@conference {282, title = {Increasing underwater manipulation autonomy using segmentation and visual tracking}, booktitle = {OCEANS 2017 - Aberdeen}, year = {2017}, month = {10/2017}, publisher = {IEEE}, organization = {IEEE}, address = {Aberdeen (UK)}, abstract = {

The 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\&$\#$39;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.

}, keywords = {archaeological scenarios, archaeology, autonomous grasping, autonomous underwater manipulation, Cameras, Computational modeling, cylinder shaped objects, grasping operations, image reconstruction, image segmentation, intuitive user interface, manipulation operations, manipulators, mobile robots, RANSAC segmentation algorithm, Remote Operated Vehicles, remotely operated vehicles, robot systems, robot vision, Robots, ROV, stereo image processing, Storage tanks, Three-dimensional displays, underwater interventions, underwater manipulation autonomy, underwater robotics, underwater scenarios, underwater vehicles, user interfaces, visual tracking, Visualization, visually guided manipulation, water conditions, water tank conditions}, isbn = {978-1-5090-5278-3 }, doi = {10.1109/OCEANSE.2017.8084762}, url = {https://doi.org/10.1109/OCEANSE.2017.8084762}, author = {Fornas, David and Sanz, Pedro J. and M. Vincze} } @conference {270, title = {Improving local symmetry estimations in rgb-d images by fiting superquadrics}, booktitle = {XXXVII Jornadas de Autom{\'a}tica}, year = {2016}, month = {09/2016}, address = {Madrid (Spain)}, isbn = { 978-84-617-4298-1}, author = {Fornas, David and Sanz, Pedro J. and Porta, Josep M. and THomas, Federico} } @conference {186, title = {Improving autonomous underwater grasp specification using primitive shape fitting in point clouds}, booktitle = {Seventeenth International Conference of the Catalan Association of Artificial Intelligence (CCIA 2014)}, year = {2014}, month = {10/2014}, publisher = {IOS Press (Frontiers in Artificial Intelligence and Applications)}, organization = {IOS Press (Frontiers in Artificial Intelligence and Applications)}, address = {Barcelona (Spain)}, abstract = {
This paper presents a research in progress towards autonomous under-
water robot manipulation. Current research in underwater robotics intends to increase the autonomy of intervention operations that require physical interaction.\ 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 in various\ degrees. To tackle those 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\ primitive shape recognition algorithm, the model parameters are estimated and a\ set of feasible grasps are computed. This approach is validated in simulation and\ the quality of different 3D reconstructions from both real and virtual scenarios is\ analyzed.
}, keywords = {grasp specification, point cloud, RANSAC, shape fitting, underwater autonomous grasping, UWSim underwater realistic simulator}, isbn = {978-1-61499-451-0 (print) | 978-1-61499-452-7 (online)}, doi = {10.3233/978-1-61499-452-7-45}, author = {Fornas, David and Sales, J. and Pe{\~n}alver, Antonio and Javier P{\'e}rez and Fern{\'a}ndez, Jos{\'e} Javier and Sanz, Pedro J.} }