Behavior based autonomous mobile Robot for industrial logistics

The design of robot behaviors to meet the requirements of the new industrial era - Industry 4.0 - has grown significantly in recent years. Especially the demand for flexible and adaptable systems has increased exponentially since intelligent robots started to be integrated into assembly lines and replace human activities. Tools such as Finite State Machines have proven to be an understandable and quick way to solve high-level problems in robotics; however, unmanageable when complexity rises. They become confusing and unreadable, making their modification and mainte- nance a problem. New tools, such as Behavior Trees, have emerged, creating modular, flexible, and adaptable systems without sacrificing readability with the increased com- plexity. The proposed architecture follows a hierarchical layered approach taking advantage of Behavior Trees, developing modular robot skills and system interfaces to create an autonomous behavior-based system. The software was implemented and tested in an Autonomous Mobile Robot capable of navigating complex environments and executing basic tasks. The results showed real advantages in using the layer-based approach, particularly giving the system modularity and increased flexibility capable of being easily improved and used in other systems. It was also concluded that Behavior Trees are an adequate tool for reactive systems in highly dynamic environments.Nos últimos anos, tem-se verificado um crescimentos na modelação de comportamen- tos robóticos com o objetivo de satisfazer necessidades dos novos paradigmas da indústria. Em particular, na indústria 4.0, com a integração de robôs nas linhas de produção e a subs- tituição dos humanos em diversas atividades, tem-se verificado um aumento na exigência de sistemas mais adaptáveis e flexíveis. Ferramentas tais como as máquinas de estado provaram ser percetíveis e de fácil uti- lização na resolução de problemas na área da robótica. No entanto, com o aumento da complexidade, tornam-se problemáticas pela sua desorganização e ilegibilidade. Por con- seguinte, emergiram novas estruturas, tais como as árvores de comportamento, capazes de tornar os sistemas mais modulares e flexíveis. A arquitetura por hierarquisação de camadas proposta, tira partido das vantagens das árvores de comportamento, com o desenvolvimento de comportamentos e interfaces de modo a criar um sistema reativo e autónomo. O software foi implementado e testado num robô móvel autónomo, capaz de navegar em ambientes complexos e de executar tarefas basicas. Os resultados mostraram vantagens na utilização da arquitetura proposta, em parti- cular, trazendo modularidade e flexibilidade ao sistema robótico, permitindo uma futura melhoria de cada um dos módulos, tal como, a sua utilização noutros sistemas

Gunrock: GPU Graph Analytics

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs, have presented two significant challenges to developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We characterize the performance of various optimization strategies and evaluate Gunrock's overall performance on different GPU architectures on a wide range of graph primitives that span from traversal-based algorithms and ranking algorithms, to triangle counting and bipartite-graph-based algorithms. The results show that on a single GPU, Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives and CPU shared-memory graph libraries such as Ligra and Galois, and better performance than any other GPU high-level graph library.Comment: 52 pages, invited paper to ACM Transactions on Parallel Computing (TOPC), an extended version of PPoPP'16 paper "Gunrock: A High-Performance Graph Processing Library on the GPU

Multimodal Route Planning Algorithm for Encouraging the Usage of Different Means of Public Transportation

Jätkuv linnastumine ja linnade kasv muudab ka linnasisese teekonna planeerimise aina keerulisemaks.. Tihti pole võimalik reisida ühest punktist teise, kasutades ainult üht transpordiliiki. Veelgi enam, juhul, kui kasutajal on spetsiifilisi eelistusi, nagu soov võtta ühistransporti kaasa ratastool, lapsevanker või jalgratas, kindlat tüüpi ühistranspordivahendi kasutamine (näiteks ratastoolisõbralik buss) on tarvilik. Sellest olenemata kalduvad olemasolevad teekonnaplaneerimise mootorid suurel määral eelistama esimest suvalist tüüpi ühistranspordi reisi, kui see vastab aegruumilistele nõudmistele, selle asemel, et kinni pidada kasutaja poolt valitud ühistranspordi liikidest. Käesoleva lõputöö eesmärk on pakkuda välja alternatiivne meetod multimodaalseks teekonnaplaneerimiseks, mis kasutaks ainult neid ühistranspordiliike, mis on kasutaja poolt lubatud. Selles lõputöös on alternatiivne kiireima multimodaalse teekonna leidmise meetod, mis kasutab ühistransporti, on arendatud. See on võimeline pakkuma konkurentsivõimelisi alternatiive olemasolevate teekonnaleidmise otsingumootorite poolt pakutud lahendustele, samal ajal kasutades vaid neid ühistranspordiliike, mis on kasutaja poolt lubatud.The ongoing urbanization and the growth of the cities is leading to the increase of complexity of the route planning in urban areas. Often it is not possible or feasible to travel from one location to another using only one mode of transportation. Moreover, in case of specific preferences like taking a wheelchair, baby carriage or a bicycle in the mean of public transport, a specific type of mean of transport (e.g. wheelchair-accessible bus) is needed. However, the existing routing engines tend to heavily prefer the first public transport trip of any mean of public transport that meets the spatiotemporal conditions instead of sticking to user’s selected modes.The aim of this thesis is to propose an alternative method for multimodal route planning, using only the modes and means of public transport that are allowed by the user. In this thesis work an alternative method for multimodal fastest pathfinding with use of public transportation is developed. It is able to propose competitive alternatives to the results of the existing routing engines at the same time using only the modes and means of public transport that are allowed by the user

Practical motion planning for aerial-like virtual agents in Meta!Blast: A full and complex three dimensional virtual environment

Motion planning, or enabling agents to navigate around a virtual environment autonomously, is an essential requirement for video games and simulations. A well implemented motion planning technique can create a realistic and immersive user experience. If motion planning is not implemented properly, agents will exhibit unrealistic behavior and cause a distraction for the user. Motion planning is often difficult to implement due to the agents\u27 movement capabilities and the complexity of the virtual environment in which the agents exist. In a traditional three dimensional video game in which the agents are bound by gravity, the agents\u27 motion takes place mostly in the XZ-plane. In other words, the agents\u27 degree of freedom (DOF) is three. In this case, motion planning is translated into a two-dimensional problem, which is relatively easier to compute. However, when the agents can move in any three dimensional direction or to any three dimensional position in space, motion planning is much more complex. Meta!Blast is a three dimensional educational video game. Implementing motion planning in Meta!Blast is challenging for three reasons: The first reason is the agents have at least six degrees of freedom and can be translated or rotated about any axis in the three dimensional virtual environment. The second reason is the agents exist in a dense environment with many irregularly shaped models that need to be considered during planning. Lastly, Meta!Blast will be deployed in the high school classroom where computer hardware resources are limited, eliminating some planning techniques found in the literature. This thesis provides a practical solution for high DOF agents in dense environments using a combination of octree space partitioning, A* path-planning, and steering behaviors

Development of an autonomous mobile robot with planning and location in a structured environment

Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáWith the advance of technology mobile robots have been increasingly applied in the industry, performing repetitive work with high performance, and in environments that pose risks to human health. The present work plans and develops a mobile robot platform for the micromouse competition. The micromouse consists of a small autonomous mobile robot that, when placed in an unknown labyrinth, is able to map it, search for the best path between the starting point and the goal and travel it in the shortest possible time. To accomplish these tasks, the robot must be able to self-locate, map the maze as it traverses it and plan paths based on the map obtained. The developed self-localization method is based on the odometry, the laser sensors present in the robot and on a previous knowledge of the start point and the configuration of the environment. Several methodologies of locomotion in unknown environment and route planning are analyzed in order to obtain the combination with the best performance. In order to verify the results, the present work is developed in real environment, in 3D simulation and also with a hardware in the loop capability. Labyrinths from previous competitions are used as basis for comparing methodologies and validating results. At the end it presents the algorithm capable of fulfilling all the requirements of the micromouse competition together with the results of its evaluation run.Com o avanço da tecnologia, os robôs móveis têm sido cada vez mais aplicados na indústria, realizando trabalhos repetitivos com alto desempenho e em ambientes que expõem riscos à saúde humana. O presente trabalho planeja e desenvolve um robô móvel para a competição micromouse. O micromouse consiste em um pequeno robô autônomo que, ao ser colocado em um labirinto desconhecido, é capaz de mapeá-lo, procurar o melhor caminho entre o ponto de partida e o objetivo, e percorrê-lo no menor tempo possível. Para realizar estas tarefas, o robô deve ser capaz de se auto-localizar, mapear o labirinto enquanto o percorre e planejar caminhos com base no mapa obtido. O método de auto-localização desenvolvido baseia-se na odometria, nos sensores a laser presentes no robô e em um prévio conhecimento do ponto de início e da configuração do ambiente. Diversas metodologias de locomoção em ambiente desconhecido e planejamento de rotas são analisadas buscando-se obter a combinação com o melhor desempenho. Para averiguação de resultados o presente trabalho desenvolve-se em ambiente real e em simulação 3D com hardware in the loop. Labirintos de competições anteriores são utilizados de base para o comparativo de metodologias e validação de resultados. Ao final apresenta-se o algoritmo capaz de cumprir todas as exigências da competição micromouse juntamente com os resultados em sua corrida de avaliação