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ABSTRACT:In this paper we are presenting work done within the joint development project ANKommEn. It deals with the development of a highly automated robotic system for fast data acquisition in civil disaster scenarios. One of the main requirements is a versatile system, hence the concept embraces a machine cluster consisting of multiple fundamentally different robotic platforms. To cover a large variety of potential deployment scenarios, neither the absolute amount of participants, nor the precise individual layout of each platform shall be restricted within the conceptual design. Thus leading to a variety of special requirements, like onboard and online data processing capabilities for each individual participant and efficient data exchange structures, allowing reliable random data exchange between individual robots. We are demonstrating the functionality and performance by means of a distributed mapping system evaluated with real world data in a challenging urban and rural indoor / outdoor scenarios.

<p><strong>Abstract.</strong> Disasters such as floods, large fires, landslides, avalanches, or forest fires are often inevitable and cannot be fully prevented, but their impact can be minimized with sound disaster management strategies aided by the latest technological advancements. A key factor affecting these strategies is the time, where any delay can result in dramatic consequences and potentially human losses. Therefore, a quick situation report of the disaster is highly demanded, but still not an easy task because - in most cases - a priori known spatial information like map data or geo-databases, are outdated. In addition, visual and geometric information on the current situation is needed to help rescue teams and first responders. From this point of view, we came up to the main idea of the joint research project ANKommEn and its extension ANKommEn 2 (german acronym for Automated Navigation and Communication for Exploration). The project idea embodies an exploratory investigation to be smart in providing correct and timely geodata that can help in emergency cases; especially in support decision making in emergency risk management. For this purpose, automated unmanned systems, both ground (UGV) and airborne (UAV), are being developed to provide up-to-date information of rescue scenarios.</p>

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