Héctor Azpúrua, Ph.D.

The current state of electronic component miniaturization coupled with the increasing efficiency in hardware and software allow the development of smaller and compact robotic systems. The convenience of using these small, simple, yet capable robots has gathered the research community’s attention towards practical applications of swarm robotics. This paper presents the design of a novel platform for swarm robotics applications that is low cost, easy to assemble using off-the-shelf components… Show more

The current state of electronic component miniaturization coupled with the increasing efficiency in hardware and software allow the development of smaller and compact robotic systems. The convenience of using these small, simple, yet capable robots has gathered the research community’s attention towards practical applications of swarm robotics. This paper presents the design of a novel platform for swarm robotics applications that is low cost, easy to assemble using off-the-shelf components, and deeply integrated with the most used robotic framework available today: ROS (Robot Operating System). The robotic platform is entirely open, composed of a 3D printed body and open-source software. We describe its architecture, present its main features, and evaluate its functionalities executing experiments using a couple of robots. Results demonstrate that the proposed mobile robot is capable of performing different swarm tasks, given its small size and reduced cost, being suitable for swarm robotics research and education. Show less

One of the steps to provide fundamental data for planning a mining effort is the magnetic surveying of a target area, which is typically carried out by conventional aircraft campaigns. However, besides the high cost, fixed‐wing aerial vehicles present shortcomings especially for drape flights on mountainous regions, where steep slopes are often present. Traditional human‐crewed flights have to perform tedious and dangerous trajectories, under strict velocity and attitude constraints. In this… Show more

One of the steps to provide fundamental data for planning a mining effort is the magnetic surveying of a target area, which is typically carried out by conventional aircraft campaigns. However, besides the high cost, fixed‐wing aerial vehicles present shortcomings especially for drape flights on mountainous regions, where steep slopes are often present. Traditional human‐crewed flights have to perform tedious and dangerous trajectories, under strict velocity and attitude constraints. In this paper, we deal with the problem of accomplishing digital magnetic‐elevation maps using autonomous and cooperative aerial robots. The proposed approach for autonomous mapping utilizes a custom‐built fluxgate sensor and off the shelf cameras adapted for small airborne platforms. We also propose an innovative approach for generating a digital magnetic‐elevation model from the gathered data. Our method was evaluated and validated in field tests in an industrial scenario to detect scrap metals in ore piles. Results show that the proposed method could reliably detect magnetic anomalies while generating accurate three‐dimensional magnetic maps. Show less

The field of robotics has received significant attention in our society due to the extensive use of robotic manipulators; however, recent advances in the research on autonomous vehicles have demonstrated a broader range of applications, such as exploration, surveillance, and environmental monitoring. In this sense, the problem of efficiently building a model of the environment using cooperative mobile robots is critical. Finding routes that are either length or time-optimized is essential for… Show more

The field of robotics has received significant attention in our society due to the extensive use of robotic manipulators; however, recent advances in the research on autonomous vehicles have demonstrated a broader range of applications, such as exploration, surveillance, and environmental monitoring. In this sense, the problem of efficiently building a model of the environment using cooperative mobile robots is critical. Finding routes that are either length or time-optimized is essential for real-world applications of small autonomous robots. This paper addresses the problem of multi-robot area coverage path planning for geophysical surveys. Such surveys have many applications in mineral exploration, geology, archeology, and oceanography, among other fields. We propose a methodology that segments the environment into hexagonal cells and allocates groups of robots to different clusters of non-obstructed cells to acquire data. Cells can be covered by lawnmower, square or centroid patterns with specific configurations to address the constraints of magneto-metric surveys. Several trials were executed in a simulated environment, and a statistical investigation of the results is provided. We also report the results of experiments that were performed with real Unmanned Aerial Vehicles in an outdoor setting. Show less

Real time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model coordination as a task allocation problem, in which specific tasks must be properly assigned to agents. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. A fitness estimation method is employed to accelerate execution of the genetic algorithm. To evaluate this approach,… Show more

Real time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model coordination as a task allocation problem, in which specific tasks must be properly assigned to agents. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. A fitness estimation method is employed to accelerate execution of the genetic algorithm. To evaluate this approach, we implement this coordination mechanism in the AI of a popular video game: StarCraft: BroodWar. Experiment results show that the genetic algorithm successfully adjusts task allocation parameters. Besides, we assess the trade-off between solution quality and execution time of the genetic algorithm with fitness estimation. Show less

Recent advances on the research of autonomous vehicles have showed a vast range of applications, such as exploration, surveillance and environmental monitoring. Considering the mining industry, it is possible to use such vehicles in the prospection of minerals of commercial interest beneath the ground. However, tasks such as geophysical surveys are highly dependent on specific sensors, which mostly are not designed to be used in these new range of autonomous vehicles. In this work, we propose a… Show more

Recent advances on the research of autonomous vehicles have showed a vast range of applications, such as exploration, surveillance and environmental monitoring. Considering the mining industry, it is possible to use such vehicles in the prospection of minerals of commercial interest beneath the ground. However, tasks such as geophysical surveys are highly dependent on specific sensors, which mostly are not designed to be used in these new range of autonomous vehicles. In this work, we propose a novel magnetic survey pipeline that aims to increase versatility, speed and robustness by using autonomous rotary-wing Unmanned Aerial Vehicles (UAVs). We also discuss the development of a state-of-the-art three-axis fluxgate, where our goal in this work was to refine and adjust the sensor topology and coupled electronics specifically for this type of vehicle and application. The sensor was built with two ring-cores using a specially developed stress-annealed CoFeSiB amorphous ribbon, in order to get sufficient resolution to detect concentrations of small ferrous minerals. Finally, we report on the results of experiments performed with a real UAV in an outdoor environment, showing the efficacy of the methodology in detecting an artificial ferrous anomaly. Show less

The correct choice of strategy is crucial for a successful realtime strategy (RTS) game player. Generally speaking, a strategy
determines the sequence of actions the player will take in order to defeat his/her opponents. In this paper we present a systematic study of strategy selection in the popular RTS game StarCraft. We treat the choice of strategy as a game itself and test several strategy selection techniques, including Nash Equilibrium and safe opponent exploitation. We adopt a subset… Show more

The correct choice of strategy is crucial for a successful realtime strategy (RTS) game player. Generally speaking, a strategy
determines the sequence of actions the player will take in order to defeat his/her opponents. In this paper we present a systematic study of strategy selection in the popular RTS game StarCraft. We treat the choice of strategy as a game itself and test several strategy selection techniques, including Nash Equilibrium and safe opponent exploitation. We adopt a subset of AIIDE 2015 StarCraft AI tournament bots as the available strategies and our results suggest that it is useful to deviate from Nash Equilibrium to exploit sub-optimal opponents on strategy selection, confirming insights from computer rock-paper-scissors tournaments. Show less

It is known that the first hours after a disaster are critical to maximize the rescue and recovery of victims. However, in disaster scenarios, with the communication infrastructure damaged and cluttered environment, first responders can be in disadvantage without proper communication and global information about the mission.

In this sense, the use of aerial robots have a clear advantage over other kind of robots, since they are able to navigate over large areas faster and with a… Show more

It is known that the first hours after a disaster are critical to maximize the rescue and recovery of victims. However, in disaster scenarios, with the communication infrastructure damaged and cluttered environment, first responders can be in disadvantage without proper communication and global information about the mission.

In this sense, the use of aerial robots have a clear advantage over other kind of robots, since they are able to navigate over large areas faster and with a privileged view from above.

This paper proposes a methodology for three-dimensional area coverage using multiple small UAVs based upon a customized cell decomposition algorithm using regular hexagons.

The approach has been thoroughly evaluated in different simulated scenarios. We also report on the results of experiments performed with real UAVs in an outdoor environment. Show less

Real time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model the coordination of these agents as a task allocation problem, in which specific tasks are given to the agents that are more suited to execute them. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. To evaluate this approach, we implement this coordination mechanism in… Show more

Real time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model the coordination of these agents as a task allocation problem, in which specific tasks are given to the agents that are more suited to execute them. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. To evaluate this approach, we implement this coordination mechanism in the AI of a popular video game: StarCraft: BroodWar. Experiment results show that the genetic algorithm enhances performance of the task allocation algorithm. Besides, performance of the proposed approach in matches against StarCraft's native AI is comparable to that of a tournament-level software-controlled player for StarCraft. Show less