Publications by Inaki Navarro Oiza

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Solar Decathlon Europe is an international competition among universities which promotes interdisciplinary learning in engineering and architecture. Students from different disciplines participate in teams guided by several professors during a 29 month pre ...

In this paper we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots. We use a noise-resistant version of Particle Swarm Optimization to learn in simulation a set of 50 weights of a plastic artificial neura ...

This paper presents an overtaking decision algorithm for networked intelligent vehicles. The algorithm is based on a cooperative tracking and sensor fusion algorithm that we previously developed. The ego vehicle is equipped with lane keeping and lane chang ...

In this paper we study the automatic synthesis of robotic controllers for the coordinated movement of multiple mobile robots. The algorithm used to learn the controllers is a noise-resistant version of Particle Swarm Optimization, which is applied in two d ...

Population-based learning techniques have been proven to be effective in dealing with noise in numerical benchmark functions and are thus promising tools for the high-dimensional optimization of controllers for multiple robots with limited sensing capabili ...

Solar Decathlon Europe (SDE) is an international multidisciplinary competition in which 20 university teams build and operate energy-efficient solar-powered houses. The aim of SDE is not only scientific but also educational and divulgative, making visitors ...

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from ...

The ability to move in complex environments is a fundamental requirement for robots to be a part of our daily lives. While in simple environments it is usually straightforward for human designers to foresee the different conditions a robot will be exposed ...

Population-based learning techniques have been proven to be effective in dealing with noise and are thus promising tools for the optimization of robotic controllers, which have inherently noisy performance evaluations. This article discusses how the result ...

The first step in order to comply with the European Union goals of Near to Zero Energy Buildings is to reduce the energy consumption in buildings. Most of the building consumption is related to the use of active systems to maintain the interior comfort. Pa ...

Taking distributed robotic system research from simulation to the real world often requires the use of small robots that can be deployed and managed in large numbers. This has led to the development of a multitude of these devices, deployed in the thousand ...

The convergence of sensor-based vehicle automation and Inter-Vehicle Communication (IVC) will be a key to achieve the full automation of vehicles. In this paper we present a new method for the design and performance evaluation of Cooperative Automated Driv ...

We introduce a plume tracking algorithm based on robot formations. The algorithm is inherently designed for multi-robot systems, and requires at least two robots to collaborate. The robots try to keep themselves centered around the plume while moving upwin ...

Particle Swarm Optimization (PSO) is a meta-heuristic for solving high dimensional optimization problems. Due to the large number of dimensions usually employed with PSO, it is not trivial to visualize and monitor the progress of the algorithm. Because of ...

This paper investigates the problem of controlling a heterogeneous group of vehicles with the aim of forming multi-lane convoys. We use a distributed, graph-based control law, implemented in a longitudinal coordinate system parallel to the road. Each vehic ...

In this article we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots, as a canonical example of cooperative robotic behavior. We use five distributed noise-resistant variations of Particle Swarm Optimizat ...

The Ranger robot was designed to interact with children in order to motivate them to tidy up their room. Its mechanical configuration, together with the limited field of view of its depth camera, make the learning of obstacle avoidance behaviors a hard pro ...

This paper presents a real-time motion planning scheme for urban autonomous driving that will be deployed as a basis for cooperative maneuvers defined in the European project AutoNet2030. We use a path-velocity decomposition approach to separate the motion ...

Particle Swarm Optimization (PSO) is a population-based metaheuristic that can be applied to optimize controllers for multiple robots using only local information. In order to cope with noise in the robotic performance evaluations, different re-evaluation ...

Inaki Navarro Oiza

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Experiences and methodology in a multidisciplinary energy and architecture competition: Solar Decathlon Europe 2012

Distributed vs. Centralized Particle Swarm Optimization for Learning Flocking Behaviors

An Overtaking Decision Algorithm for Networked Intelligent Vehicles Based on Cooperative Perception

Distributed Learning of Cooperative Robotic Behaviors using Particle Swarm Optimization

A Distributed Noise-Resistant Particle Swarm Optimization Algorithm for High-Dimensional Multi-Robot Learning

Electrical energy balance contest in Solar Decathlon Europe 2012

Variable Threshold Algorithm for Division of Labor Analyzed as a Dynamical System

The Effect of the Environment in the Synthesis of Robotic Controllers: A Case Study in Multi-Robot Obstacle Avoidance using Distributed Particle Swarm Optimization

Analysis of Fitness Noise in Particle Swarm Optimization: From Robotic Learning to Benchmark Functions

Passive design strategies and performance of Net Energy Plus Houses

The Khepera IV Mobile Robot: Performance Evaluation, Sensory Data and Software Toolbox

Simulation of Cooperative Automated Driving by Bidirectional Coupling of Vehicle and Network Simulators

A Plume Tracking Algorithm Based on Crosswind Formations

SwarmViz: An Open-Source Visualization Tool for Particle Swarm Optimization

Distributed Graph-Based Control of Convoys of Heterogeneous Vehicles using Curvilinear Road Coordinates

Distributed Particle Swarm Optimization - Particle Allocation and Neighborhood Topologies for the Learning of Cooperative Robotic Behaviors

Noise-Resistant Particle Swarm Optimization for the Learning of Robust Obstacle Avoidance Controllers using a Depth Camera

Motion Planning for Urban Autonomous Driving using Bezier Curves and MPC

Distributed Particle Swarm Optimization using Optimal Computing Budget Allocation for Multi-Robot Learning

A Plume Tracking Algorithm based on Crosswind Formations