Patricio A. Vela

TL;DR: It is demonstrated that popular initialization methods often perform poorly and that there are in fact strong alternatives to these methods, and eight commonly used linear time complexity initialization methods are compared.

TL;DR: A deep learning architecture is proposed to predict graspable locations for robotic manipulation by defining the learning problem to be classified with null hypothesis competition instead of regression, the deep neural network with red, green, blue and depth image input predicts multiple grasp candidates for a single object or multiple objects, in a single shot.

TL;DR: In this paper, the authors evaluate a commercially available Ultra Wideband (UWB) system for real-time, mobile resource location tracking in harsh construction environments and demonstrate the applicability of UWB for the design of construction management support tools.

TL;DR: This paper extensively reviews these state-of-the-art vision-based construction performance monitoring methods and divides them into two categories (namely project level: visual monitoring of civil infrastructure or building elements vs. operation level:Visual monitoring of construction equipment and workers).

TL;DR: The principal objective of this paper is to test and demonstrate the feasibility of tracking workers from statically placed and dynamically moving cameras, and to review existing techniques to monitor workforce.