Local Movement Control with Neural Networks in the Small-Size League

Abstract. In the RoboCup small-size league, it is common to calculate the robot’s position calculated via a camera over the field as well as different kinds of artificial intelligence that’s run on a PC outside the field. In this case, the robot’s position must be predicted because of the various delays until the position data arrived at the robot. This paper focuses on the use of local sensors on the robot and a neural network to estimate the robot’s actual position. This paper shows how local sensors can compensate for the effect of latency times and how robot’s actual position can ascertained. Slip and friction effects that cannot be measured with local sensors are adjusted by a neutral network.

WS4D: SOA-Toolkits making embedded systems ready for Web Services

Abstract. The usage of the Service Oriented Architecture (SOA) paradigm currently changes the view on many enterprise applications. SOA allows the creation of modular and clearly defined software architectures that ensure a high grade of interoperability and reusability. As even small, resource-constraint networked devices get more and more powerful it is common sense to try to adopt the SOA paradigms to embedded device networks. This idea is substantiated in the specification of the Devices Profile for Web Services (DPWS), a standard that uses the primitives of the Web Services Architecture (WSA) to create a framework for interoperable and standardized communication between embedded devices. This paper introduces the WS4D initiative, a project that tries to provide a common open source platform for using DPWS in different environments. As a basis, we have developed three DPWS stacks that will be released as open source