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

BEHAVIOR BASED CONTROL AND FUZZY Q-LEARNING FOR AUTONOMOUS FIVE LEGS ROBOT NAVIGATION

This paper presents collaboration of behavior based control and fuzzy Q-learning for five legs robot navigation systems. There are many fuzzy Q-learning algorithms that have been proposed to yield individual behavior like obstacle avoidance, find target and so on. However, for complicated tasks, it is needed to combine all behaviors in one control schema using behavior based control. Based this fact, this paper proposes a control schema that incorporate fuzzy q-learning in behavior based schema to overcome complicated tasks in navigation systems of autonomous five legs robot. In the proposed schema, there are two behaviors which is learned by fuzzy q-learning. Other behaviors is constructed in design step. All behaviors are coordinated by hierarchical hybrid coordination node. Simulation results demonstrate that the robot with proposed schema is able to learn the right policy, to avoid obstacle and to find the target. However, Fuzzy q-learning failed to give right policy for the robot to avoid collision in the corner location. Keywords : behavior based control, fuzzy q-learnin

IMPLEMENTATION OF A LOCALIZATION-ORIENTED HRI FOR WALKING ROBOTS IN THE ROBOCUP ENVIRONMENT

This paper presents the design and implementation of a human–robot interface capable of evaluating robot localization performance and maintaining full control of robot behaviors in the RoboCup domain. The system consists of legged robots, behavior modules, an overhead visual tracking system, and a graphic user interface. A human–robot communication framework is designed for executing cooperative and competitive processing tasks between users and robots by using object oriented and modularized software architecture, operability, and functionality. Some experimental results are presented to show the performance of the proposed system based on simulated and real-time information. </jats:p

A layered architecture using schematic plans for controlling mobile robots

Robotic soccer is a way of putting different developments in intelligent agents into practice, including not only problems such as multi-agent planning and coordination, but also physical problems related to vision and communication subsystems. In this work, we present the design used as the basis for a multi-agent system, implemented for controlling a team of robots, having as main goal to facilitate the testing of new theories developed on reasoning, knowledge representation, planning, agent communication, among others Artificial Intelligence techniques. The implementation of the system was carried out following a three-layer architecture which consists of a reactive layer, an executive layer and a deliberative layer, each of which is associated with a different level of abstraction. This layered design allows to construct a functional system with basic services that can be tested and refined progressively. We will focus our explanation on the executive layer, responsible for sensorial processing and the execution of schematic plans.Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Control and Localisation for the ISePorto Robotic Soccer Team

International Conference on Advanced Robotics, Coimbra, Portugal, Julho 2003This paper describes the control and localisation design and implementation status of the ISePorto robotic football team for participation in Robocup Middle Size League (F2000). The objectives guiding the project were the applications and research in hybrid control and coordination systems. The system has also an educational support role. A special attention is made to the custom design to allow the execution of complex manoeuvres and team coordinated behaviours. The robot has different pass, shot, and manoeuvre capabilities providing high level tactical and strategic planing and coordination

An efficacious method to assemble a modern multi-modal robotic team: dilemmas, challenges, possibilities and solutions

A modern multiagent robotic platform consists of a cooperative team of humans which develop a collaborative team of robots. The multi-modal nature of both the system and the team causes a complex problem which needs to be solved for optimum performance. Both the management and the technical aspect of a modern robotic team are explored in this Chapter in the platform of the RoboCup Competition. RoboCup is an example of such an environment where researchers from different disciplines join to develop a robotic team for completion as an evaluation challenge (Robocup, 2011). RoboCup competitions were first proposed by Mackworth in 1993. The main goal of this scientific competition is to exploit, improve and integrate the methods and techniques from robotics, machine vision and artificial intelligence disciplines to create an autonomous team of soccer playing robots(Kitano, 1997a; Kitano, 1997b; Kitano et al., 1997). Such experiment includes several challenges, from inviting an expert of specific field to the team to choosing bolts and nuts for each part of the robots. Usually each challenge has several possible solutions and choosing the best one is often challenging. We have participated in several world wide RoboCup competitions (Abdollahi, Samani et al. 2002, 2003 & 2004) and share our experience as an extensive instruction for setting up a modern robotic team including management and technical issues.Peer ReviewedPostprint (published version

A Hybrid Multi-Robot Control Architecture

Multi-robot systems provide system redundancy and enhanced capability versus single robot systems. Implementations of these systems are varied, each with specific design approaches geared towards an application domain. Some traditional single robot control architectures have been expanded for multi-robot systems, but these expansions predominantly focus on the addition of communication capabilities. Both design approaches are application specific and limit the generalizability of the system. This work presents a redesign of a common single robot architecture in order to provide a more sophisticated multi-robot system. The single robot architecture chosen for application is the Three Layer Architecture (TLA). The primary strength of TLA is in the ability to perform both reactive and deliberative decision making, enabling the robot to be both sophisticated and perform well in stochastic environments. The redesign of this architecture includes incorporation of the Unified Behavior Framework (UBF) into the controller layer and an addition of a sequencer-like layer (called a Coordinator) to accommodate the multi-robot system. These combine to provide a robust, independent, and taskable individual architecture along with improved cooperation and collaboration capabilities, in turn reducing communication overhead versus many traditional approaches. This multi-robot systems architecture is demonstrated on the RoboCup Soccer Simulator showing its ability to perform well in a dynamic environment where communication constraints are high

Multi-Agent Task Allocation for Robot Soccer

This is the published version. Copyright De GruyterThis paper models and analyzes task allocation methodologies for multiagent systems. The evaluation process was implemented as a collection of simulated soccer matches. A soccer-simulation software package was used as the test-bed as it provided the necessary features for implementing and testing the methodologies. The methodologies were tested through competitions with a number of available soccer strategies. Soccer game scores, communication, robustness, fault-tolerance, and replanning capabilities were the parameters used as the evaluation criteria for the mul1i-agent systems