Abstract
Abstract. Compared to current industry standards future production systems will be more flexible and robust and will adapt to unforeseen states and events. Industrial robots will interact with each other as well as with human coworkers. To be able to act in such a dynamic environment, each acting entity ideally needs complete knowledge of its surroundings, concerning working materials as well as other working entities. Therefore new monitoring methods providing complete coverage for complex and changing working areas are needed. While single 3-D sensors already provide detailed information within their field of view, complete coverage of a complete work area can only be achieved by relying on a multitude of these sensors. However, to provide useful information all data of each sensor must be aligned to each other and fused into an overall world picture. To be able to align the data correctly, the position and orientation of each sensor must be known with sufficient exactness. In a quickly changing dynamic environment, the positions of sensors are not fixed, but must be adjusted to maintain optimal coverage. Therefore, the sensors need to autonomously align themselves in real time. This can be achieved by adding defined markers with given geometrical patterns to the environment which can be used for calibration and localization of each sensor. As soon as two sensors detect the same markers, their relative position to each other can be calculated. Additional anchor markers at fixed positions serve as global reference points for the base coordinate system. In this paper we present a prototype for a self-aligning monitoring system based on a robot operating system (ROS) and Microsoft Kinect. This system is capable of autonomous real-time calibration relative to and with respect to a global coordinate system as well as to detect and track defined objects within the working area.
Highlights
The ability to autonomously acquire new knowledge through interaction with the environment has been in the focus of significant research in the field of dynamic work area
In order to accurately manipulate the objects in a dynamic work area, a reliable and precise vision system is required in a robotic system to detect and track workpieces and to monitor the operation of the robots to accomplish manufacturing tasks such as assembly planning (Ewert et al, 2012)
From the calibration the location of the points on the marker and its counterparts in the ers are used for sensor self-alignment and simple geometrical markers are attached on objects to distinguish and track them, which enables the monitoring system to be aware of the real-time position and pose status of sensing elements, robots and objects in it
Summary
The ability to autonomously acquire new knowledge through interaction with the environment has been in the focus of significant research in the field of dynamic work area. The proposed 3-D monitoring system, comprised of multiple Microsoft Kinects, is capable of self-alignment through calibrating Kinect both individually and as a stereo camera with reference to markers to obtain the relative location information between each other, as well as their pose in the global coordinate system. From the calibration the location of the points on the marker and its counterparts in the ers are used for sensor self-alignment and simple geometrical markers are attached on objects to distinguish and track them, which enables the monitoring system to be aware of the real-time position and pose status of sensing elements, robots and objects in it. – Coordinate transformation: transform object pose which is relative to scene in camera coordinate system to global coordinate system
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