Fitting primitive shapes in point clouds: a practical approach to improve autonomous underwater grasp specification of unknown objects

This article presents research on the subject of autonomous underwater robot manipulation. Ongoing research in underwater robotics intends to increase the autonomy of intervention operations that require physical interaction in order to achieve social benefits in fields such as archaeology or biology that cannot afford the expenses of costly underwater operations using remote operated vehicles. Autonomous grasping is still a very challenging skill, especially in underwater environments, with highly unstructured scenarios, limited availability of sensors and adverse conditions that affect the robot perception and control systems. To tackle these issues, we propose the use of vision and segmentation techniques that aim to improve the specification of grasping operations on underwater primitive shaped objects. Several sources of stereo information are used to gather 3D information in order to obtain a model of the object. Using a RANSAC segmentation algorithm, the model parameters are estimated and a set of feasible grasps are computed. This approach is validated in both simulated and real underwater scenarios.This research was partly supported by Spanish Ministry of Research and Innovation DPI2011-27977-C03 (TRITON Project), by Foundation Caixa Castelló Bancaixa PI-1B2011-17, by Universitat Jaume I PhD grants PREDOC/2012/47 and PREDOC/ 2013/46, and by Generalitat Valenciana PhD grant ACIF/2014/298

Visually-Guided Manipulation Techniques for Robotic Autonomous Underwater Panel Interventions

The long term of this ongoing research has to do with increasing the autonomy levels for underwater intervention missions. Bearing in mind that the speci c mission to face has been the intervention on a panel, in this paper some results in di erent development stages are presented by using the real mechatronics and the panel mockup. Furthermore, some details are highlighted describing two methodologies implemented for the required visually-guided manipulation algorithms, and also a roadmap explaining the di erent testbeds used for experimental validation, in increasing complexity order, are presented. It is worth mentioning that the aforementioned results would be impossible without previous generated know-how for both, the complete developed mechatronics for the autonomous underwater vehicle for intervention, and the required 3D simulation tool. In summary, thanks to the implemented approach, the intervention system is able to control the way in which the gripper approximates and manipulates the two panel devices (i.e. a valve and a connector) in autonomous manner and, results in di erent scenarios demonstrate the reliability and feasibility of this autonomous intervention system in water tank and pool conditions.This work was partly supported by Spanish Ministry of Research and Innovation DPI2011-27977-C03 (TRITON Project) and DPI2014-57746-C3 (MERBOTS Project), by Foundation Caixa Castell o-Bancaixa and Universitat Jaume I grant PID2010-12, by Universitat Jaume I PhD grants PREDOC/2012/47 and PREDOC/2013/46, and by Generalitat Valenciana PhD grant ACIF/2014/298. We would like also to acknowledge the support of our partners inside the Spanish Coordinated Projects TRITON and MERBOTS: Universitat de les Illes Balears, UIB (subprojects VISUAL2 and SUPERION) and Universitat de Girona, UdG (subprojects COMAROB and ARCHROV)

Increasing underwater manipulation autonomy using segmentation and visual tracking

Comunicació presentada a Oceans 2017 Conference, Aberdeen, 19-22 June 2017The present research in underwater robotics aims to increase the autonomy of manipulation operations in fields such as archaeology or biology, that cannot afford costly underwater interventions using traditional Remote Operated Vehicles (ROV). This paper describes a work towards the long term goal of autonomous underwater manipulation. Autonomous grasping, with limited sensors and water conditions which affect the robot systems, is a growing skill in underwater scenarios. Here we present a framework that uses vision, segmentation, user interfaces and grasp planning to perform visually guided manipulation to improve the specification of grasping operations. With it, a user commands and supervises the robot to recover cylinder shaped objects, a very common restriction in archaeological scenarios. This framework, though, can be expanded to detect other kind of objects. Information of the environment is gathered with stereo cameras and laser reconstruction methods to obtain a model of the object's graspable area. A RANSAC segmentation algorithm is used to estimate the model parameters and the best grasp is presented to the user in an intuitive user interface. The grasp is then executed by the robot. This approach has been tested in simulation and in water tank conditions

Exploring 3-D Reconstruction Techniques: A Benchmarking Tool for Underwater Robotics

When the results of research in the field of robotics are presented to the scientific community, the same question is asked repeatedly: Are the results really reproducible? Regarding benchmarking issues, some technological areas where complex mechatronic devices, such as robots, have a central role are very far from other research areas like physics or chemistry, to name but a few, where reproducibility is always mandatory. Aside from mechatronic complexities, the comparison between two different algorithms in the same conditions is influenced by the experimental validation scenario. In underwater environments, the difficulties for benchmarking characterization increase substantially. This is especially true when the test bed is the sea where uncertainty is high. It is the aim of this article to present a software tool which enables a comparison between two different algorithms when the algorithms are being used to solve the same problem in water tank conditions. This is a preliminary stage before the final validation on the seabed. The evaluated algorithms fall into the three-dimensional (3-D) image reconstruction context, as a prior step to their autonomous manipulation. Performance results are presented for both simulation and real water tank conditions

Guidelines for the use of flow cytometry and cell sorting in immunological studies

International audienceThe classical model of hematopoiesis established in the mouse postulates that lymphoid cells originate from a founder population of common lymphoid progenitors. Here, using a modeling approach in humanized mice, we showed that human lymphoid development stemmed from distinct populations of CD127(-) and CD127(+) early lymphoid progenitors (ELPs). Combining molecular analyses with in vitro and in vivo functional assays, we demonstrated that CD127(-) and CD127(+) ELPs emerged independently from lympho-mono-dendritic progenitors, responded differently to Notch1 signals, underwent divergent modes of lineage restriction, and displayed both common and specific differentiation potentials. Whereas CD127(-) ELPs comprised precursors of T cells, marginal zone B cells, and natural killer (NK) and innate lymphoid cells (ILCs), CD127(+) ELPs supported production of all NK cell, ILC, and B cell populations but lacked T potential. On the basis of these results, we propose a "two-family" model of human lymphoid development that differs from the prevailing model of hematopoiesis