@article {242,
	title = {Visually-guided manipulation techniques for robotic autonomous underwater panel interventions},
	journal = {Annual Reviews in Control},
	volume = {40},
	year = {2015},
	month = {10/2015},
	chapter = {201-211},
	keywords = {3D Simulation, Autonomous Manipulation, I-AUV, Panel Intervention, Robot Kinematics, Underwater Intervention, Vision Guidance},
	issn = {1367-5788},
	doi = {10.1016/j.arcontrol.2015.09.012},
	author = {Pe{\~n}alver, Antonio and Javier P{\'e}rez and Fern{\'a}ndez, Jos{\'e} Javier and Sales, Jorge and Sanz, Pedro J. and Garc{\'\i}a, Juan Carlos and Fornas, David and Mar{\'\i}n, Ra{\'u}l}
}
@conference {5152515,
	title = {Vision-tactile-force integration and robot physical interaction},
	booktitle = {IEEE International Conference on Robotics and Automation},
	year = {2009},
	month = {05/2009},
	pages = {3975 -3980},
	address = {Kobe (Japan)},
	abstract = {<p>This paper presents an approach for integrating vision, tactile and force sensors in a robotic manipulation framework. Having an initial estimation of the object pose in the environment, a position-based visual servoing loop controls the hand for task execution, based on the input received from a model-based articular pose estimator following the Virtual Visual Servoing approach. The visual control is combined with another control signal obtained from tactile feedback, through a set of selection matrices that can be modified at runtime in order to select the best modality for a given cartesian degree of freedom. The result of the preliminary integration is modified by an impedance force controller, in charge of performing the task motion along the task direction, at the same time that forces are regulated on the rest of directions. The design of the controller allows to perform the task even if a sensor is not available or provides inaccurate data. Several experiments are performed, first by considering only force feedback, and then adding vision and, finally, tactile information. Errors in the estimation of the object initial position are manually introduced in the experiments, and results show how the vision-tactile-force combination is able to deal with them, performing much better than the vision-force and force-alone approaches.</p>
},
	issn = {1050-4729},
	doi = {10.1109/ROBOT.2009.5152515},
	author = {Prats, Mario and Sanz, Pedro J. and del Pobil, Angel P.}
}
@conference {123,
	title = {Vision-based grasp planning of 3D objects by extending 2D contour based algorithms},
	booktitle = {International Conference on Intelligent Robots and Systems},
	year = {2008},
	month = {09/2008},
	address = {Nice, France},
	isbn = {978-1-4244-2058-2},
	author = {Speth, J. and Morales, Antonio and Sanz, Pedro J.}
}
@inbook {121,
	title = {Vision-Based Grasp Tracking for Planar Objects},
	booktitle = {IEE Transactions on Systems, Man, and Cybernetics},
	volume = {38},
	year = {2008},
	chapter = {Part C, applications and reviews},
	issn = {1094-6977},
	author = {Recatal{\'a}, Gabriel and Carloni, Raffaella and Melchiori, Claudio and Sanz, Pedro J. and Cervera, Enric and del Pobil, Angel P.}
}
