J.L. Posadas

Agent-based distributed architecture for mobile robot control

Mobile robots are physical agents that move and interact continuously while embedded in a dynamic environment. Communications can be one of the most difficult parts of building robot architecture because of the increasing complexity of sensor and actuator hardware, and the interaction between intelligent features and real-time constraints. Currently, hybrid architectures offer the most widespread solutions for controlling intelligent mobile robots. This paper deals with the communications framework necessary to design and implement these architectures. The main goal of this work is to design a modular and portable architecture that allows the development of robot control systems. A multi-level and distributed architecture based on the reactive/deliberative paradigm is presented. Its main components are mobile software agents that interact through a distributed blackboard communications framework. These agents can be run on onboard processors, as well as on fixed workstations depending on their real-time restrictions. The presented control architecture has been tested in a real mobile robot and results demonstrate the effectiveness of distributing software agents to guarantee hard real-time execution.

Communications structure for sensory data in mobile robots

Abstract Mobile robotics development provides an excellent opportunity to experiment with various architectural solutions for distributed real-time systems. This is because of the increasing complexity of sensor and actuator hardware, and the interaction between intelligent features and real-time constraints. Currently, hybrid control structures seem to be the most widespread method of control. This paper describes a communications scenario resulting from hybrid structures. The YAIR robot and its communication infrastructure is described by addressing the control problems found and the solutions adopted. This paper presents a case study of implementing a hybrid communications system using the CAN bus. The worst-case message delay analysis for this bus is also presented, as well as the structure of identifiers defining its semantic possibilities. The deliberative part of the communication system is a developed object bus on TCP/IP protocol networks. The programming interface at this level takes the form of a distributed blackboard with extended properties such as a bind-notification mechanism and a temporal register recording the temporal firewall of information supplied. The overlap between both communication systems is a gateway service performing bi-directional mirroring over a set of CAN identifiers. Finally, a system test is presented. The test emphasises the intra-level gateway for validating performance and time expressiveness.

Communication jitter influence on control loops using protocols for distributedreal-time systems on can bus

Abstract The paper focuses on the behaviour of distributed control loops affected by the jitter derived from the communication latencies of CAN. The work uses a hybrid communication protocol between a pure TTP (Time Triggered Protocol) and ETP (Event Triggered Protocol), a reasonable choice for distributed real-time systems, as a reactive mobile robot. This hybrid protocol shares the time-slots to reduce the jitter effects. This guarantees fixed transmissions latencies for periodic messages, allowing also sporadic messages transmission, as is the case of alarms, or in long data blocks, by means of using shared TTP slots. The protocol assigns private time slots for realtime messages, and shared time slots for non real-time messages. Also, the protocol uses only a simple and static table. The implementation is validated by means of a quantitative comparison, using the data obtained from a simulation of a typical distributed control system consisting of an industrial process and a remote controller forming a closed control loop that uses CAN as its communication channel. In the simulation, the effect of the jitter introduced into the control loop is measured for the above mentioned communication protocols, and the obtained results from this simulation are also discussed.

QoS-Based Middleware Architecture for Distributed Control Systems

This paper presents an implementation of a middleware architecture to control distributed systems. The main objective is providing a QoS level between the communications layer and the control layer. This architecture is based on the use of a hierarchical communications structure called “logical namespace tree” and a structured set of control processes interconnected, called “logical sensors graph”. This architecture is named Frame Sensor Adapter Control (FSA-Ctrl). In this architecture both: communication layer and control layer can manage the QoS policies. The communication layer is based on the Data Distribution Service (DDS), a standard proposed by Object Management Group (OMG). Control layer is derived from the Sensor Web Enablement (SWE) model proposed by Open Geospatial Consortium (OGC). By means of QoS policies, control components can take important decisions about distributed questions, like components mobility or information redundancy detection.

Communications Structure for Sensor Fusion in Distributed Real Time Systems

Abstract This paper describes a communication system called SC (Sistema de Comunicaciones) that is suitable for real-time systems with distributed sensory architecture. This system has been implemented in the YAIR robot, an autonomous robot with intelligent sensors that produces different measurements about the environment and its position within it. To guarantee good response times, the sensory modules are connected using the CAN bus. The robots main controller executes a control algorithm that can be decomposed into smaller parts using a communications server. Thus, the execution can be shared between different processors connected through an Ethernet network.

From the Queue to the Quality of Service Policy: A Middleware Implementation

Quality of service policies in communications is one of the current trends in distributed systems based on middleware technology. To implement the QoS policies it is necessary to define some common parameters. The aim of the QoS policies is to optimize the user defined QoS parameters. This article describes how to obtain the common QoS parameters using message queues for the communications and control components of communication. The paper introduces the “Queue-based Quality of Service Cycle” concept for each middleware component. The QoS parameters are obtained directly from the queue parameters, and Quality of Service Policies controls directly the message queues to obtain the user-defined parameters values.

Communication system architecture to manage a containers terminal

Currently, containers are used in the transport of products because of the point-to-point service they offer. By using specialized cranes, operation in maritime transport and land transport can be achieved quickly. To optimize the operation costs, the whole management of terminal is computerized proportionally with the complexity of the problem. The multi-agent system paradigm seems suitable to solve the computational problem. The communication between agents and the corresponding data warehouse is made by means of a number of content-oriented communication channels. For supplying an organized message routes to the system, an event oriented communication system has been developed. The communication channels determine the communication system architecture. This paper describes how common communications architecture for agents can facilitate the management of an industrial system. The aim is to separate the agents of the communications. The communications system used is based on the distributed blackboard architecture.

An architecture to control mobile robots by means of code delegation and multi-agent systems

Abstract In this paper is presented an architecture to control mobile intelligent robots based on the hybrid reactive/deliberative paradigm. This architecture is multi-level and distributed, and their main components are mobile software agents that interact through a distributed blackboard communications system. These agents can run on processors on board or on fixed workstations depending on its real time constraints.

Vehicle Guidance with Distributed Selection of Emergent Behaviour

Abstract In this paper, a new architecture for vehicle guidance based on behavioural composition is proposed. The behaviour selection is distributed and based on the concept of motivation. The operation under real time constraints is obtained avoiding the deliberative cycle sense-plan-act and taking into account a behavioural description of basic tasks. The system is based on a blackboard architecture where objects and processes are located. The motivation processes allow us to modify the expected behavior of the system changing the action priorities. The described architecture is part of the YAIR project developed in the department, the project is focused on developing an embedded hardware and software architecture for autonomous robots.

Adding an Ontology to a Standardized QoS-Based MAS Middleware

In a Multi-Agent system, middleware is one of the components used to isolate control and communications. The use of standards in the implementation of an intelligent distributed system is always advantageous. This paper presents a middleware that provides support to a multi-agent system. Middleware is based on the standard Data Distribution Services (DDS), proposed by Object Management Group (OGM). Middleware organizes information by tree based ontology and provides a set of quality of service policies that agents can use to increase efficiency. DDS provides a set of quality of service policy. Joining quality of service policy and the ontology allows getting many advantages, among others the possibility of to conceal some details of the communications system to agents, the correct location of the agents in the distributed system, or the monitoring agents in terms of quality of service. For modeling the middleware architecture it has used UML class diagrams. As an example it has presented the implementation of a mobile robot navigation system through agents that model behaviors.