Microsoft robotics soccer challenge : movement optimization of a quadruped robot

Estágio realizado na Universidade de Aveiro e orientado pelo Prof. Doutor Nuno LauTese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Responsive Motion Control for Robot Soccer Navigation Using Adaptive Social Force Framework

This paper presents a modified Social Force Model (SFM) for navigation control of a soccer robot application. We modified the way of determining the parameter value of the gain factor, , of the SFM using the Fuzzy Inference System (FIS), so that the value of the gain factor, , is adaptive. The purpose of the gain factor adaptation is that the robot can move responsively but not over-reactive when it encounters an obstacle at high speed, which is a weakness of SFM with fixed parameters. Modification of SFM parameters using FIS is hereinafter referred to as the Fuzzy-based Social Force Model (F-SFM). We used this technique on a soccer robot with an omnidirectional drive platform with three motors. As an experiment, several modifications to the FIS rules were made and compared to the SFM with fixed parameters. The simulation-based experimental results show that the proposed method outperforms the SFM method with fixed-parameters, and the computation time does not differ significantly so that it can be applied for real implementation

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

A Real-time Global Optimal Path Planning for mobile robot in Dynamic Environment Based on Artificial Immune Approach

This paper illustrates a method to finding a globaloptimal path in a dynamic environment of known obstacles foran Mobile Robot (MR) to following a moving target. Firstly, theenvironment is defined by using a practical and standard graphtheory. Then, a suboptimal path is obtained by using DijkstraAlgorithm (DA) that is a standard graph searching method. Theadvantages of using DA are; elimination the uncertainness ofheuristic algorithms and increasing the speed, precision andperformance of them. Finally, Continuous Clonal SelectionAlgorithm (CCSA) that is combined with Negative SelectionAlgorithm (NSA) is used to improve the suboptimal path andderive global optimal path. To show the effectiveness of themethod it is compared with some other methods in this area

Magnetic suspension turbine flow meter

Measurement of liquid flow in certain area such as industrial plant is in critical. Inaccurate measurement can cause serious result. Most of the liquid flow are using Bernoulli principle‘s but in turbine flow meter the flow rate is determine differently by using kinetic energy. Turbine flow meter is one of flow rate transducer that widely used in metallurgical, petroleum, chemical and other industrial and agricultural areas, as shown in Figure 1.1. It is present as high precision of flow meter and when fluid flow troughs it the impeller that faces the fluid will rotate due to flow force exist. The rotation speed is directly proportional to the speed of fluid. During the process, the working states of impeller and bearing are very complicated due the interactive effects from the fluid axial thrust, impeller rotating, and static and dynamic components. In current turbine flow meter design, the common material use for meter bulk body is 1Cr18Ni9Ti, while for the blade 2Gr13 are used. Axis and bearing are made from stainless steel or carbide alloy. The space between the axis and bearing determines it minimum flow rate and life span, and also determines its measurement range (1:10~1:15 - maximum flow rate to minimum flow rate). Since the turbine has movable parts it can produce friction between the axis and ring during the operation. This will cause accuracy of the measurement decrease and can damage the impeller blade. In this research, the friction can be reduced by adopting the principle of magnetic suspension. Rotating shaft will levitate in the magnetic field due to the forces. Friction coefficient reduced because of rotating shaft rotates without abrasion and mechanical contact in space

Comparative Research on Robot Path Planning Based on GA-ACA and ACA-GA

The path planning for mobile robots is one of the core contents in the field of robotics research with complex, restrictive and nonlinear characteristics. It consists of automatically determining a path from an initial position of the robot to its final position. Due to classic approaches have several drawbacks, evolutionary methods such as Ant Colony Optimization Algorithm (ACA) and Genetic Algorithm (GA) are employed to solve the path planning efficiently

Dynamic path planning of multiple mobile robots

Ph.DDOCTOR OF PHILOSOPH

Control of free-ranging automated guided vehicles in container terminals

Container terminal automation has come to the fore during the last 20 years to improve their efficiency. Whereas a high level of automation has already been achieved in vertical handling operations (stacking cranes), horizontal container transport still has disincentives to the adoption of automated guided vehicles (AGVs) due to a high degree of operational complexity of vehicles. This feature has led to the employment of simple AGV control techniques while hindering the vehicles to utilise their maximum operational capability. In AGV dispatching, vehicles cannot amend ongoing delivery assignments although they have yet to receive the corresponding containers. Therefore, better AGV allocation plans would be discarded that can only be achieved by task reassignment. Also, because of the adoption of predetermined guide paths, AGVs are forced to deploy a highly limited range of their movement abilities while increasing required travel distances for handling container delivery jobs. To handle the two main issues, an AGV dispatching model and a fleet trajectory planning algorithm are proposed. The dispatcher achieves job assignment flexibility by allowing AGVs towards to container origins to abandon their current duty and receive new tasks. The trajectory planner advances Dubins curves to suggest diverse optional paths per origin-destination pair. It also amends vehicular acceleration rates for resolving conflicts between AGVs. In both of the models, the framework of simulated annealing was applied to resolve inherent time complexity. To test and evaluate the sophisticated AGV control models for vehicle dispatching and fleet trajectory planning, a bespoke simulation model is also proposed. A series of simulation tests were performed based on a real container terminal with several performance indicators, and it is identified that the presented dispatcher outperforms conventional vehicle dispatching heuristics in AGV arrival delay time and setup travel time, and the fleet trajectory planner can suggest shorter paths than the corresponding Manhattan distances, especially with fewer AGVs.Open Acces