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.