Developed societies have a high level of preparedness for natural or man-made disasters. But such incidents cannot be completely prevented, and when an incident like an earthquake or an accident in a chemical or nuclear plant hits a populated area, rescue teams need to be employed. In such situations it is a necessity for rescue teams to get a quick overview of the situation in order to identify possible locations of victims that need to be rescued and dangerous locations that need to be secured. Rescue forces must operate quickly in order to save lives, and they often need to operate in dangerous environments. Hence, robot-supported systems are increasingly used to support and accelerate search operations. The objective of the SENEKA concept is to network the various robots and sensor systems used by first responders in order to make the search for victims and survivors more quick and efficient. SENEKA targets the integration of the robot-sensor network into the operation procedures of the rescue teams. The aim of this paper is to inform on the goals and first research results of the ongoing joint research project SENEKA

Abstract-Many industrial domains rely on vision-based applications which require to comply with severe performance and embedded requirements. TULIPP will develop a reference platform, which consists of a hardware system, a tool chain and a real-time operating system. This platform defines implementation rules and interfaces to tackle power consumption issues while delivering high, energy efficient and guaranteed computing performance for image processing applications. Using this reference platform will enable designers to develop a complete solution at a reduced cost to meet the typical embedded systems requirements: Size, Weight and Power. Moreover, for less constrained systems which performance requirements cannot be fulfilled by one instance of the platform, the reference platform will also be scalable so that the resulting boards can be chained for higher processing power. The instance of the reference platform developed during the project will be use-case driven and split between the implementation of: a reference hardware architecture -a scalable low-power board; a low-power operating system and image processing libraries; a productivityenhancing tool chain. It will lead to three proof-of-concept demonstrators across different application domains: real-time and low-power medical image processing product prototype of surgical X-ray system (mobile c-arm); embedded image processing systems within Unmanned Aerial Vehicles (UAVs); automotive real time embedded systems for driver assistance. TULIPP will set up an ecosystem and will closely work with standardization organizations to propose new standards derived from its reference platform to the industry.

The paper describes an autonomous water vehicle (ASV) capable of autonomously mapping shallow water environments above and below the water surface. Over the past two years, Fraunhofer IOSB has developed a system that is fully electrified and equipped with extensive sensor technology (multibeam sonar, lidar, cameras, IMU, GNSS). For autonomous navigation, the complete processing pipeline was implemented, from obstacle detection and avoidance to trajectory planning and control to multi-sensor localization and mapping. Above water, both lidar-based mapping and photogrammetric methods are used; underwater, bathymetry data is obtained using sonar. The interface to the operator is realized by an interactive digital map table, which allows intuitive mission specification and evaluation.

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