Title: Multi-camera architecture for perception strategies
Authors: Enrique Hernández, Gonzalo López-Nicolás and Rosario Aragüés.
Conference: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2019), September 10-13, 2019, Zaragoza, Spain.
Abstract: Building the 3D model of an object is a complex problem that involves aspects such as modeling, control, perception or planning. Performing this task requires a set of different views to cover the entire surface of the object. Since a single camera takes too long to travel through all these positions, we consider a multi-camera scenario. Due to the camera constraints such as the limited field of view or self-occlusions, it is essential to use an effective configuration strategy to select the appropriate views that provide more information of the model. In this paper, we develop a multi-camera architecture built on the Robot Operating System. The advantages of the proposed architecture are illustrated with a formation-based algorithm to compute the view that satisfies these constraints for each robot of the formation to obtain the volumetric reconstruction of the target object.
Collaborative Robotic Mobile Manipulation of Deformable Objects in Industrial Applications