José Antonio López Orozco

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This paper presents a path planner for Unmanned Air Vehicles (UAVs) based on Evolutionary Algorithms (EA) that can be used in realistic risky scenarios. The path returned by the algorithm fulfills and optimizes multiple criteria which (1) are calculated based on properties of real UAVs, terrains, radars and missiles, and (2) are used to rank the solutions(More)
In this paper, a multisensor fusion system that is used for calculating the position and orientation of an autonomous mobile robot is presented. The developed fusion system is distributed, robust, and asynchronous. It is distributed to permit the parallel function of all the sensors. It is robust because, being distributed, the system has been designed to(More)
This paper presents an approach to the local stereo matching problem using edge segments as features with several attributes. We have verified that the differences in attributes for the true matches cluster in a cloud around a center. The correspondence is established on the basis of the minimum distance criterion, computing the Mahalanobis distance between(More)
This paper presents a new evolutionary planner for optimizing the input commands of multiple Unmanned Aircraft Vehicles (UAVs) in target search missions. This planner minimizes the target detection time and maximizes the UAVs performance, given 1) the uncertainty in the target location and sensor information, and 2) the UAV motion and sensorial payload(More)