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Compared to current industry standards future production systems will bemore flexible and robust and will adapt to unforeseen states and events.Industrial robots will interact with each other as well as with humancoworkers. To be able to act in such a dynamic environment, each actingentity ideally needs complete knowledge of its surroundings, concerningworking materials as well as other working entities. Therefore newmonitoring methods providing complete coverage for complex and changingworking areas are needed. While single 3-D sensors already provide detailedinformation within their field of view, complete coverage of a complete workarea can only be achieved by relying on a multitude of these sensors.  However, to provide useful information all data of each sensor must bealigned to each other and fused into an overall world picture. To be able toalign the data correctly, the position and orientation of each sensor mustbe known with sufficient exactness. In a quickly changing dynamicenvironment, the positions of sensors are not fixed, but must be adjusted tomaintain optimal coverage. Therefore, the sensors need to autonomously alignthemselves in real time. This can be achieved by adding defined markers withgiven geometrical patterns to the environment which can be used forcalibration and localization of each sensor. As soon as two sensors detectthe same markers, their relative position to each other can be calculated.Additional anchor markers at fixed positions serve as global referencepoints for the base coordinate system.  In this paper we present a prototype for a self-aligning monitoring systembased on a robot operating system (ROS) and Microsoft Kinect. This system is capable of autonomousreal-time calibration relative to and with respect to a globalcoordinate system as well as to detect and track defined objects within theworking area

Work area monitoring in dynamic environments using multiple auto-aligning 3-D sensors