Integration of a stereo vision system into an autonomous underwater vehicle for pipe manipulation tasks

Integration of stereo vision system for detecting cylindrical pipes in autonomous underwater interventions.Vision-based object detection, pose estimation, and tracking for manipulation of submerged items.Experiments include successful underwater grasping of target pipe in different light conditions. Display Omitted Underwater object detection and recognition using computer vision are challenging tasks due to the poor light condition of submerged environments. For intervention missions requiring grasping and manipulation of submerged objects, a vision system must provide an Autonomous Underwater Vehicles (AUV) with object detection, localization and tracking capabilities. In this paper, we describe the integration of a vision system in the MARIS intervention AUV and its configuration for detecting cylindrical pipes, a typical artifact of interest in underwater operations. Pipe edges are tracked using an alpha-beta filter to achieve robustness and return a reliable pose estimation even in case of partial pipe visibility. Experiments in an outdoor water pool in different light conditions show that the adopted algorithmic approach allows detection of target pipes and provides a sufficiently accurate estimation of their pose even when they become partially visible, thereby supporting the AUV in several successful pipe grasping operations.

[1]  Huimin Lu,et al.  Contrast enhancement for images in turbid water. , 2015, Journal of the Optical Society of America. A, Optics, image science, and vision.

[2]  Pere Ridao,et al.  I-AUV Mechatronics Integration for the TRIDENT FP7 Project , 2015, IEEE/ASME Transactions on Mechatronics.

[3]  Giuseppe Casalino,et al.  A Novel Practical Technique to Integrate Inequality Control Objectives and Task Transitions in Priority Based Control , 2016, J. Intell. Robotic Syst..

[4]  P. Ridao,et al.  Multipurpose autonomous underwater intervention: A systems integration perspective , 2012, 2012 20th Mediterranean Conference on Control & Automation (MED).

[5]  Hanumant Singh,et al.  Visually Navigating the RMS Titanic with SLAM Information Filters , 2005, Robotics: Science and Systems.

[6]  Stefano Caselli,et al.  Investigation of Vision-Based Underwater Object Detection with Multiple Datasets , 2015 .

[7]  Carlos Silvestre,et al.  TRIDENT An European project targeted to increase the autonomy levels for underwater intervention missions , 2013, 2013 OCEANS - San Diego.

[8]  Giuseppe Casalino,et al.  Cooperation between autonomous underwater vehicle manipulations systems with minimal information exchange , 2015, OCEANS 2015 - Genova.

[9]  Konstantinos Kyriakopoulos,et al.  PANDORA - Persistent Autonomy Through Learning, Adaptation, Observation and Replanning , 2012 .

[10]  Stefan B. Williams,et al.  Generation and visualization of large‐scale three‐dimensional reconstructions from underwater robotic surveys , 2010, J. Field Robotics.

[11]  Luc Jaulin,et al.  Color-based underwater object recognition using water light attenuation , 2012, Intell. Serv. Robotics.

[12]  Arjan Kuijper,et al.  Underwater stereo calibration utilizing virtual object points , 2015, OCEANS 2015 - Genova.

[13]  Fabio Oleari,et al.  Underwater intervention robotics: An outline of the Italian national project Maris , 2016 .

[14]  Penny Probert Smith,et al.  UNION: underwater intelligent operation and navigation , 1998, IEEE Robotics Autom. Mag..

[15]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[16]  Stefano Caselli,et al.  An underwater stereo vision system: From design to deployment and dataset acquisition , 2015, OCEANS 2015 - Genova.

[17]  Mehdi Loueipour,et al.  Robotics vision-based system for an underwater pipeline and cable tracker , 2009, OCEANS 2009-EUROPE.

[18]  Pedro J. Sanz,et al.  Robotic Manipulation Within the Underwater Mission Planning Context , 2015 .

[19]  Fabjan Kallasi,et al.  Computer vision in underwater environments: A multiscale graph segmentation approach , 2015, OCEANS 2015 - Genova.

[20]  Stefan B. Williams,et al.  True Color Correction of Autonomous Underwater Vehicle Imagery , 2016, J. Field Robotics.

[21]  Antonella Ferrara,et al.  AMADEUS: advanced manipulation for deep underwater sampling , 1997, IEEE Robotics Autom. Mag..

[22]  G. Buchsbaum A spatial processor model for object colour perception , 1980 .

[23]  Joaquim Salvi,et al.  Intervention Payload for Valve Turning with an AUV , 2015, EUROCAST.

[24]  Visesh Chari,et al.  A theory of multi-layer flat refractive geometry , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Oleari Fabio,et al.  Performance Evaluation of a Low-Cost Stereo Vision System for Underwater Object Detection , 2014 .

[26]  Cuneyt Akinlar,et al.  EDLines: A real-time line segment detector with a false detection control , 2011, Pattern Recognit. Lett..