A wireless sensor network-based approach to large-scale dimensional metrology

In many branches of industry, dimensional measurements have become an important part of the production cycle, in order to check product compliance with specifications. This task is not trivial especially when dealing with largescale dimensional measurements: the bigger the measurement dimensions are, the harder is to achieve high accuracies. Nowadays, the problem can be handled using many metrological systems, based on different technologies (e.g. optical, mechanical, electromagnetic). Each of these systems is more or less adequate, depending upon measuring conditions, user's experience and skill, or other factors such as time, cost, accuracy and portability. This article focuses on a new possible approach to large-scale dimensional metrology based on wireless sensor networks. Advantages and drawbacks of such approach are analysed and deeply discussed. Then, the article briefly presents a recent prototype system - the Mobile Spatial Coordinate-Measuring System (MScMS-II) - which has been developed at the Industrial Metrology and Quality Laboratory of DISPEA - Politecnico di Torino. The system seems to be suitable for performing dimensional measurements of large-size objects (sizes on the order of several meters). Owing to its distributed nature, the system - based on a wireless network of optical devices - is portable, fully scalable with respect to dimensions and shapes and easily adaptable to different working environments. Preliminary results of experimental tests, aimed at evaluating system performance as well as research perspectives for further improvements, are discusse

The concept of virtual landmarks in 3D multi-view fringe projection

For a 360-deg 3D measurement of an object the optical 3D sensor scan the object from different positions and the resulting single patches have to transform into a common global coordinate system so that these point clouds are patched together to generate the final complete 3D data set. Here we summarize and give some system realizations for the method, which we called "method of virtual landmarks" /1, 2/ realizing this local-global coordinate transformation without accurate mechanical sensor handling, sensor tracking, markers fixed on the object or point-cloud based registration techniques. For this the calculation of the co-ordinates, orientation of the sensor and local-global coordinate transformation is done by bundle adjustment methods, whereby the pixel of the so called connecting camera form 'virtual landmarks' for the registration of the single views in order to obtain a complete all around image. The flexibility makes the method useful for a wide range of system realizations which will be shown in the paper, like robot guided, handheld /3/ and tripod based systems for the flexible measurement of complex and/or large objects

View planning for 3D reconstruction using time-of-flight camera data as a-priori information

Solving the next best view (NBV) problem is an important task for automated 3D reconstruction. An NBV algorithm provides sensor positions, from which maximal information gain about the measurement object during the next scan can be expected. With no or limited information available during the first views, automatic data driven view planning performs suboptimal. In order to overcome these inefficiencies during startup phase, we examined the use of time-of-flight (TOF) camera data to improve view planning. The additional low resolution 3D information, gathered during sensor movement, allows to plan even the first scans customized to previously unknown objects. Measurement examples using a robot mounted fringe projection stereo 3D scanner with a TOF camera are presented

Comparison and evaluation of correspondence finding methods in 3D measurement systems using fringe projection

Three different methods to realize point correspondences in 3D measurement systems based on fringe projection are described and compared concerning accuracy, sensitivity, and handling. Advantages and disadvantages of the three techniques are discussed. A suggestion is made to combine the principles in order to achieve an improved completeness of the measurements. The principle of a virtual image point raster which is the basis of the combination of the methods is explained. A model to describe the random error of a 3D point measurement for the three methods is established and described. Simulations and real measurements confirm this error model. Experiments are described and results are presented

High Performance, low latency 3D sensor network for live full object reconstruction

With recent advances in high speed 3D measurement sensor technologies, focus changes from merely acquiring 3D sensor data fast. An advanced application area is to fusion multiple sensor streams into a complete object representation without occlusions. Even more challenging is how to process the high speed 3D streams online, instead of the current offline processing approaches. To this end we combine our cost-effective GOBO slide-based pattern projector (GOes Before Optics) with commodity GigE vision network sensors to a multi sensor system for complete online monitoring capabilities. The targeted use-case has to deal with partial occlusions and low latency requirements for machine control. Specifically, three active NIR stereo 3D sensors are aggregated through a 10Gb-Ethernet-switch and processed by a single GPU assisted workstation. Thus a combined continuous data-stream of up to 78 million 3D points is calculated online per second out of a raw 2D data-stream of up to approximately 1250 Mb/s. The systems latency for simpler 3D analysis task, like movement tracking, is ≤ 200 ms