Cipriano Galindo

TL;DR: A multi-hierarchical approach is presented to enable a mobile robot to acquire semantic information from its sensors, and to use it for navigation tasks, and the link between spatial and semantic information is established via anchoring.

TL;DR: This paper defines a specific type of semantic maps, which integrates hierarchical spatial information and semantic knowledge, and describes how these semantic maps can improve task planning in two ways: extending the capabilities of the planner by reasoning about semantic information, and improving the planning efficiency in large domains.

TL;DR: This work presents a thorough experimental characterization of UWB ranges within a variety of environments and situations and derives a probabilistic model which is then used by a particle filter to combine different readings from UWB beacons as well as the vehicle odometry.

TL;DR: The approach is described and the results are presented, which assess the higher motivational adequacy of using a complete robot in these subjects and also the real fulfillment of the other requirements along several academic years.

TL;DR: A predictive model based on a Bayesian Filter, a tool from the Machine Learning field, to estimate and predict the gradual degradation of such machinery, permitting the operators to make informed decisions regarding maintenance operations is described.