Model Dan Teknik Kalibrasi Citra Untuk Sistem Autonomous Robot

Kalibrasi kamera dan pengolahan citra adalah faktor yang paling penting dalam computer vision. Beberapa teknik yang diterapkan dalam proses kalibrasi diantaranya adalah teknik linier, teknik non linier dan teknik dengan dua tahap. Teknik-teknik kalibrasi tersebut dapat dimanfaatkan untuk implementasi autonomous robotic khususnya dalam robotic soccer. Proses kalibrasi menjadikan faktor penentu keberhasilan dalam permainan robotic soccer. Saat ini tim yang berhasil melakukan kalibrasi kamera dengan baik adalah tim yang akanmampu memenangkan pertandingan

RoboCup: Robot Soccer!

A presentation in the Undergraduate Research Kaleidoscope: Library East Commons Performance Space, February 9, 2009Runtime: 20 seconds (07 finals)Runtime: 7:24 minutes (Bardagjy edit)Runtime: 7:24 minutes (Bardagjy)The RoboCup Small Size Robotic Soccer League exists to drive research in robotics and artificial intelligence and the systems which compose those fields. In the Small Size League, teams of five fully autonomous robots play soccer with an orange golf ball in two fifteen minute halves. Due to size restrictions (the robots must be 180 mm in diameter), significant integration and power issues, which are rarely seen in traditional robotics, must be overcome. Additionally, due to the fast paced fully autonomous nature of the game, sophisticated control systems must be developed including systems such as path planning, obstacle avoidance, strategy and artificial intelligence systems. In this work, the development of a robotic system to compete in the RoboCup Small Size Robotic Soccer league is described. This work describes a novel combination of subsystems including mechanical, electrical and software which will hopefully prove successful in this year’s competition. In particular, this work describes the development process and offers some insight into the decisions and trade offs which were made.Tucker Balc

Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams

Using Monte Carlo Search With Data Aggregation to Improve Robot Soccer Policies

RoboCup soccer competitions are considered among the most challenging multi-robot adversarial environments, due to their high dynamism and the partial observability of the environment. In this paper we introduce a method based on a combination of Monte Carlo search and data aggregation (MCSDA) to adapt discrete-action soccer policies for a defender robot to the strategy of the opponent team. By exploiting a simple representation of the domain, a supervised learning algorithm is trained over an initial collection of data consisting of several simulations of human expert policies. Monte Carlo policy rollouts are then generated and aggregated to previous data to improve the learned policy over multiple epochs and games. The proposed approach has been extensively tested both on a soccer-dedicated simulator and on real robots. Using this method, our learning robot soccer team achieves an improvement in ball interceptions, as well as a reduction in the number of opponents' goals. Together with a better performance, an overall more efficient positioning of the whole team within the field is achieved

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Performance evaluation of a distributed integrative architecture for robotics

The eld of robotics employs a vast amount of coupled sub-systems. These need to interact cooperatively and concurrently in order to yield the desired results. Some hybrid algorithms also require intensive cooperative interactions internally. The architecture proposed lends it- self amenable to problem domains that require rigorous calculations that are usually impeded by the capacity of a single machine, and incompatibility issues between software computing elements. Implementations are abstracted away from the physical hardware for ease of de- velopment and competition in simulation leagues. Monolithic developments are complex, and the desire for decoupled architectures arises. Decoupling also lowers the threshold for using distributed and parallel resources. The ability to re-use and re-combine components on de- mand, therefore is essential, while maintaining the necessary degree of interaction. For this reason we propose to build software components on top of a Service Oriented Architecture (SOA) using Web Services. An additional bene t is platform independence regarding both the operating system and the implementation language. The robot soccer platform as well as the associated simulation leagues are the target domain for the development. Furthermore are machine vision and remote process control related portions of the architecture currently in development and testing for industrial environments. We provide numerical data based on the Python frameworks ZSI and SOAPpy undermining the suitability of this approach for the eld of robotics. Response times of signi cantly less than 50 ms even for fully interpreted, dynamic languages provides hard information showing the feasibility of Web Services based SOAs even in time critical robotic applications

Neural network in computer vision for RoboCup middle size league

Robot World Cup Initiative (RoboCup) is a worldwide competition proposed to advance research in robotics and artificial intelligence. It has a league called RoboCup soccer devoted for soccer robots. Robotic soccer is a challenge because robots are mobile, fully autonomous, multi-agents, and they play on a dynamic environment. Moreover, robots must recognize the game entities, which is a crucial task during a game. A camera is usually used as an input system to recognize ball, opponents, soccer field, and so on. These elements may be recognized applying some tools of computational intelligence, for example an artificial neural network. This paper describes the application of an artificial neural network on middle size robotic football league, where a multilayer perceptron neural network is trained with the backpropagation algorithm, to classify elements on the image. The results show that an artificial neural network successfully classified the entities. They were recognized even when similar color entities were present on the image.info:eu-repo/semantics/publishedVersio

The robotic soccer turing test

One of the long-range objectives of the RoboCup initiative is to develop robotic technology to the point that, within the next fifty years, robots can play soccer at a competitive level against humans. In this paper we first make some comments on the Turing Test, proposed by Alan Turing in 1950, and then advance a proposal for a new kind of experiment to allow machines to compete against humans. We suggest to give human operators the same view of the playing field as that of autonomous robots, to let persons operate a team by driving them, and thus let humans play against a fully automatic robot team. In this way soccer matches of humans against robots could be held in the immediate future and the perceptual capabilities and ability of the autonomous robots could be more adequately assessed. We propose to held a “Robotic Turing Test Challenge” at RoboCup tournaments which would allow us to gauge the state of the art in this field