@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 {179, title = {Primitive shape fitting in point clouds for enabling autonomous underwater grasping}, booktitle = {5TH MARTECH International Workshop On Marine Technology}, year = {2013}, month = {10/2013}, address = {Girona (Spain)}, abstract = {

Autonomous grasping of unknown objects by a
robot is a highly challenging skill that is receiving increasing
attention in the last years, and is still more challenging in
underwater environments, with highly unstructured scenarios,
limited availability of sensors and adverse conditions that affect
the robot perception and control systems. This paper describes
an approach for increase the autonomy of grasping operations
on underwater primitive shaped objects from floating vehicles,
in particular cylinder shaped objects like an amphora. Various
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 obtained
and a set of feasible grasps are computed. Then the user specifies
the best one or it is specified using analytical constraints. This
approach is tested with the UWSim simulator.

}, keywords = {autonomous grasping, point cloud, RANSAC, shape fitting, underwater}, isbn = {978-84-616-5764-3}, author = {Fornas, David and Pe{\~n}alver, Antonio and Prats, Mario and Fern{\'a}ndez, Jos{\'e} Javier and Sales, J.} }