The Use of the Blackboard Archiecture for a Decision making System for the Control of Craft with various Actuator and Movement Capabilities

This paper provides an overview of an approach to the control of multiple craft with heterogeneous movement and actuation characteristics that is based on the Blackboard software architecture. An overview of the Blackboard architecture is provided. Then, the operational and mission requirements that dictate the need for autonomous control are characterized and the utility of the Blackboard architecture is for meeting these requirements is discussed. The performance of a best-path solver and naïve solver are compared. The results demonstrate that the best-path solver outperforms the naïve solver in the amount of time taken to generate a solution, however, the number of solver-runs to be executed against the Blackboard must be sufficient to allow the lower individual-run times to offset the time required to propagate the data utilized by the best-path solver for solution generation through the database. The existence of other justifications for this approach (even if the number of runs for each data propagation cycle is not sufficient) is also discussed

A Contribution to Resource-Aware Architectures for Humanoid Robots

The goal of this work is to provide building blocks for resource-aware robot architectures. The topic of these blocks are data-driven generation of context-sensitive resource models, prediction of future resource utilizations, and resource-aware computer vision and motion planning algorithms. The implementation of these algorithms is based on resource-aware concepts and methodologies originating from the Transregional Collaborative Research Center "Invasive Computing" (SFB/TR 89)

Model-driven behavior specification for robotic teams

Summarization: Modern model-driven engineering and Agent-Oriented Software Engineering (AOSE) methods are rarely utilized in developing robotic software. In this paper, we show how a Model-Driven AOSE methodology can be used for specifying the behavior of multi-robot teams. Specifically, the Agent Systems Engineering Methodology (ASEME) was used for developing the software that realizes the behavior of a physical robot team competing in the Standard Platform League of the RoboCup competition (the robot soccer world cup). The team consists of four humanoid robots, which play soccer autonomously in real time utilizing the on-board sensing, processing, and actuating capabilities, while communicating and coordinating with each other in order to achieve their common goal of winning the game. Our work focuses on the challenges of coordinating the base functionalities (object recognition, localization, motion skills) within each robot (intra-agent control) and coordinating the activities of the robots towards a desired team behavior (inter-agent control). We discuss the difficulties we faced and present the solutions we gave to a number of practical issues, which, in our view, are inherent in applying any AOSE methodology to robotics. We demonstrate the added value of using an AOSE methodology in the development of robotic systems, as ASEME allowed for a platform-independent team behavior specification, automated a large part of the code generation process, and reduced the total development time.Παρουσιάστηκε στο: 11th International Conference on Autonomous Agents and Multiagent System