Low Cost Swarm Based Diligent Cargo Transit System

The goal of this paper is to present the design and development of a low cost cargo transit system which can be adapted in developing countries like India where there is abundant and cheap human labour which makes the process of automation in any industry a challenge to innovators. The need of the hour is an automation system that can diligently transfer cargo from one place to another and minimize human intervention in the cargo transit industry. Therefore, a solution is being proposed which could effectively bring down human labour and the resources needed to implement them. The reduction in human labour and resources is achieved by the use of low cost components and very limited modification of the surroundings and the existing vehicles themselves. The operation of the cargo transit system has been verified and the relevant results are presented. An economical and robust cargo transit system is designed and implemented.Comment: 6 pages, 9 figures, 1 block diagra

Robot Path Planning Using Cellular Automata and Genetic Algorithm

In path planning Problems, a complete description of robot geometry, environments and obstacle are presented; the main goal is routing, moving from source to destination, without dealing with obstacles. Also, the existing route should be optimal. The definition of optimality in routing is the same as minimizing the route, in other words, the best possible route to reach the destination. In most of the routing methods, the environment is known, although, in reality, environments are unpredictable;But with the help of simple methods and simple changes in the overall program, one can see a good view of the route and obstacles ahead. In this research, a method for solving robot routing problem using cellular automata and genetic algorithm is presented.In this method, the working space model and the objective function calculation are defined by cellular automata, and the generation of initial responses and acceptable responses is done using the genetic algorithm.During the experiments and the comparison we made, we found that the proposed algorithm yielded a path of 28.48 if the lengths of the paths obtained in an environment similar to the other algorithm of 15 / 32, 29.5 and 29.49, which is more than the proposed method

Evolutionary Distributed Control of a Biologically Inspired Modular Robot

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Optimal path planning algorithm for swarm robots using bat algorithm with mutation (bam)

In robot navigation, path planning is always the most crucial problem where robots should be able to move from starting position to goal position without colliding into any obstacle. This is because robot is unable to plan an optimum path in a known situation and obstacles available increases the difficulty for robot to move according to the planned path in an environment. The current research in robot navigation is to implement an obstacle avoidance algorithm to a single mobile robot to realize the path planning of a mobile robot. However, there is still room for improvement such as implementing the obstacle avoidance algorithm into swarm robot. The objective of this study is to propose Bat Algorithm with Mutation (BAM) for solving the problem of obstacle avoidance of mobile robots. This project is completed by creating a wheeled mobile robot where the robot uses a P controller. Next, robot is trained to travel from one point to another point and inserted into a virtual environment with static obstacle. The obstacle avoidance algorithm is then implemented to the robot. Lastly, it can be seen that the robot is able to move in the planned path without colliding with the obstacle in the environment

Arquitectura multiagentes para un equipo de pequeños robots

 Using the distributed artificial intelligence and the distribuited robotics as a frame of reference, particularly the RoboCup World Championship, in this work and architecture for multiple mobile, autonomous, rational and coordinated agents is proposed. This architecture is composed of a mechanism of reasoning or automatic decision making, a functional and control structure, an artificial vision system, a navigation system, and a robotic architecture for a team of small minibots with capacity of acting at the Small Size League. In the design, development and construction of the components are coupled methods and techniques of Emergent Computation with models based on the traditional knowledge representation of Artificial Intelligence, producing algorithms that combine properties as adaptibility, robustness, uniformity with representation, inference and universality. The Agents are conformed by mechanisms that integrate sensors out of the body of the robot with effectors embedded in the robot and processes behaviors which are exhibited by the minibots while they operate in real time. The execution and performance of the architecture proposed had been experimented and evaluated through the implementation of a Multiagent System thar allows the operation of one or more robots on a testbed conformed by a football field made to comply with RoboCup rules. Tomando como marco de referencia a la Inteligencia Artificial Distribuida y la Robótica Distribuida, particularmente a la Copa Mundial de Fútbol de Robots RoboCup, en este trabajo se propone una arquitectura para múltiples agentes móviles, autónomos, racionales, coordinados, la cual comprende un modelo de organización para los agentes, una estructura funcional y de control para cada uno de los agentes, un mecanismo de razonamiento o toma de decisiones automáticas, un sistema de visión artificial, un sistema de navegación y una arquitectura para un equipo de pequeños minibots con capacidad de actuación en la Liga de Pequeños Robots. En el diseño, desarrollo y construcción de estos componentes se acoplan métodos y técnicas clasificadas dentro de Computación Emergente con modelos basados en la representación tradicional de la Inteligencia Artificial, dando lugar a algoritmos que combinan las propiedades de adaptabilidad, robustez y uniformidad con la representación, inferencia y la universalidad. Los Agentes están conformados por mecanismos que integran sensores ubicados fuera del cuerpo del robot con efectores instalados en el robot y procesos que se ejecutan en forma conjunta sobre diferentes dispositivos de cómputo, dotándolos de comportamientos competitivos y cooperativos los cuales son exhibidos por los minibots al operar en tiempo real. La ejecución y rendimiento de la arquitectura propuesta ha sido experimentada y evaluada mediante la implementación de un Sistema Multiagentes que permite la operación de uno o más robots en un ambiente de trabajo constituido por un campo de fútbol, construido de acuerdo a las normativas de RoboCup

Abstracting Multidimensional Concepts for Multilevel Decision Making in Multirobot Systems

Multirobot control architectures often require robotic tasks to be well defined before allocation. In complex missions, it is often difficult to decompose an objective into a set of well defined tasks; human operators generate a simplified representation based on experience and estimation. The result is a set of robot roles, which are not best suited to accomplishing those objectives. This thesis presents an alternative approach to generating multirobot control algorithms using task abstraction. By carefully analysing data recorded from similar systems a multidimensional and multilevel representation of the mission can be abstracted, which can be subsequently converted into a robotic controller. This work, which focuses on the control of a team of robots to play the complex game of football, is divided into three sections: In the first section we investigate the use of spatial structures in team games. Experimental results show that cooperative teams beat groups of individuals when competing for space and that controlling space is important in the game of robot football. In the second section, we generate a multilevel representation of robot football based on spatial structures measured in recorded matches. By differentiating between spatial configurations appearing in desirable and undesirable situations, we can abstract a strategy composed of the more desirable structures. In the third section, five partial strategies are generated, based on the abstracted structures, and a suitable controller is devised. A set of experiments shows the success of the method in reproducing those key structures in a multirobot system. Finally, we compile our methods into a formal architecture for task abstraction and control. The thesis concludes that generating multirobot control algorithms using task abstraction is appropriate for problems which are complex, weakly-defined, multilevel, dynamic, competitive, unpredictable, and which display emergent properties

Common metrics for cellular automata models of complex systems

The creation and use of models is critical not only to the scientific process, but also to life in general. Selected features of a system are abstracted into a model that can then be used to gain knowledge of the workings of the observed system and even anticipate its future behaviour. A key feature of the modelling process is the identification of commonality. This allows previous experience of one model to be used in a new or unfamiliar situation. This recognition of commonality between models allows standards to be formed, especially in areas such as measurement. How everyday physical objects are measured is built on an ingrained acceptance of their underlying commonality. Complex systems, often with their layers of interwoven interactions, are harder to model and, therefore, to measure and predict. Indeed, the inability to compute and model a complex system, except at a localised and temporal level, can be seen as one of its defining attributes. The establishing of commonality between complex systems provides the opportunity to find common metrics. This work looks at two dimensional cellular automata, which are widely used as a simple modelling tool for a variety of systems. This has led to a very diverse range of systems using a common modelling environment based on a lattice of cells. This provides a possible common link between systems using cellular automata that could be exploited to find a common metric that provided information on a diverse range of systems. An enhancement of a categorisation of cellular automata model types used for biological studies is proposed and expanded to include other disciplines. The thesis outlines a new metric, the C-Value, created by the author. This metric, based on the connectedness of the active elements on the cellular automata grid, is then tested with three models built to represent three of the four categories of cellular automata model types. The results show that the new C-Value provides a good indicator of the gathering of active cells on a grid into a single, compact cluster and of indicating, when correlated with the mean density of active cells on the lattice, that their distribution is random. This provides a range to define the disordered and ordered state of a grid. The use of the C-Value in a localised context shows potential for identifying patterns of clusters on the grid