3D Sensors for Sewer Inspection: A Quantitative Review and Analysis

Automating inspection of critical infrastructure such as sewer systems will help utilities optimize maintenance and replacement schedules. The current inspection process consists of manual reviews of video as an operator controls a sewer inspection vehicle remotely. The process is slow, labor-intensive, and expensive and presents a huge potential for automation. With this work, we address a central component of the next generation of robotic inspection of sewers, namely the choice of 3D sensing technology. We investigate three prominent techniques for 3D vision: passive stereo, active stereo, and time-of-flight (ToF). The Realsense D435 camera is chosen as the representative of the first two techniques wheres the PMD CamBoard pico flexx represents ToF. The 3D reconstruction performance of the sensors is assessed in both a laboratory setup and in an outdoor above-ground setup. The acquired point clouds from the sensors are compared with reference 3D models using the cloud-to-mesh metric. The reconstruction performance of the sensors is tested with respect to different illuminance levels and different levels of water in the pipes. The results of the tests show that the ToF-based point cloud from the pico flexx is superior to the output of the active and passive stereo cameras.

Vision and RTLS Safety Implementation in an Experimental Human—Robot Collaboration Scenario

Human–robot collaboration is becoming ever more widespread in industry because of its adaptability. Conventional safety elements are used when converting a workplace into a collaborative one, although new technologies are becoming more widespread. This work proposes a safe robotic workplace that can adapt its operation and speed depending on the surrounding stimuli. The benefit lies in its use of promising technologies that combine safety and collaboration. Using a depth camera operating on the passive stereo principle, safety zones are created around the robotic workplace, while objects moving around the workplace are identified, including their distance from the robotic system. Passive stereo employs two colour streams that enable distance computation based on pixel shift. The colour stream is also used in the human identification process. Human identification is achieved using the Histogram of Oriented Gradients, pre-learned precisely for this purpose. The workplace also features autonomous trolleys for material supply. Unequivocal trolley identification is achieved using a real-time location system through tags placed on each trolley. The robotic workplace’s speed and the halting of its work depend on the positions of objects within safety zones. The entry of a trolley with an exception to a safety zone does not affect the workplace speed. This work simulates individual scenarios that may occur at a robotic workplace with an emphasis on compliance with safety measures. The novelty lies in the integration of a real-time location system into a vision-based safety system, which are not new technologies by themselves, but their interconnection to achieve exception handling in order to reduce downtimes in the collaborative robotic system is innovative.

Optical Tracking of a Tactile Probe for the Reverse Engineering of Industrial Impellers

Different sensor technologies are available for dimensional metrology and reverse engineering processes. Tactile systems, optical sensors, and computed tomography (CT) are being used to an increasing extent in various industrial contexts. However, each technique has its own peculiarities, which may limit its usability in demanding applications. The measurement of complex shapes, such as those including hidden and twisted geometries, could be better afforded by multisensor systems combining the advantages of two or more data acquisition technologies. In this paper, a fully automatic multisensor methodology has been developed with the aim at performing accurate and reliable measurements of both external and internal geometries of industrial components. The methodology is based on tracking a customized hand-held tactile probe by a passive stereo vision system. The imaging system automatically tracks the probe by means of photogrammetric measurements of markers distributed over a plate rigidly assembled to the tactile frame. Moreover, the passive stereo system is activated with a structured light projector in order to provide full-field scanning data, which integrate the point-by-point measurements. The use of the same stereo vision system for both tactile probe tracking and structured light scanning allows the two different sensors to express measurement data in the same reference system, thus preventing inaccuracies due to misalignment errors occurring in the registration phase. The tactile methodology has been validated by measuring primitive shapes. Moreover, the effectiveness of the integration between tactile probing and optical scanning has been experienced by reconstructing twisted and internal shapes of industrial impellers.