denominadas de Viterbi-JD(Viterbi com janela deslizante) e Viterbi- JD-MTE(Viterbi com janela deslizante sobre um modelo oculto de Markov com matriz de transição esparsa). Os experimentos mostram que o desempenho de tempo e memória do rastreamento baseado nessas implementações aproximadas é significativamente melhor que aquele do algoritmo original. A hipótese de rastreamento gerada é sub ótima em relação àquela calculada pelo algoritmo original, contudo, não há um aumento substancial do erro. Os experimentos foram realizados utilizando dados simulados de RSSI (Received Signal Strength Indicator).

Faculty of Engineering in collaboration with the National Agricultural and Livestock Investigation Institute is developing a low cost platform capable of dealing with challenges imposed by agricultural activities, specifically, fruit transportation inside fields. In this context, the consequent dissertation focuses on the development of a dynamic model of an all terrain articulated autonomous vehicle to be applied in the aforementioned platform. The study includes the kinematic and dynamic analysis of the vehicle. Once those models are deducted, they are put together against the ones obtained for a biarticulated robot arm without ground fixation. To sum up, results will be adapted for computational simulation which was done via Gazebo, an ambience of the robot operating system ROS. Through this simulations it was possible to determine the model validity for the autonomous operating robotic platform. / Facultad de Ingeniería en conjunto con el Instituto Nacional de Investigación Agropecuaria desarrolla una plataforma móvil de bajo costo capaz de enfrentar los retos impuestos por la actividad agrícola, más específicamente, asistencia en el transporte de fruta. Es en este contexto que el presente trabajo se enfoca en desarrollar un modelo dinámico de un vehículo autónomo articulado todoterreno para ser aplicado en la mencionada plataforma. El estudio comprende el análisis de la cinemática y dinámica del vehículo. Una vez obtenidos los modelos cinemáticos y dinámicos, se compara los mismos con los obtenidos para un brazo biarticulado sin vínculo a tierra. Finalmente se adaptan los resultados para simulación computacional la cual fue realizada utilizando el ambiente Gazebo del sistema operativo robótico ROS. A través de esta simulación se pudo comprobar la validez del modelo desarrollado para la plataforma robótica autónoma en operación.

O problema de navegação de robôs móveis tem sido estudado ao longo de vários anos, com o objetivo de se construir um robô com elevado grau de autonomia. O aumento da autonomia de um robô móvel está relacionado com a capacidade de aquisição de informações e com a automatização de tarefas, tal como a construção de mapas de ambiente. Sistemas de visão são amplamente utilizados em tarefas de robôs autônomos devido a grande quantidade de informação contida em uma imagem. Além disso, sensores omnidirecionais catadióptricos permitem ainda a obtenção de informação visual em uma imagem de 360º, dispensando o movimento da câmera em direções de interesse para a tarefa do robô. Mapas de ambiente podem ser construídos para a implementação de estratégias de navegações mais autônomas. Nesse trabalho desenvolveu-se uma metodologia para a construção de mapas para navegação, os quais são a representação da geometria do ambiente. Contém a informação adquirida por um sensor catadióptrico omnidirecional estéreo, construído por uma câmera e um espelho hiperbólico. Para a construção de mapas, os processos de alinhamento, correspondência e integração, são efetuados utilizando-se métricas de diferença angular e de distância entre os pontos. A partir da fusão dos mapas locais cria-se um mapa global do ambiente. O processo aqui desenvolvido para a construção do mapa global permite a adequação de algoritmos de planejamento de trajetória, estimativa de espaço livre e auto-localização, de maneira a obter uma navegação autônoma. / The problem of mobile robot navigation has been studied for many years, aiming at build a robot with an high degree of autonomy. The increase in autonomy of a mobile robot is related to its capacity of acquisition of information and the “automation” of tasks, such as the environment map building. In this aspect vision has been widely used due to the great amount of information in an image. Besides that catadioptric omnidirectional sensors allow to get visual information in a 360o image, discharging the need of camera movement in directions of interest for the robot task. Environment maps may be built for an implementation of strategies of more autonomous navigations. In this work a methodology is developed for building maps for robot navigations, which are the representation of the environment geometry. The map contains the information received by a stereo omnidirectional catadioptric sensor built by a camera and a hyperbolic mirror. For the map building, the processes of alignment, registration and integration are performed using metric of angular difference and distance between the points. From the fusion of local maps a global map of the environment is created. The method developed in this work for global map building allows to be coupled with algorithms of path planning, self-location and free space estimation, so that autonomous robot navigation can be obtained.

The demands of mobile robots system are growing rapidly in recent days. Autonomous and semi-autonomous mobile robots for indoor environments have become great helper to human, such as transport robot in warehouse, cleaning robot for apartment and various humanoids for personal assistance, education and space exploration. This thesis project work describes how to implement a mobile robot system for unstructured indoor environment. This mobile robot system is able to build a map of the environment, plan path and navigate robot between user-defined locations in the environment autonomously or teleoperated by human through GUI or keyboard on a remote control terminal. Additionally, this mobile robot will be equipped a laser pointer worked as an interaction interface between robot and human by showing robot intensions to operator or surroundings. The development of this project work will involve two rapid growing features, one is depth camera and the other is ROS. Use depth camera as the primary sensor has been accepted by more and more mobile robot platform. ROS, as the fast-growing robot software framework, is an inevitable path when developing robot systems.

O problema de navegação de robôs móveis tem sido estudado ao longo de vários anos, com o objetivo de se construir um robô com elevado grau de autonomia. O aumento da autonomia de um robô móvel está relacionado com a capacidade de aquisição de informações e com a automatização de tarefas, tal como a construção de mapas de ambiente. Sistemas de visão são amplamente utilizados em tarefas de robôs autônomos devido a grande quantidade de informação contida em uma imagem. Além disso, sensores omnidirecionais catadióptricos permitem ainda a obtenção de informação visual em uma imagem de 360º, dispensando o movimento da câmera em direções de interesse para a tarefa do robô. Mapas de ambiente podem ser construídos para a implementação de estratégias de navegações mais autônomas. Nesse trabalho desenvolveu-se uma metodologia para a construção de mapas para navegação, os quais são a representação da geometria do ambiente. Contém a informação adquirida por um sensor catadióptrico omnidirecional estéreo, construído por uma câmera e um espelho hiperbólico. Para a construção de mapas, os processos de alinhamento, correspondência e integração, são efetuados utilizando-se métricas de diferença angular e de distância entre os pontos. A partir da fusão dos mapas locais cria-se um mapa global do ambiente. O processo aqui desenvolvido para a construção do mapa global permite a adequação de algoritmos de planejamento de trajetória, estimativa de espaço livre e auto-localização, de maneira a obter uma navegação autônoma. / The problem of mobile robot navigation has been studied for many years, aiming at build a robot with an high degree of autonomy. The increase in autonomy of a mobile robot is related to its capacity of acquisition of information and the “automation" of tasks, such as the environment map building. In this aspect vision has been widely used due to the great amount of information in an image. Besides that catadioptric omnidirectional sensors allow to get visual information in a 360o image, discharging the need of camera movement in directions of interest for the robot task. Environment maps may be built for an implementation of strategies of more autonomous navigations. In this work a methodology is developed for building maps for robot navigations, which are the representation of the environment geometry. The map contains the information received by a stereo omnidirectional catadioptric sensor built by a camera and a hyperbolic mirror. For the map building, the processes of alignment, registration and integration are performed using metric of angular difference and distance between the points. From the fusion of local maps a global map of the environment is created. The method developed in this work for global map building allows to be coupled with algorithms of path planning, self-location and free space estimation, so that autonomous robot navigation can be obtained.

Teleoperation of ground/aerial vehicle extends operator's ability (e.g. expertise, strength, mobility) into the remote environment, and haptic feedback enhances the human operator's perception of the slave environment. In my thesis, two cases are studied: wheeled mobile robot (MWR) haptic tele-driving over the Internet and unmanned aerial vehicle (UAV) haptic teleoperation over the Internet. We propose novel control frameworks for both dynamic WMR and kinematic WMR in various tele-driving modes, and for a "mixed" UAV with translational dynamics and attitude kinematics. The recently proposed passive set-position modulation (PSPM) framework is extended to guarantee the passivity and/or stability of the closed-loop system with time-varying/packet-loss in the communication; and proved performance in steady state is shown by theoretical measurements.For UAV teleoperation, we also derive a backstepping trajectory tracking control with robustness analysis. Experimental results for dynamic/kinematic WMR and an indoor quadrotor-type UAV are presented to show the efficacy of the proposed control framework.

In the field of mobile robotics, many applications require feedback control laws that provide perfect path following. Previous work has shown that transverse feedback linearization is an effective approach to designing path following controllers that achieve perfect path following and path invariance. This thesis uses transverse feedback linearization and augments it with dynamic extension to present a framework for designing path following controllers for certain kinematic models of mobile robots. This approach can be used to design path following controllers for a large class of paths. While transverse feedback linearization makes the desired path attractive and invariant, dynamic extension allows the closed-loop system to achieve the desired motion along the path. In particular, dynamic extension can be used to make the mobile robot track a desired velocity or acceleration profile while moving along a path.