Publications

Due to the increasing scarcity of human operators and the fast development of technology, there is a trend towards higher levels of automation in warehouses. The increased automation level results in a large warehouse complexity and a correspondingly large warehouse design effort. To support the warehouse designer in his effort, Vanderlande Industries and the Embedded Systems Institute started the Falcon project in October 2006.

The paper focuses on maximizing the economic performance (throughput) of industrial printers under changing operating conditions. An interesting problem for these printers is the cold start, when printing components have to be heated up as soon as possible to have minimum delay for the first print. To maximize the throughput of these machines, it is important to determine an optimal heating strategy, as temperature considerably influences the print quality.

In recent years, autonomous mobile robots (AMR) have emerged as a means of transportation system in warehouses. The complexity of the transport tasks requires efficient high-level control, i.e. planning and scheduling of the tasks as well as low-level motion control of the robots. Hence, an efficient coordination between robots is needed to achieve flexibility, robustness and scalability of the transportationsystem.

Warehouse management and control systems are responsible for the operations in a warehouse. These systems are usually very complex due to the delivery requirements of the warehouse customers. These delivery requirements are often very specific for a group of customers, which makes it hard to reuse warehouse management and control functionality for other warehouses.

We consider the problem of constructing critical paths from incomplete information. In general, a directed acyclic graph of tasks with their execution times (i.e., a task graph) is necessary to extract critical paths. We assume, however, that only the set of tasks, and their start and end times are known, e.

Wireless sensor networks are typically operating in a dynamic context where events, such as moving sensor nodes and changing external interference, constantly impact the qualityof-service of the network. We present a distributed feedback control mechanism that actively balances multiple conflicting network-wide quality metrics, such as power consumption and end-to-end packet latency, for a heterogeneous wireless sensor network operating in a dynamic context.

Scenario-aware dataflow graphs (SADFs) efficiently model dynamic applications. The throughput of an application is an important metric to determine the performance of the system. For example, the number of frames per second output by a video decoder should always stay above a threshold that determines the quality of the system.

Practical experience reveals the characteristic properties of Wireless Body Area Networks (WBANs), signifying the need for a well-designed communication protocol. High mobility, stringent resource constraints, and low and time-variant quality of wireless links are some of the challenging issues in WBANs.

Adaptation of the network architecture through ondemand data forwarding is an efficient mechanism to provide robustness against long outages in WBANs. We developed an experimental testbed that provides online observation of the network behavior for different data propagation approaches in WBANs. The demonstration shows how different approaches deal with special challenges in WBANs such as low quality of wirelesslinks, topology variations due to posture changes, and mobility.

This paper describes the use of a formal method to support component-based development in the healthcare domain. The method is based on a commercial tool suite which combines formal modeling, compositional model checking, and code generation. The main approach of the tool suite will be explained and demonstrated from a user point of view.